Analysis of Terrorist Attacts from 1970 until 2016
Introduction
The project is based on the dataset from the University of Maryland that updates a ledger of terrorist attacks globally. The link is here (https://www.kaggle.com/START-UMD/gtd). The task was to use Naive Bayes Statistics in building posterios for different periods or different geographic areas, and impute the missing data for 1993.
I also added data from other sources, global population and oil price for the same years.
Preliminary Findings
You can see on graphs below that the number of terrorist attacks for Chechnya after the second Military Campaign in Chechnya pushed the terrorist activities to the neighbouring republics of Ingushetia and Dagestan. At the same time, if one looks at the map of the main oil pipelines and reading more on the subject and financing of the terrorist activity in the region it becomes clear that oil has been a definite source of criminal activity in the region.
I also compared the correlation for the global oil price vs terrorist activity and it becomes significant with data shift by 2 - 5 years. That speaks for accumulative effect of oil trades on criminal activities in the regions of Russian and globally.
In [2]:
import pandas as pd
import numpy as np
import matplotlib as plt
In [6]:
%matplotlib inline
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import datetime
from dateutil.relativedelta import relativedelta
import seaborn as sns
import statsmodels.api as sm
from statsmodels.tsa.stattools import acf
from statsmodels.tsa.stattools import pacf
from statsmodels.tsa.seasonal import seasonal_decompose
from datetime import datetime
from urllib import urlretrieve
from zipfile import ZipFile
import pysal
from pandas.core import datetools
In [9]:
df = pd.read_csv('../../../../Google_Drive/GA_project_data/project_5/globalterrorismdb_0617dist.csv', low_memory=False)
In [10]:
def eda(dataframe):
print "missing values \n", dataframe.isnull().sum()
print "dataframe index \n", dataframe.index
print "dataframe types \n", dataframe.dtypes
print "dataframe shape \n", dataframe.shape
print "dataframe describe \n", dataframe.describe()
for item in dataframe:
print item
print dataframe[item].nunique()
eda(df)
missing values
eventid 0
iyear 0
imonth 0
iday 0
approxdate 162886
extended 0
resolution 168131
country 0
country_txt 0
region 0
region_txt 0
provstate 14502
city 446
latitude 4606
longitude 4606
specificity 4
vicinity 0
location 122376
summary 66138
crit1 0
crit2 0
crit3 0
doubtterr 0
alternative 143719
alternative_txt 143719
multiple 0
success 0
suicide 0
attacktype1 0
attacktype1_txt 0
...
propextent 109805
propextent_txt 109805
propvalue 134863
propcomment 115919
ishostkid 178
nhostkid 157858
nhostkidus 157913
nhours 166649
ndays 162942
divert 170037
kidhijcountry 167051
ransom 94037
ransomamt 169071
ransomamtus 169854
ransompaid 169643
ransompaidus 169863
ransomnote 169879
hostkidoutcome 160439
hostkidoutcome_txt 160439
nreleased 161028
addnotes 144911
scite1 66200
scite2 100765
scite3 131133
dbsource 0
INT_LOG 0
INT_IDEO 0
INT_MISC 0
INT_ANY 0
related 147505
Length: 135, dtype: int64
dataframe index
RangeIndex(start=0, stop=170350, step=1)
dataframe types
eventid int64
iyear int64
imonth int64
iday int64
approxdate object
extended int64
resolution object
country int64
country_txt object
region int64
region_txt object
provstate object
city object
latitude float64
longitude float64
specificity float64
vicinity int64
location object
summary object
crit1 int64
crit2 int64
crit3 int64
doubtterr int64
alternative float64
alternative_txt object
multiple int64
success int64
suicide int64
attacktype1 int64
attacktype1_txt object
...
propextent float64
propextent_txt object
propvalue float64
propcomment object
ishostkid float64
nhostkid float64
nhostkidus float64
nhours float64
ndays float64
divert object
kidhijcountry object
ransom float64
ransomamt float64
ransomamtus float64
ransompaid float64
ransompaidus float64
ransomnote object
hostkidoutcome float64
hostkidoutcome_txt object
nreleased float64
addnotes object
scite1 object
scite2 object
scite3 object
dbsource object
INT_LOG int64
INT_IDEO int64
INT_MISC int64
INT_ANY int64
related object
Length: 135, dtype: object
dataframe shape
(170350, 135)
dataframe describe
eventid iyear imonth iday \
count 1.703500e+05 170350.000000 170350.000000 170350.000000
mean 2.001776e+11 2001.709997 6.474365 15.466845
std 1.314444e+09 13.144146 3.392364 8.817929
min 1.970000e+11 1970.000000 0.000000 0.000000
25% 1.990053e+11 1990.000000 4.000000 8.000000
50% 2.007121e+11 2007.000000 6.000000 15.000000
75% 2.014023e+11 2014.000000 9.000000 23.000000
max 2.017013e+11 2016.000000 12.000000 31.000000
extended country region latitude \
count 170350.000000 170350.000000 170350.000000 165744.000000
mean 0.043634 132.526669 7.091441 23.399774
std 0.204279 112.848161 2.949206 18.844885
min 0.000000 4.000000 1.000000 -53.154613
25% 0.000000 75.000000 5.000000 11.263580
50% 0.000000 98.000000 6.000000 31.472680
75% 0.000000 160.000000 10.000000 34.744167
max 1.000000 1004.000000 12.000000 74.633553
longitude specificity ... ransomamt \
count 165744.000000 170346.000000 ... 1.279000e+03
mean 26.350909 1.454428 ... 3.224502e+06
std 58.570068 1.009005 ... 3.090625e+07
min -176.176447 1.000000 ... -9.900000e+01
25% 2.396199 1.000000 ... 0.000000e+00
50% 43.130000 1.000000 ... 1.420000e+04
75% 68.451297 1.000000 ... 4.000000e+05
max 179.366667 5.000000 ... 1.000000e+09
ransomamtus ransompaid ransompaidus hostkidoutcome nreleased \
count 4.960000e+02 7.070000e+02 487.000000 9911.000000 9322.000000
mean 4.519918e+05 3.849663e+05 272.462012 4.624458 -28.717335
std 6.070186e+06 2.435027e+06 3130.068208 2.041008 58.737198
min -9.900000e+01 -9.900000e+01 -99.000000 1.000000 -99.000000
25% 0.000000e+00 -9.900000e+01 0.000000 2.000000 -99.000000
50% 0.000000e+00 0.000000e+00 0.000000 4.000000 0.000000
75% 0.000000e+00 7.356800e+02 0.000000 7.000000 1.000000
max 1.320000e+08 4.100000e+07 48000.000000 7.000000 1201.000000
INT_LOG INT_IDEO INT_MISC INT_ANY
count 170350.000000 170350.000000 170350.000000 170350.000000
mean -4.583387 -4.510555 0.091083 -3.975128
std 4.542694 4.630440 0.583166 4.691492
min -9.000000 -9.000000 -9.000000 -9.000000
25% -9.000000 -9.000000 0.000000 -9.000000
50% -9.000000 -9.000000 0.000000 0.000000
75% 0.000000 0.000000 0.000000 0.000000
max 1.000000 1.000000 1.000000 1.000000
[8 rows x 77 columns]
eventid
170350
iyear
46
imonth
13
iday
32
approxdate
1833
extended
2
resolution
1859
country
205
country_txt
205
region
12
region_txt
12
provstate
2494
city
33957
latitude
61028
longitude
60602
specificity
5
vicinity
3
location
39816
summary
101538
crit1
2
crit2
2
crit3
2
doubtterr
3
alternative
5
alternative_txt
5
multiple
2
success
2
suicide
2
attacktype1
9
attacktype1_txt
9
attacktype2
9
attacktype2_txt
9
attacktype3
7
attacktype3_txt
7
targtype1
22
targtype1_txt
22
targsubtype1
110
targsubtype1_txt
110
corp1
31300
target1
82975
natlty1
213
natlty1_txt
213
targtype2
22
targtype2_txt
22
targsubtype2
97
targsubtype2_txt
97
corp2
2474
target2
4790
natlty2
156
natlty2_txt
156
targtype3
20
targtype3_txt
20
targsubtype3
89
targsubtype3_txt
89
corp3
376
target3
665
natlty3
104
natlty3_txt
104
gname
3454
gsubname
1098
gname2
383
gsubname2
58
gname3
103
gsubname3
13
motive
13033
guncertain1
2
guncertain2
2
guncertain3
2
individual
2
nperps
112
nperpcap
50
claimed
3
claimmode
10
claimmode_txt
10
claim2
3
claimmode2
9
claimmode2_txt
9
claim3
2
claimmode3
8
claimmode3_txt
8
compclaim
3
weaptype1
12
weaptype1_txt
12
weapsubtype1
29
weapsubtype1_txt
29
weaptype2
11
weaptype2_txt
11
weapsubtype2
28
weapsubtype2_txt
28
weaptype3
10
weaptype3_txt
10
weapsubtype3
23
weapsubtype3_txt
23
weaptype4
5
weaptype4_txt
5
weapsubtype4
16
weapsubtype4_txt
16
weapdetail
18246
nkill
199
nkillus
30
nkillter
90
nwound
233
nwoundus
44
nwoundte
42
property
3
propextent
4
propextent_txt
4
propvalue
640
propcomment
18344
ishostkid
3
nhostkid
202
nhostkidus
27
nhours
35
ndays
313
divert
143
kidhijcountry
217
ransom
3
ransomamt
395
ransomamtus
22
ransompaid
136
ransompaidus
8
ransomnote
345
hostkidoutcome
7
hostkidoutcome_txt
7
nreleased
150
addnotes
14150
scite1
75887
scite2
56562
scite3
32562
dbsource
26
INT_LOG
3
INT_IDEO
3
INT_MISC
3
INT_ANY
3
related
20829
In [11]:
for i in df.columns:
print i, '\n'
print type(df[i][10])
print len(df[i].unique())
print df[i].unique()
print '========'
eventid
<type 'numpy.int64'>
170350
[197000000001 197000000002 197001000001 ..., 201612310043 201612310044
201701270001]
========
iyear
<type 'numpy.int64'>
46
[1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1986 1982 1983
1984 1985 1987 1988 1989 1990 1991 1992 1994 1995 1996 1997 1998 1999 2000
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
2016]
========
imonth
<type 'numpy.int64'>
13
[ 7 0 1 2 3 4 5 6 8 9 10 11 12]
========
iday
<type 'numpy.int64'>
32
[ 2 0 1 3 6 8 9 10 11 12 13 14 15 19 20 21 22 25 26 27 28 30 31 4 7
16 17 18 23 24 5 29]
========
approxdate
<type 'float'>
1834
[nan 'January 19-20, 1970' 'February 6-9, 1970' ..., '2016-12-28 00:00:00'
'December 26-31, 2016' '2016-12-31 00:00:00']
========
extended
<type 'numpy.int64'>
2
[0 1]
========
resolution
<type 'float'>
1860
[nan '3/8/1970' '3/15/1970' ..., '12/2/2011' '12/9/2011' '12/27/2011']
========
country
<type 'numpy.int64'>
205
[ 58 130 160 78 101 217 218 98 499 65 83 222 362 199 102
185 30 60 11 110 96 209 158 94 603 45 26 145 142 21
97 38 14 153 230 198 49 406 36 201 156 106 155 15 236
92 69 428 6 61 205 87 195 136 53 138 4 159 43 88
235 59 144 604 162 121 178 29 100 42 377 7 200 184 215
183 104 95 182 203 186 139 17 20 207 19 605 8 128 173
56 93 124 403 359 55 349 86 137 208 213 151 161 111 72
113 18 147 89 174 231 84 80 532 22 81 127 221 5 41
176 57 164 32 196 197 116 91 70 66 33 143 166 146 141
204 68 67 76 129 90 108 157 44 112 47 123 75 228 168
177 37 51 50 74 16 119 115 34 214 132 12 167 99 103
10 28 62 202 120 219 109 31 64 223 46 23 179 118 226
35 54 180 73 149 63 189 71 117 107 220 229 1003 181 347
190 85 1002 422 210 175 122 25 1001 1004]
========
country_txt
<type 'str'>
205
['Dominican Republic' 'Mexico' 'Philippines' 'Greece' 'Japan'
'United States' 'Uruguay' 'Italy' 'East Germany (GDR)' 'Ethiopia'
'Guatemala' 'Venezuela' 'West Germany (FRG)' 'Switzerland' 'Jordan'
'Spain' 'Brazil' 'Egypt' 'Argentina' 'Lebanon' 'Ireland' 'Turkey'
'Paraguay' 'Iran' 'United Kingdom' 'Colombia' 'Bolivia' 'Nicaragua'
'Netherlands' 'Belgium' 'Israel' 'Canada' 'Australia' 'Pakistan' 'Zambia'
'Sweden' 'Costa Rica' 'South Yemen' 'Cambodia' 'Taiwan' 'Panama' 'Kuwait'
'West Bank and Gaza Strip' 'Austria' 'Czechoslovakia' 'India' 'France'
'South Vietnam' 'Algeria' 'El Salvador' 'Thailand' 'Haiti' 'Sudan'
'Morocco' 'Cyprus' 'Myanmar' 'Afghanistan' 'Peru' 'Chile' 'Honduras'
'Yugoslavia' 'Ecuador' 'New Zealand' 'Zaire' 'Portugal' 'Malaysia'
'Singapore' 'Botswana' 'Jamaica' 'Chad' 'North Yemen' 'Andorra' 'Syria'
'South Korea' 'United Arab Emirates' 'South Africa' 'Kenya' 'Iraq'
'Somalia' 'Tanzania' 'Sri Lanka' 'Namibia' 'Bahamas' 'Barbados'
'Trinidad and Tobago' 'Bangladesh' "People's Republic of the Congo"
'Angola' 'Mauritania' 'Saudi Arabia' 'Djibouti' 'Indonesia' 'Malta'
'Rhodesia' 'Soviet Union' 'Denmark' 'Western Sahara' 'Guyana' 'Mozambique'
'Tunisia' 'Uganda' 'Norway' 'Poland' 'Lesotho' 'Gabon' 'Libya' 'Bahrain'
'Nigeria' 'Hong Kong' 'Senegal' 'Zimbabwe' 'Guinea' 'Grenada'
'New Hebrides' 'Belize' 'Guadeloupe' 'Martinique' 'Vatican City' 'Albania'
'Central African Republic' 'Seychelles' 'Dominica' 'Qatar' 'Bulgaria'
'Suriname' 'Swaziland' 'Luxembourg' 'Iceland' 'French Guiana'
'Falkland Islands' 'Burkina Faso' 'New Caledonia' 'Romania' 'Niger'
'Nepal' 'Togo' 'Finland' 'Fiji' 'Ghana' 'Mauritius' 'Hungary' 'Laos'
'Papua New Guinea' 'China' 'Liberia' 'Republic of the Congo' 'Mali'
'Germany' 'Yemen' 'Rwanda' 'Sierra Leone' 'Cameroon' 'Cuba' 'Croatia'
'Georgia' 'Azerbaijan' 'Madagascar' 'Lithuania' 'Burundi' 'Ukraine'
'Moldova' 'Armenia' 'Russia' 'Ivory Coast' 'Kazakhstan'
'Antigua and Barbuda' 'Bosnia-Herzegovina' 'Equatorial Guinea'
'Tajikistan' 'Malawi' 'Uzbekistan' 'Latvia' 'Brunei' 'Estonia' 'Vietnam'
'Comoros' 'Benin' 'Slovak Republic' 'Macedonia' 'Wallis and Futuna'
'Belarus' 'Czech Republic' 'Slovenia' 'Gambia' 'North Korea' 'Eritrea'
'St. Kitts and Nevis' 'French Polynesia' 'Macau' 'Kyrgyzstan' 'Vanuatu'
'Democratic Republic of the Congo' 'Kosovo' 'Solomon Islands' 'East Timor'
'St. Lucia' 'Guinea-Bissau' 'Montenegro' 'International' 'Turkmenistan'
'Serbia-Montenegro' 'Maldives' 'Bhutan' 'Serbia' 'South Sudan']
========
region
<type 'numpy.int64'>
12
[ 2 1 5 8 4 3 9 11 10 12 6 7]
========
region_txt
<type 'str'>
12
['Central America & Caribbean' 'North America' 'Southeast Asia'
'Western Europe' 'East Asia' 'South America' 'Eastern Europe'
'Sub-Saharan Africa' 'Middle East & North Africa' 'Australasia & Oceania'
'South Asia' 'Central Asia']
========
provstate
<type 'str'>
2495
[nan 'Tarlac' 'Attica' ..., 'Equator' 'Karak' 'Mongala']
========
city
<type 'str'>
33958
['Santo Domingo' 'Mexico city' 'Unknown' ..., 'Garoua' 'Nakolongbo'
'Guachochi']
========
latitude
<type 'numpy.float64'>
61029
[ 18.456792 19.432608 15.478598 ..., 7.027067 4.308611 26.819644]
========
longitude
<type 'numpy.float64'>
60603
[ -69.951164 -99.133207 120.599741 ..., 124.386552 25.091389
-107.069898]
========
specificity
<type 'numpy.float64'>
6
[ 1. 4. 5. 2. 3. nan]
========
vicinity
<type 'numpy.int64'>
3
[ 0 1 -9]
========
location
<type 'float'>
39817
[nan 'Edes Substation' 'Caparra Shopping Center' ...,
'The incident occurred in the Sinak area of the Rusafa neighborhood.'
'The incident occurred in the New Baghdad area of the 9 Nissan neighborhood.'
'The incident occurred in Jakdalk district.']
========
summary
<type 'float'>
101539
[nan
'1/1/1970: Unknown African American assailants fired several bullets at police headquarters in Cairo, Illinois, United States. There were no casualties, however, one bullet narrowly missed several police officers. This attack took place during heightened racial tensions, including a Black boycott of White-owned businesses, in Cairo Illinois.'
'1/2/1970: Unknown perpetrators detonated explosives at the Pacific Gas & Electric Company Edes substation in Oakland, California, United States. Three transformers were damaged costing an estimated $20,000 to $25,000. There were no casualties.'
...,
"12/31/2016: Assailants attacked a village and abducted 33 civilians in Nakolongbo, Bas-Uele, Democratic Republic of the Congo. The hostages were rescued by security forces on January 8, 2017. No group claimed responsibility for the incident; however, sources attributed the attack to the Lord's Resistance Army (LRA)."
'12/31/2016: Assailants opened fire on the house of Gabriel Valencia Juarez in Chihuahua, Mexico. Juarez, a journalist, was not harmed in the attack. No group claimed responsibility for the incident.'
'12/30/2016: Assailants armed with firearms attacked Nertiti, Central Darfur, Sudan. At least three people, including a soldier, were killed and 47 others were wounded in ensuing clashes. No group claimed responsibility; however, sources suspected that the attack was carried out by the Sudan Liberation Movement, which denied involvement.']
========
crit1
<type 'numpy.int64'>
2
[1 0]
========
crit2
<type 'numpy.int64'>
2
[1 0]
========
crit3
<type 'numpy.int64'>
2
[1 0]
========
doubtterr
<type 'numpy.int64'>
3
[ 0 -9 1]
========
alternative
<type 'numpy.float64'>
6
[ nan 2. 1. 3. 5. 4.]
========
alternative_txt
<type 'str'>
6
[nan 'Other Crime Type' 'Insurgency/Guerilla Action'
'Intra/Inter-group Conflict' 'State Actors' 'Lack of Intentionality']
========
multiple
<type 'numpy.int64'>
2
[0 1]
========
success
<type 'numpy.int64'>
2
[1 0]
========
suicide
<type 'numpy.int64'>
2
[0 1]
========
attacktype1
<type 'numpy.int64'>
9
[1 6 3 7 2 4 9 8 5]
========
attacktype1_txt
<type 'str'>
9
['Assassination' 'Hostage Taking (Kidnapping)' 'Bombing/Explosion'
'Facility/Infrastructure Attack' 'Armed Assault' 'Hijacking' 'Unknown'
'Unarmed Assault' 'Hostage Taking (Barricade Incident)']
========
attacktype2
<type 'numpy.float64'>
10
[ nan 2. 7. 3. 6. 1. 4. 5. 9. 8.]
========
attacktype2_txt
<type 'float'>
10
[nan 'Armed Assault' 'Facility/Infrastructure Attack' 'Bombing/Explosion'
'Hostage Taking (Kidnapping)' 'Assassination' 'Hijacking'
'Hostage Taking (Barricade Incident)' 'Unknown' 'Unarmed Assault']
========
attacktype3
<type 'numpy.float64'>
8
[ nan 2. 4. 7. 3. 6. 1. 5.]
========
attacktype3_txt
<type 'float'>
8
[nan 'Armed Assault' 'Hijacking' 'Facility/Infrastructure Attack'
'Bombing/Explosion' 'Hostage Taking (Kidnapping)' 'Assassination'
'Hostage Taking (Barricade Incident)']
========
targtype1
<type 'numpy.int64'>
22
[14 7 10 3 21 4 2 6 1 8 22 15 20 19 18 12 16 9 17 13 11 5]
========
targtype1_txt
<type 'str'>
22
['Private Citizens & Property' 'Government (Diplomatic)'
'Journalists & Media' 'Police' 'Utilities' 'Military'
'Government (General)' 'Airports & Aircraft' 'Business'
'Educational Institution' 'Violent Political Party'
'Religious Figures/Institutions' 'Unknown' 'Transportation' 'Tourists'
'NGO' 'Telecommunication' 'Food or Water Supply'
'Terrorists/Non-State Militia' 'Other' 'Maritime' 'Abortion Related']
========
targsubtype1
<type 'numpy.float64'>
111
[ 68. 45. 54. 46. 22. 25. 107. 28. 21. 27. 42. 7.
nan 34. 49. 4. 110. 76. 71. 14. 23. 86. 73. 99.
15. 8. 44. 3. 12. 96. 100. 69. 1. 53. 32. 17.
11. 82. 2. 81. 18. 79. 5. 62. 67. 84. 90. 43.
52. 77. 35. 61. 88. 9. 93. 29. 64. 50. 78. 10.
108. 6. 75. 80. 47. 87. 95. 89. 56. 55. 109. 104.
59. 98. 97. 16. 57. 106. 37. 31. 105. 48. 85. 58.
94. 74. 26. 102. 101. 103. 20. 70. 40. 19. 92. 72.
51. 13. 60. 24. 83. 65. 39. 36. 111. 41. 91. 63.
30. 66. 33.]
========
targsubtype1_txt
<type 'str'>
111
['Named Civilian' 'Diplomatic Personnel (outside of embassy, consulate)'
'Radio Journalist/Staff/Facility' 'Embassy/Consulate'
'Police Building (headquarters, station, school)'
'Police Security Forces/Officers' 'Electricity'
'Military Recruiting Station/Academy'
'Government Building/Facility/Office'
'Military Barracks/Base/Headquarters/Checkpost'
'Aircraft (not at an airport)' 'Retail/Grocery/Bakery' nan
'Military Personnel (soldiers, troops, officers, forces)'
'School/University/Educational Building' 'Multinational Corporation'
'Party Office/Facility' 'House/Apartment/Residence'
'Race/Ethnicity Identified' 'Judge/Attorney/Court'
'Police Patrol (including vehicles and convoys)' 'Place of Worship'
'Vehicles/Transportation' 'Bus (excluding tourists)'
'Politician or Political Party Movement/Meeting/Rally' 'Hotel/Resort'
'Airport' 'Bank/Commerce' 'Construction' 'Tour Bus/Van'
'Train/Train Tracks/Trolley' 'Religion Identified' 'Gas/Oil'
'Newspaper Journalist/Staff/Facility' 'Military Maritime' 'Head of State'
'Entertainment/Cultural/Stadium/Casino' 'Labor Union Related'
'Restaurant/Bar/Caf\xe9' 'Museum/Cultural Center/Cultural House'
'Government Personnel (excluding police, military)'
'Public Area (garden, parking lot, garage, beach, public building, camp)'
'Industrial/Textiles/Factory' 'International NGO'
'Unnamed Civilian/Unspecified' 'Political Party Member/Rally'
'Telephone/Telegraph' 'Airline Officer/Personnel' 'Water Supply'
'Laborer (General)/Occupation Identified'
'Military Transportation/Vehicle (excluding convoys)' 'Domestic NGO'
'Radio' 'Farm/Ranch' 'Terrorist' 'Military Unit/Patrol/Convoy'
'Fire Fighter/Truck' 'Other Personnel'
'Procession/Gathering (funeral, wedding, birthday, religious)' 'Mining'
'Oil' 'Medical/Pharmaceutical' 'Village/City/Town/Suburb'
'Memorial/Cemetery/Monument'
'International Organization (peacekeeper, aid agency, compound)'
'Affiliated Institution' 'Tourism Travel Agency' 'Television'
'Other (including online news agencies)'
'Television Journalist/Staff/Facility'
'Party Official/Candidate/Other Personnel'
'Highway/Road/Toll/Traffic Signal' 'Oil Tanker' 'Other Facility' 'Tourist'
'Royalty' 'Civilian Maritime' 'Gas' 'NATO' 'Military Aircraft'
'Taxi/Rickshaw' 'Teacher/Professor/Instructor' 'Religious Figure'
'Commercial Maritime' 'Non-State Militia' 'Marketplace/Plaza/Square'
'Prison/Jail' 'Subway' 'Bus Station/Stop' 'Bridge/Car Tunnel'
'Intelligence' 'Student' 'Clinics' 'Election-related'
'Multiple Telecommunication Targets' 'Farmer' 'Food Supply'
'Private Security Company/Firm' 'Port' 'Police Checkpoint' 'Protester'
'Refugee Camp' 'Paramilitary' 'Military Checkpoint' 'Rally' 'Personnel'
'Internet Infrastructure' 'Ambulance' 'Military Weaponry'
'Demilitarized Zone (including Green Zone)' 'Non-combatant Personnel']
========
corp1
<type 'float'>
31301
[nan 'Belgian Ambassador Daughter' 'Voice of America' ...,
'Nakolongbo Village' 'Norawa' 'Nierteti Town']
========
target1
<type 'str'>
82976
['Julio Guzman' 'Nadine Chaval, daughter' 'Employee' ...,
'Deputy Head: Mohammad Esa' 'Convoy of Relief Workers'
'Residence of Journalist: Gabriel Valencia Juarez']
========
natlty1
<type 'numpy.float64'>
214
[ 58. 21. 217. 218. 75. 216. 222. 163. 97. 15.
199. 102. 65. 185. nan 101. 422. 60. 158. 359.
96. 11. 160. 44. 155. 999. 233. 30. 87. 183.
162. 45. 78. 145. 93. 235. 98. 403. 99. 94.
38. 161. 198. 209. 49. 167. 95. 51. 69. 120.
229. 142. 43. 89. 228. 130. 200. 92. 144. 174.
6. 159. 236. 173. 55. 362. 17. 26. 61. 29.
83. 110. 149. 5. 184. 153. 104. 53. 156. 186.
59. 121. 136. 182. 139. 12. 20. 106. 137. 147.
86. 201. 208. 138. 207. 128. 32. 205. 18. 68.
223. 215. 124. 14. 231. 230. 8. 151. 100. 213.
50. 111. 203. 84. 67. 56. 113. 63. 4. 88.
604. 123. 19. 80. 220. 22. 377. 166. 195. 42.
41. 112. 176. 57. 605. 46. 196. 221. 115. 81.
127. 349. 197. 33. 125. 143. 36. 178. 238. 116.
146. 141. 90. 204. 91. 520. 76. 129. 157. 164.
168. 37. 64. 177. 109. 79. 28. 119. 34. 16.
103. 74. 10. 351. 214. 132. 62. 202. 108. 31.
219. 175. 47. 72. 179. 118. 134. 23. 35. 152.
54. 73. 334. 1001. 189. 107. 117. 180. 70. 347.
1003. 181. 190. 85. 1002. 25. 122. 24. 192. 1004.
603. 210. 169. 212.]
========
natlty1_txt
<type 'str'>
214
['Dominican Republic' 'Belgium' 'United States' 'Uruguay' 'Germany'
'Great Britain' 'Venezuela' 'Puerto Rico' 'Israel' 'Austria' 'Switzerland'
'Jordan' 'Ethiopia' 'Spain' nan 'Japan' 'International' 'Egypt' 'Paraguay'
'Soviet Union' 'Ireland' 'Argentina' 'Philippines' 'China'
'West Bank and Gaza Strip' 'Multinational' 'Northern Ireland' 'Brazil'
'Haiti' 'South Africa' 'Portugal' 'Colombia' 'Greece' 'Nicaragua'
'Indonesia' 'Yugoslavia' 'Italy' 'Rhodesia' 'Ivory Coast' 'Iran' 'Canada'
'Poland' 'Sweden' 'Turkey' 'Costa Rica' 'Russia' 'Iraq' 'Cuba' 'France'
'Malawi' 'Democratic Republic of the Congo' 'Netherlands' 'Chile'
'Hong Kong' 'Yemen' 'Mexico' 'Syria' 'India' 'New Zealand' 'Senegal'
'Algeria' 'Peru' 'Czechoslovakia' 'Saudi Arabia' 'Denmark'
'West Germany (FRG)' 'Bahamas' 'Bolivia' 'El Salvador' 'Botswana'
'Guatemala' 'Lebanon' 'North Korea' 'Albania' 'South Korea' 'Pakistan'
'Kenya' 'Cyprus' 'Panama' 'Sri Lanka' 'Ecuador' 'Malaysia' 'Morocco'
'Somalia' 'Namibia' 'Armenia' 'Barbados' 'Kuwait' 'Mozambique' 'Nigeria'
'Guyana' 'Taiwan' 'Tunisia' 'Myanmar' 'Trinidad and Tobago' 'Mauritania'
'Bulgaria' 'Thailand' 'Bahrain' 'Finland' 'Vietnam' 'United Arab Emirates'
'Malta' 'Australia' 'Zimbabwe' 'Zambia' 'Angola' 'Norway' 'Jamaica'
'Uganda' 'Croatia' 'Lesotho' 'Tanzania' 'Guinea' 'Fiji' 'Djibouti' 'Libya'
'Eritrea' 'Afghanistan' 'Honduras' 'Zaire' 'Mali' 'Bangladesh' 'Grenada'
'Vanuatu' 'Belize' 'North Yemen' 'Romania' 'Sudan' 'Chad'
'Central African Republic' 'Liberia' 'Seychelles' 'Dominica'
"People's Republic of the Congo" 'Comoros' 'Suriname' 'Vatican City'
'Lithuania' 'Guadeloupe' 'Martinique' 'Western Sahara' 'Swaziland'
'Burkina Faso' 'Man, Isle of' 'New Caledonia' 'Cambodia' 'Singapore'
'Corsica' 'Luxembourg' 'Niger' 'Nepal' 'Hungary' 'Togo' 'Iceland'
'Sinhalese' 'Ghana' 'Mauritius' 'Papua New Guinea' 'Qatar' 'Rwanda'
'Cameroon' 'Estonia' 'Sierra Leone' 'Latvia' 'Greenland'
'Bosnia-Herzegovina' 'Madagascar' 'Burundi' 'Azerbaijan' 'Kazakhstan'
'Georgia' 'Antigua and Barbuda' 'Commonwealth of Independent States'
'Ukraine' 'Moldova' 'Equatorial Guinea' 'Tajikistan' 'Laos' 'Brunei'
'Uzbekistan' 'Serbia-Montenegro' 'Republic of the Congo' 'Gabon'
'Slovak Republic' 'Macedonia' 'Mongolia' 'Benin' 'Belarus' 'Oman'
'Czech Republic' 'Gambia' 'Asian' 'Serbia' 'St. Kitts and Nevis'
'Kyrgyzstan' 'Macau' 'Slovenia' 'French Guiana' 'East Timor' 'Kosovo'
'Solomon Islands' 'St. Lucia' 'Guinea-Bissau' 'Montenegro' 'Bhutan'
'Maldives' 'Bermuda' 'St. Martin' 'South Sudan' 'United Kingdom'
'Turkmenistan' 'Saba (Netherlands Antilles)' 'Tuvalu']
========
targtype2
<type 'numpy.float64'>
23
[ nan 3. 8. 20. 1. 14. 2. 16. 21. 6. 4. 7. 15. 17. 19.
10. 18. 22. 12. 11. 5. 13. 9.]
========
targtype2_txt
<type 'float'>
23
[nan 'Police' 'Educational Institution' 'Unknown' 'Business'
'Private Citizens & Property' 'Government (General)' 'Telecommunication'
'Utilities' 'Airports & Aircraft' 'Military' 'Government (Diplomatic)'
'Religious Figures/Institutions' 'Terrorists/Non-State Militia'
'Transportation' 'Journalists & Media' 'Tourists'
'Violent Political Party' 'NGO' 'Maritime' 'Abortion Related' 'Other'
'Food or Water Supply']
========
targsubtype2
<type 'numpy.float64'>
98
[ nan 25. 50. 2. 70. 5. 15. 68. 77. 67. 88. 22.
49. 1. 23. 69. 107. 79. 78. 34. 46. 45. 28. 85.
87. 21. 48. 93. 71. 18. 7. 99. 3. 54. 72. 89.
37. 108. 84. 4. 98. 100. 82. 9. 62. 43. 61. 53.
97. 92. 106. 73. 10. 11. 35. 57. 27. 86. 75. 96.
55. 12. 8. 81. 40. 42. 101. 76. 29. 6. 26. 47.
64. 17. 109. 60. 74. 14. 51. 104. 19. 102. 20. 52.
39. 36. 13. 24. 56. 103. 65. 90. 94. 58. 44. 63.
105. 16.]
========
targsubtype2_txt
<type 'float'>
98
[nan 'Police Security Forces/Officers' 'Other Personnel'
'Restaurant/Bar/Caf\xe9' 'Student' 'Industrial/Textiles/Factory'
'Politician or Political Party Movement/Meeting/Rally' 'Named Civilian'
'Laborer (General)/Occupation Identified' 'Unnamed Civilian/Unspecified'
'Radio' 'Police Building (headquarters, station, school)'
'School/University/Educational Building' 'Gas/Oil'
'Police Patrol (including vehicles and convoys)' 'Religion Identified'
'Electricity'
'Public Area (garden, parking lot, garage, beach, public building, camp)'
'Procession/Gathering (funeral, wedding, birthday, religious)'
'Military Personnel (soldiers, troops, officers, forces)'
'Embassy/Consulate' 'Diplomatic Personnel (outside of embassy, consulate)'
'Military Recruiting Station/Academy' 'Religious Figure'
'Affiliated Institution' 'Government Building/Facility/Office'
'Teacher/Professor/Instructor' 'Terrorist' 'Race/Ethnicity Identified'
'Government Personnel (excluding police, military)'
'Retail/Grocery/Bakery' 'Bus (excluding tourists)' 'Bank/Commerce'
'Radio Journalist/Staff/Facility' 'Farmer' 'Television' 'NATO' 'Oil'
'Political Party Member/Rally' 'Multinational Corporation'
'Other Facility' 'Train/Train Tracks/Trolley' 'Labor Union Related'
'Farm/Ranch' 'International NGO' 'Airline Officer/Personnel'
'Domestic NGO' 'Newspaper Journalist/Staff/Facility' 'Tourist'
'Multiple Telecommunication Targets' 'Gas' 'Vehicles/Transportation'
'Mining' 'Entertainment/Cultural/Stadium/Casino'
'Military Transportation/Vehicle (excluding convoys)' 'Civilian Maritime'
'Military Barracks/Base/Headquarters/Checkpost' 'Place of Worship'
'Village/City/Town/Suburb' 'Tour Bus/Van'
'Television Journalist/Staff/Facility' 'Construction' 'Hotel/Resort'
'Museum/Cultural Center/Cultural House' 'Clinics'
'Aircraft (not at an airport)' 'Bus Station/Stop'
'House/Apartment/Residence' 'Military Unit/Patrol/Convoy'
'Medical/Pharmaceutical' 'Prison/Jail'
'International Organization (peacekeeper, aid agency, compound)'
'Fire Fighter/Truck' 'Head of State'
'Party Official/Candidate/Other Personnel' 'Port'
'Marketplace/Plaza/Square' 'Judge/Attorney/Court' 'Food Supply'
'Highway/Road/Toll/Traffic Signal' 'Election-related' 'Subway'
'Intelligence' 'Water Supply' 'Paramilitary' 'Military Checkpoint'
'Private Security Company/Firm' 'Police Checkpoint'
'Other (including online news agencies)' 'Bridge/Car Tunnel'
'Refugee Camp' 'Telephone/Telegraph' 'Non-State Militia'
'Commercial Maritime' 'Airport' 'Ambulance' 'Taxi/Rickshaw' 'Royalty']
========
corp2
<type 'float'>
2475
[nan 'Fraternal Order of Police' 'San Francisco State College' ...,
'Special Task Force (STF)' 'General Citizenship Department'
'Government of Khalabat']
========
target2
<type 'float'>
4791
[nan 'Fraternal Order of Police, Cleveland Ohio'
'Officer of the president, San Francisco State College' ...,
'Ethiopian Soldiers' 'Council Secretary: Naseer Ahmad'
'Civilian: Norsel Bulaybulay']
========
natlty2
<type 'numpy.float64'>
157
[ nan 217. 233. 422. 216. 30. 144. 142. 92. 218.
605. 130. 96. 185. 45. 145. 100. 98. 61. 97.
110. 94. 59. 359. 201. 173. 83. 51. 21. 199.
209. 38. 95. 69. 60. 160. 231. 101. 75. 235.
11. 43. 159. 163. 999. 155. 153. 183. 15. 143.
113. 186. 162. 65. 603. 200. 208. 4. 157. 47.
362. 213. 89. 203. 36. 112. 167. 14. 106. 104.
179. 166. 6. 78. 197. 156. 198. 87. 84. 123.
151. 42. 124. 168. 53. 19. 102. 205. 81. 93.
177. 222. 55. 74. 44. 228. 34. 8. 229. 5.
175. 1003. 219. 195. 28. 26. 35. 141. 139. 107.
50. 12. 147. 202. 22. 16. 121. 204. 67. 99.
108. 182. 137. 174. 184. 103. 118. 32. 138. 86.
88. 161. 114. 223. 136. 146. 334. 207. 62. 63.
41. 214. 90. 119. 1004. 18. 54. 158. 37. 206.
56. 111. 33. 164. 76. 238. 215.]
========
natlty2_txt
<type 'float'>
157
[nan 'United States' 'Northern Ireland' 'International' 'Great Britain'
'Brazil' 'New Zealand' 'Netherlands' 'India' 'Uruguay'
"People's Republic of the Congo" 'Mexico' 'Ireland' 'Spain' 'Colombia'
'Nicaragua' 'Jamaica' 'Italy' 'El Salvador' 'Israel' 'Lebanon' 'Iran'
'Ecuador' 'Soviet Union' 'Taiwan' 'Saudi Arabia' 'Guatemala' 'Cuba'
'Belgium' 'Switzerland' 'Turkey' 'Canada' 'Iraq' 'France' 'Egypt'
'Philippines' 'Zimbabwe' 'Japan' 'Germany' 'Yugoslavia' 'Argentina'
'Chile' 'Peru' 'Puerto Rico' 'Multinational' 'West Bank and Gaza Strip'
'Pakistan' 'South Africa' 'Austria' 'New Caledonia' 'Libya' 'Sri Lanka'
'Portugal' 'Ethiopia' 'United Kingdom' 'Syria' 'Tunisia' 'Afghanistan'
'Papua New Guinea' 'Republic of the Congo' 'West Germany (FRG)' 'Uganda'
'Hong Kong' 'Tanzania' 'Cambodia' 'Liberia' 'Russia' 'Australia' 'Kuwait'
'Kenya' 'Slovak Republic' 'Romania' 'Algeria' 'Greece' 'Swaziland'
'Panama' 'Sweden' 'Haiti' 'Guinea' 'Mali' 'Norway' 'Chad' 'Malta' 'Rwanda'
'Cyprus' 'Bangladesh' 'Jordan' 'Thailand' 'Guadeloupe' 'Indonesia'
'Sierra Leone' 'Venezuela' 'Denmark' 'Georgia' 'China' 'Yemen' 'Burundi'
'Angola' 'Democratic Republic of the Congo' 'Albania' 'Serbia-Montenegro'
'Kosovo' 'Uzbekistan' 'Sudan' 'Bosnia-Herzegovina' 'Bolivia' 'Belarus'
'Nepal' 'Namibia' 'Kyrgyzstan' 'Croatia' 'Armenia' 'Nigeria' 'Tajikistan'
'Belize' 'Azerbaijan' 'Malaysia' 'Togo' 'Fiji' 'Ivory Coast' 'Laos'
'Somalia' 'Mozambique' 'Senegal' 'South Korea' 'Kazakhstan' 'Macedonia'
'Bulgaria' 'Myanmar' 'Guyana' 'Honduras' 'Poland' 'Liechtenstein'
'Vietnam' 'Morocco' 'Niger' 'Asian' 'Trinidad and Tobago'
'Equatorial Guinea' 'Eritrea' 'Central African Republic' 'Ukraine'
'Hungary' 'Madagascar' 'South Sudan' 'Bahrain' 'Czech Republic' 'Paraguay'
'Cameroon' 'Tonga' 'Djibouti' 'Lesotho' 'Burkina Faso' 'Qatar' 'Ghana'
'Corsica' 'United Arab Emirates']
========
targtype3
<type 'numpy.float64'>
21
[ nan 1. 14. 2. 3. 6. 10. 22. 7. 4. 15. 21. 12. 18. 19.
8. 17. 16. 11. 13. 9.]
========
targtype3_txt
<type 'float'>
21
[nan 'Business' 'Private Citizens & Property' 'Government (General)'
'Police' 'Airports & Aircraft' 'Journalists & Media'
'Violent Political Party' 'Government (Diplomatic)' 'Military'
'Religious Figures/Institutions' 'Utilities' 'NGO' 'Tourists'
'Transportation' 'Educational Institution' 'Terrorists/Non-State Militia'
'Telecommunication' 'Maritime' 'Other' 'Food or Water Supply']
========
targsubtype3
<type 'numpy.float64'>
90
[ nan 8. 68. 18. 25. 42. 72. 77. 46. 34. 85. 67.
53. 39. 108. 62. 15. 11. 7. 21. 76. 86. 82. 97.
96. 101. 49. 47. 87. 1. 71. 3. 73. 45. 100. 22.
13. 78. 81. 23. 93. 70. 69. 61. 99. 48. 88. 37.
35. 89. 75. 19. 36. 26. 27. 84. 12. 2. 74. 24.
60. 14. 44. 5. 6. 107. 63. 57. 79. 64. 54. 104.
10. 9. 90. 94. 33. 65. 4. 20. 29. 80. 92. 55.
109. 52. 50. 17. 83. 58.]
========
targsubtype3_txt
<type 'float'>
90
[nan 'Hotel/Resort' 'Named Civilian'
'Government Personnel (excluding police, military)'
'Police Security Forces/Officers' 'Aircraft (not at an airport)' 'Farmer'
'Laborer (General)/Occupation Identified' 'Embassy/Consulate'
'Military Personnel (soldiers, troops, officers, forces)'
'Religious Figure' 'Unnamed Civilian/Unspecified'
'Newspaper Journalist/Staff/Facility' 'Paramilitary' 'Oil'
'International NGO' 'Politician or Political Party Movement/Meeting/Rally'
'Entertainment/Cultural/Stadium/Casino' 'Retail/Grocery/Bakery'
'Government Building/Facility/Office' 'House/Apartment/Residence'
'Place of Worship' 'Labor Union Related' 'Tourist' 'Tour Bus/Van'
'Bus Station/Stop' 'School/University/Educational Building'
'International Organization (peacekeeper, aid agency, compound)'
'Affiliated Institution' 'Gas/Oil' 'Race/Ethnicity Identified'
'Bank/Commerce' 'Vehicles/Transportation'
'Diplomatic Personnel (outside of embassy, consulate)'
'Train/Train Tracks/Trolley'
'Police Building (headquarters, station, school)'
'Private Security Company/Firm'
'Procession/Gathering (funeral, wedding, birthday, religious)'
'Museum/Cultural Center/Cultural House'
'Police Patrol (including vehicles and convoys)' 'Terrorist' 'Student'
'Religion Identified' 'Domestic NGO' 'Bus (excluding tourists)'
'Teacher/Professor/Instructor' 'Radio' 'NATO'
'Military Transportation/Vehicle (excluding convoys)' 'Television'
'Village/City/Town/Suburb' 'Election-related' 'Military Checkpoint'
'Prison/Jail' 'Military Barracks/Base/Headquarters/Checkpost'
'Political Party Member/Rally' 'Construction' 'Restaurant/Bar/Caf\xe9'
'Marketplace/Plaza/Square' 'Police Checkpoint' 'Port'
'Judge/Attorney/Court' 'Airport' 'Industrial/Textiles/Factory'
'Medical/Pharmaceutical' 'Electricity' 'Ambulance' 'Civilian Maritime'
'Public Area (garden, parking lot, garage, beach, public building, camp)'
'Fire Fighter/Truck' 'Radio Journalist/Staff/Facility'
'Highway/Road/Toll/Traffic Signal' 'Mining' 'Farm/Ranch'
'Telephone/Telegraph' 'Non-State Militia' 'Non-combatant Personnel'
'Refugee Camp' 'Multinational Corporation' 'Intelligence'
'Military Unit/Patrol/Convoy' 'Memorial/Cemetery/Monument'
'Multiple Telecommunication Targets'
'Television Journalist/Staff/Facility'
'Party Official/Candidate/Other Personnel' 'Water Supply'
'Other Personnel' 'Head of State' 'Protester' 'Commercial Maritime']
========
corp3
<type 'float'>
377
[nan 'Howard Johnson Hotel' 'Royal Ulster Constabulary' 'Airplane'
'City of San Sebastien' 'EFE' 'independent'
'Democratic Revolutionary Front (FDR)' 'India' 'Guatemalan' 'local papers'
'unk' 'Unknown' 'Mobil' 'Save the Children Fund' 'colombian army'
'local, La Traviata Hacienda' 'Sinn Fein' 'Mill hill missionaries'
'West German firm/Mannesmann -Anlagenban AG' 'UPS'
'International Jewish Film Festival' 'French Auto Companies'
'Kuwait Airways' 'Catholic Church' 'International Red Cross'
'Village Council (government)' 'Mountain Climbing Federation' 'Tourists'
'Military' 'Journalist' 'Sanford Canadian Company' 'Journalists'
'Christian Missions in Many Lands' 'Lakas Manggagawa Labor Center'
'local government' 'Doctors without Borders'
"Noah's Ark Research Foundation" 'government'
'African National Congress (ANC)' 'World Action Against Hunger' 'Unk'
'Schlumberger' 'Sieromco' 'Jinotega Department / "Humbolt" NGO'
'Intl Agency (UN Development Program)' 'German tourists' 'civilians'
'Ibero-American Summit' 'Indian Army' 'Sri Lankan Police' 'Civilians'
'Rioclaro Cement' 'Christian Religious Denomination'
'ETPM French Oil Field Services Corporation' 'Small businesses'
'Credit Lyonnais' 'person in shop' 'Govt' 'Triton Hotel' 'Police'
'Farm administrator' 'Civilian' 'Alcatel' 'Cooperative'
'Caloto Government' 'Christian Congressional Association' 'Vehicles'
'European Union (EU)' 'Turkish Government' 'Indian railway'
'Shell Oil Company' 'Namibia Police' 'United Nations' 'Relief Workers'
'Humanitarian aid workers' 'Turkish government' 'Nigerian citizen'
'Philippines police' 'Kashmir police' 'Tamil party'
'Bangladesh Rifles (BDR)' 'Bilbao Bizkaia Kutxa (BBK)'
'Colombia Government' 'Tenere Hotel' 'Shell Oil' 'Civilian vehicle'
'Kenyan Civilians' 'Sri Lankan civilians' 'Abkhaz Translator'
'Muslim Community in Athlone, South Africa'
'Agricultural Development Bank' 'Municipality of Surata'
'Guinean government' 'Sri Lankan police' 'A rival terrorist group'
"Municipal People's Assembly" 'Telecommunications office'
'Indian Paramilitary'
'Private citizens and property in the vicinity of the blast'
'Undangan Police' 'Private citizens' 'Employees' 'Philippine military'
'Airline Travellers' 'Barrancabermeja Harbor'
'Pagadian citizens and property' 'Australian Tourist' 'American Airlines'
'United Airlines' 'Haifa police officers'
'Krasnodar nongovernmental organizations' 'Sgem World of Colombia'
'Algerian Police' 'Government Administrative Infrastructure'
'Royal Nepalese Army' 'US diplomat' 'United Nations Observers'
'Civilians and civilian property' 'Bus load of tourists' 'Local Bus'
'Spanish police' 'Spanish Tourism Industry' 'Businesses'
'Local businesses' 'A passenger bus' 'Indian Police force'
"Les Coulisses' newspaper" 'Border Security Force'
'Parliamentary candidate' 'Local Telecommunications equipment'
'Government of the United Kingdom' 'A bus terminal'
'Indiscriminate Algerian citizens' 'US Department of Defense'
'Indian Military Forces' 'NATO' 'Algerian soldiers' 'Nepalese Bank'
'British Soldiers' 'Turkish Police' 'British security firm'
'Orascom Employees' 'Peacekeepers' 'Pan-Arab Satellite TV network'
'Olice Security' 'Village' 'Halliburton' 'Kroll Inc.'
'Government Polling Station' 'Israel Defense Force'
'Indiscriminate Algerian civilians' 'Indian Police Forces'
'Nepalese Military Forces' 'Sri Lankan Prison guards'
'Regional French Government' 'Assam Police Forces'
'Property of civilian(s)' 'Iraqi Government' 'Toribio Police'
'Sunni Islam' 'Nepalese Military' 'Son of the Governor' 'Train Station'
'Bodyguard' 'Shi i mosques' 'Thai Police' 'Hotels' 'Telefonica'
'British Petroleum'
"People's Liberation Organisation of Tamil Eelam (PLOTE)"
'Turkish Road Construction Company' 'Baghdad Police' 'Iraqi Police Force'
'India Police' 'Afghan Police' 'Indian civilians'
'Afghan deputy security commander of Urozgan' 'Restaurants' 'Restaurant'
'Turkish Military' 'Pakistan Petroleum Limited' 'Local Shop'
'Bangladesh Police' 'Burundi citizens' 'Iraqna Mobile Phone Company'
'Nepalese Government' 'Doctors Without Borders' 'Albanian police'
'Khan Bani Saad tribal council member' 'Government of Nepal'
'Somali government official' 'Spanish local police' 'Private homes'
'Nigerian Military' 'Indian Military' 'Thailand Armed Forces'
'Gol Agha Sherzai, former Governor of Kandahar (Province)'
'Sri Lankan guards' 'Sri Lankan government' 'Federal Electoral Tribunal'
'Car Dealership' 'Austrian Police' 'Chad Military' 'Madrid Airport'
'Shops' 'Business' 'Mosque' 'Great Britain' 'Factory workers'
'General National Security Directorate' 'Hospital' 'Mayor'
'Iraqi civilians' 'Nepal Electricity Industry' 'Iraqi Police'
'Police forces' 'Shopping Center' 'Saddar Bazaar' 'Gendarmes'
'Paramilitary of the Civilian Armed Forces Geographical Unit'
'Security forces' 'Not Applicable' 'Security guards' 'Educational'
'Greek power firm' 'Telecommunication' 'Somali police'
'Indian police forces' 'US armed forces'
'Green Zone military and diplomatic compound' 'Hyundai'
'Eritrean Government' 'Tipo Tipo Law Enforcement'
'International Rescue Committee' 'Tangcal city Law Enforcement'
"People's National Army" 'Filipino Government'
'United Nations High Commissioner for Refugees'
'Action Contre la Faim/Action Against Hunger' 'Tourist'
'Philippines Military' 'Indian Law Enforcement'
'Zugdidi Police Department' 'Algerian firefighters'
'Action Against Hunger' 'Filipino Military' 'Radio Hobyo'
'Colombian Military' "Ba'quba Law Enforcement"
'German Development Cooperation (GTZ)' 'Spanish Embassy'
'Indian COBRA Military Forces' 'India Special Police Personnel'
'Pakistani Law Enforcement' 'Afghan Law Enforcement'
'Turkish Judicial Government' 'International Medical Corps'
'Indian Forest Department' 'Areva' 'Ivoirian Law Enforcement'
'Yemeni Military' 'Maiduguri Law Enforcement' 'Domodedovo Airport'
'Pakistani Home Secretary' 'Afghan Military' 'Congolese Military'
'Jharkhand Armed Police' 'Engineer' 'Toribio Law Enforcement'
'German Military' 'Indian District Law Enforcement'
'Arturo Ledesma Hacienda' 'Thai Law Enforcement' 'Lashkar-e-Jhangvi'
'Afghan Government' 'Not applicable' 'PT Freeport'
'Emergency response teams' 'Safaricom' 'Homes' 'AusAID'
'Indonesian Armed Forces' 'Abdul Kaliq Shindandi Security Company'
'Government of Balochistan' 'Parliament of the Republic of Somalia'
'Braeval Mining Corporation' 'Ras Kamboni Militia'
'Government of Pakistan' 'Army' 'French Armed Forces'
'Ministry of Finance' 'Pakistani Police' 'Government of Peshawar'
'Pakistan Rangers' 'INTERSOS' 'Saudi Arabian Ministry of Foreign Affairs'
'Afghan National Security Force (ANSF)' 'Etisalat'
'North Refineries Company (NRC)' 'ASEA Brown Boveri (ABB)'
'Sulaiman Bek Town' 'National Directorate of Security (NDS)'
'Afghan Ministry of Transport and Civil Aviation'
'Armed Forces of the Philippines (AFP)' 'Philippine National Police (PNP)'
'Samora Machel Military Academy' 'Somali National Army (SNA)'
'Kanar Oil Field' 'Iraqi Police Service (IPS)'
'Central Security Organization (CSO)' 'Mandisar Hospital'
'Piacentini Costruzioni SpA' 'Al-Naqshabandiya Army' 'Zintan Militia'
'Ukrainian Army' 'Military of Yemen' 'Mitra Television'
'Nigeria Police Force (NPF)' 'Geidam Town' 'Babban Gida Village'
'Sahwa Council' 'Bangladesh Chhatra League (BCL)' 'Uttaran Printing Press'
'Armed Forces of Ukraine' 'Iraqi Volunteer Forces'
'Congolese National Police (PNC)' 'Al-Mabrook Oilfield' 'Fotokol Town'
'Iraqi Armed Forces' 'Adhaim Dam' 'Central Hotel'
'Central Security Forces (CSF)' 'Hizballah' 'Central Bank of Somalia'
'Pan African Minerals' 'Iraqi Army' 'Levies Forces' 'Popular Committees'
'Capalonga College' 'Afghan Central Statistics Organziation'
'Kafrayah Town' 'Fuah Town' 'South Sudan National Police Service (SSNPS)'
'African Union Mission in Somalia (AMISOM)' 'Government of Burkina Faso'
'Israel Police' 'General National Congress (GNC)'
'South African National Defense Force (SANDF)'
'Egyptian National Police (ENP)' 'Turkish National Police (EGM)'
'Diyarbakir Bar Association' 'Mindanao State University (MSU)'
'Yemeni Police' 'Frontier Corps (FC)' 'Burundi National Police'
'Al-Baghdadi Town' 'Federal Police' 'Kismaayo University'
'Pattani Concrete Company, Ltd.' "Asa'ib Ahl al-Haqq"
"Republican Forces of Cote d'Ivoire (FRCI)"
'Partido Demokratiko Pilipino-Lakas ng Bayan (PDP-Laban)'
'al-Baghdadi District' 'Armed Forces of Libya' 'Raja Town'
'Turkish Armed Forces (TSK)' 'Iraqi Ministry of Health'
'Government of Kunduz' 'Government of Somalia'
'Russian Ministry of the Interior' 'Ungwan Misisi Village'
'United States Armed Forces' 'Syrian Arab Red Crescent (SARC)'
'Armed Forces of the Democratic Republic of the Congo (FARDC)'
'Tal Afar Airport' 'Gold Bus Line Company']
========
target3
<type 'float'>
666
[nan 'The Downtown Howard Johnson Hotel in New Orleans' 'Brian Haslehurst'
'Zuhayr Mughrabi, driver' 'Norman Lynch, Protestant' 'woolworth'
'Cypriot Airlines' 'Angel Crus Salcines, Policeman'
'Filadelfo Martinez, EFE; correspondent' 'Gabriel Gomez Arrubla, rancher'
'British Airways' 'Manuel Franco, leader' '4 construction workers'
'Centroamericana Building (houses 4 embassies)' 'Banker, Ilkay KArokoc'
'unknown' 'Corporal, Unk, Military Driver, Unk' 'Leading Clergyman'
'unk, bodyguard (wounded)' 'unidentified woman'
'Felit Argueta, seminarist' 'Rafael Arrieta, reporter'
'car (on Ilisia) belonging to foreign diplomatic mission'
'Karl Hans Schulz, technician' 'James Greenwell, 18' 'Unknowns'
"Surgeon: Dr. As'ad Taha" '3 unk militiamen escorts'
'Oil storage complex (called Munhava tanker farm)' 'Unks' 'pavillion'
'Orlando Estrada, sgt.' 'Jorge Montoya, land owners, peasants'
'Joe Keenan' 'Rev Zachariah Chatin, roman catholic priest'
'unk, interpreter' 'Maggie Fox, 25, fereelance reporter'
'International Jewish Film Festival' 'Rental Car Agency/Ford Dealer'
'Office of National Planning Institute' 'Turkish Woman, 27 years old'
'state enterprise' '1 Citroen dealership' 'Homes (2)'
'Kuwait Airways property and employees' '*' 'Ruben Gallo, associate'
'Trevor Anderson' 'Dino Rossy' '4 soldiers' 'Wemer Kiwitt'
'Engineer Marcel Chambard' 'Aurora Building' 'West German National'
'5 Others' '3 Missionaries'
'Honorio Bulacao, Pres. Cebu alternative workers assembly' '4 persons'
'Belgian Paramedic' '5 companions to mayor' 'governor'
'East Rand (ANC official)' 'Tourist Vehicle Carrying German tourists'
'other leaders' 'tourists, 1 Swede, Tommy Cylad (21)'
'International Bus Terminal' 'Apartment block occupied by immigrants'
'Foreign workers' "Foreign support of the gov't"
'Students and teachers at the Lincoln Savage Middle School' 'Sarah Howart'
'German tourists' 'Asylum seeker' 'civilians including children'
'Summit Attendees' 'Two soldiers' 'Egyptian Embassy'
'Police near army headquarters and Slave Island Railway Station'
'Russian Citizens' 'Ulrich Dresser' 'UN Peacekeepers'
'UN peacekeepers/ Aid Workers' 'Aid workers'
'Roman Catholic Priests/Nuns*' '1 orphanage' 'AID Workers' 'UN Personnel'
'Tourists at Empire State Bldg' 'Oil barge 3 Britons'
'Shops surrounding the bus station' 'Arab civilian' 'Bank'
'Filipino Good Samaritan' 'work crew' 'Candidates (6)' 'Hotel'
'Egyptian police' 'Colombian Birdwatchers' 'Colombian Civilians'
'Civilians' 'Juan Carlos Sierra' 'Sri Lankan Police Officers'
'Shops and Banks in Dabeiba' 'Palestinian civilians' 'Rudolf Peichy'
'Vehicles owned by residents of Albania, Colombia'
"Civilians' homes in Chinhungo, Algeria"
"Australian tourists near Sana'a, Yemen"
'Four civilians working for Alcatel in Chinchina, Colombia'
'Three New Zealander Tourists' 'Cooperative in Piendamo, Colombia'
'City Hall and Town Council in Caloto, Colombia'
'Civilians at roadblocks in El Desastre' 'Civilians in Margosatubig'
'British Citizen' 'Angolan Aid Workers'
'A cargo truck and three trailers transporting vehicles from Venezuela'
'Stephan Devaux, EU Official' 'A private homestead'
'Two Indian Army Soldiers' 'Nigerian jet passengers'
'Private homes in El Espino' 'Serb civilian'
'Unnamed municipal government buildings in Diyadin District'
'New Jalpaiguri railway station' 'Employees of Shell Oil'
'Nigerian Citizens working on a Royal Dutch Oil rig'
'Namibia Police Station in Katima Mulilo, Namibia'
'United Nations staff in Sierra Leone' 'Norwegian Relief Workers'
'United Nations High Commissioner for Refugees (UNHCR) employee'
'Foreign civilians in Sucumbios Province, Ecuador'
'Workers of an unnamed U.S. Oil Company'
'Workers from an unnamed humanitarian aid organization'
'Individuals at the Turkish embassy' 'Nigerian citizens'
'Nigerian citizen' 'Police officers in the area of Tibao village'
'Constable Latief Ahmad; Constable Mohammad Dayim' "Tamil party's office"
'Bangladesh Rifles (BDR)'
'A cash dispenser at a Bilbao Bizkaia Kutxa (BBK) bank in Gernika'
'Government buildings in Puerra' 'Government buildings in Cordoba'
'Government buildings in Potosi' 'Farmer Angga Antinado'
'Tenere Hotel in Algeria' 'Private Shell secuity guards'
'South Korean Citizens living in residences owned by Elf Aquitaine Oil Company'
'Private vehicle between Anori and Amalfi, Antioquia Department, Colombia'
'Kenyan Civilians who had gathered around a stadium in Isiolo'
'Tamil civilians' 'An Abkhaz Woman Interpreter' 'Italian Journalist'
'Power Plant, Tomas Razon town' 'A journalist in the park'
'Samaj Community Center and Gatesville Mosque, Athlone'
'UN employee Sapeu Laurence Djeya'
'Agricultural Development Bank building in Bhorletar in Lamjung District'
'Mayor Orlando Lizcano' 'Government buildings in Gueckedou'
'Police officers on board the passenger bus'
'United Self Defense Units of Colombia (AUC)'
"Chairman of Bordj Thar's Municipal People's Assembly"
'Students at the university in Grozny'
'Indonesian Telecommunications office'
'Civilian accompanying the transport'
'Civilians on board a passenger plane bound for Chiang Mai'
'Civilians worshipping in a mosque in Lahore'
'A paramilitary soldier in Imphal'
'Private citizens and property near Montecarlo Hotel'
'Police Barracks in Kasese'
'Private citizens in the vicinity of the blast'
'Serbian Civilian in the village of Matejce'
'Employees at the Dos Palmas Island Resort at Honda Bay'
'Philippine soldiers responding to the attack'
'People at the airport waiting to depart' 'Barrancabermeja Harbor'
'Citizens and property in the vicinity of the explosion'
'Amanda Brigg, Australian Tourist'
'American Airlines-owned Boeing 767 passenger jet aircraft'
'United Airlines-owned Boeing 767 passenger jet aircraft'
'American Airlines-owned Boeing 757 passenger jet aircraft'
'United Airlines-owned Boeing 757 passenger jet aircraft'
'Police officers in the vicinity of the explosion'
'A convoy of Krasnodar nongovernmental organization vehicles'
'Employees of Sgem World of Colombia'
'Algerian policemen at a restaurant in Laghouat'
'Nepal district administrative offices in Salleri'
'Civilians in Cauca, Colombia' 'Nepalese soldiers in Mangalsen'
'US diplomat and wife' 'UN Observers in Lebanon'
'Private homes and civilians in Rovira'
'Tourists unloading from bus near the Ghriba synogogue'
'Tourists in the vicinity of the Jewish shrine'
'Civilians at the Mamara Hotel in Istanbul' 'A bus in Bilbao'
'Police in the vicinity of the parking lot at the university'
'Tourists and vehicles in the Spanish town of Santander'
'Pakistani security guard' 'Small and large business buildings in Dolores'
'Local businesses in the vicinity of the police station'
'A passenger bus traveling to Palu' 'Central Reserve Police Force (CRPF)'
'Afghan civilians' "Nicaise Kibelbel, editor of 'Les Coulisses' newspaper"
'2 American teachers working at a school near the mine'
'Border Security Force members at a bus stand in Surankote'
'Civilians at a bar in Georgetown'
'Zahoor Ali Chishti, a candidate for Parliament'
'Nephew of Mayor Luis Antonio Motta' 'Indiscriminate civilians in Gitega'
'Indiscriminate civilians at the Paradise Hotel in Mombasa'
'Multi-Access Radio relay equipment in Peddaktnta, India'
'Civilians in the vicinity of the hotel'
'Various Congolese Shop Owners in Yamba'
'British High Commissioner in Wellington, New Zealand'
'Civilians in Ricaurte, Colombia' 'A bus terminal in Parang'
'Indiscriminate citizens in Siocon, Philippines'
'Civilians in the vicinity of a patrol in Granada'
'Algerian civilians travelling through Batna'
'Indians and tourists visiting the Gateway of India and the Zaveri Bazaar'
'Attendees at the weekly sermon at the Tomb of Ali'
'Somali maintenance worker'
'US Deputy Defense Secretary Paul D. Wolfowitz'
'Federal Police at the central telegraph office in Srinagar'
'International Security Assistance Force'
'Churchgoers and passersby at the incident site'
'Algerian soldier driving through Skikda'
'A state-run bank in the town of Bhojpur'
'Two British soldiers serving in Basra'
'Indiscriminate Syrian civilian near the Diplomatic Quarters in Damascus'
'A Police Station of Pervari, Turkey.'
'Security guards from a private British security firm'
'Iraqi Orascom employees in Qaim, Iraq' 'Icelandic peacekeepers'
'Pan-Arab Satellite TV network' 'Olice Security Convoy'
'Indiscriminate Iraqi citizens' 'Indiscriminate citizens' 'Unknown'
'Contractors' 'British and American employees of Kroll Inc. in Baghdad'
'A government polling station located 90 miles south of Charlie Camp'
'Civilians in Yala Province' 'IDF soldiers manning the Qarni Checkpoint'
'Algerian citizens on a public bus travelling on Wilaya Road 19'
'Four policemen in Pulwama (District)' 'Major Ravi Gartaula'
'prison guards' 'Offices of the Corsican Regional Natural Park'
'Police forces' 'Indian policemen near the Punjab National Bank in Poonch'
'Two houses of school-teachers, Two empty civilian homes, and One excavator vehicle'
'Ministry of Agriculture in Baghdad'
'Policemen near Alvaro Ulcue Hospital' 'Australian National in Baghdad'
'Sunni leaders in Baghdad'
'Indicriminate civilians in the resort town of Jounieh, Lebanon'
'Civilians at the Rajpur bazaar' 'UN employee in the internet caf\xe9'
'Chorhawa Military Base'
'Son of the governor of Iraq\x92s Anbar Governorate, Raja Nawaf Farhan al- Mahalawi'
'Srinagar civilians' 'The Thepa train station'
'Bodyguard assigned to ZagirArukhov'
'Civilians attending a funeral at Abdul Rab Akhundzada Mosque'
'Thadchanamoorthy Karunamoorthy, a civilian'
'Husseiniyah Abdul- Rassul mosque and Albu Jumaa mosque'
'Thai Police in Yala' 'Mosque in Al-Musayyib'
'Hotels at and around the Egyptian resort of Sharm el-Sheikh.'
'A Telefonica sales offices in Gexto' 'Civilians in Antalya'
'The British Petroleum office in Tehran' 'Civilians in Baghdad'
"Relangi Selvarajah and S. Selvarajah, supporters of the People's Liberation Organisation of Tamil Eelam (PLOTE)"
'Indiscriminate Egyptian and Indian civilians'
'Five employees of a Turkish construction firm in Afghanistan'
'Police transporting injured people to Kindi Hospital'
'Promenade Hotel in Beirut'
'Iraqi policemen working at the Joint Coordination Center for Diyala Governorate'
"Police providing security at Irrigation Minister Qazi Afzal's political rally"
"Policemen providing security for Addison's convoy"
'Civilians in the state of Jammu and Kashmir' 'Abdol Matin'
'Restaurants located near Jimbaran Beach' 'Raja Restaurant in Kuta'
'Police officer in the vicinity of the water truck' 'Tourists in Hillah'
'Algerian citizens at a town market in Medea'
'Soldiers stationed in Semdinli' 'Baghdad Civilians'
'The Qadduri restaurant in central Baghdad'
'A Pakistan Petroleum Limited office in Karachi'
'Guests staying at the Hamra Hotel in Baghdad' 'Thai police officers'
'A liquor store in Kirkuk' 'Police working at a court complex in Gazipur'
'A police checkpoint in Chittagong'
'Civilian in the vicinity of the fruit stand' 'Burundi Citizens in Magara'
'Kenyan workers for Iraqna Mobile Phone Company'
'Private homes and property'
'Police officers in Batticaloa riding in a targeted army truck'
'Police constables in the vicinity of the attack'
'Nepalese Government Officials'
'Dutch doctors from Doctors Without Borders in the Norte de Santander Department, Colombia'
'Police roadblock near Rreshen in the Mirdite (District)'
'Raad Ahmed Chibish al-Jibouri' 'Nepalese Civilians' '(District) Prison'
'Somali parliamentarian' 'Central African Republic doctors'
'Spanish police officers who arrived to help at the scene of the fire.'
'Private homes' 'Bus driver and conductor'
'Soldiers in the Nigerian Military' 'Indian Soldier' 'Thailand Marines'
"Gol Agha Sherzai's home"
'Iranian pilgrims at the Shi i shrine of Maitham al-Tamar in Kufa, Iraq'
'Guards in the vicinity' "Members of the Eelam People's Democratic Party"
'fishing harbor in the port city of Galle'
'United Nations Assistance Mission to Afghanistan regional office in Konar Province, Afghanistan'
'Government' 'Chevrolet Dealership' 'Austrian police officers'
'Chad Soldiers' 'NATO officers' 'Parking garage loctaed at Madrid Airport'
'Gaza' 'Shops in Tal Afar market' 'Afghani laborers'
'Karradah market district' 'Civilians near the incident' 'Villa Somalia'
'Mosque in Slalma, Algeria'
'Child and other civilians in the vicinity of the attack' 'Kirkuk'
'Indian workers in a factory in Vilage Developmental Area'
'Residence of Ali Tounsi, the director of the General National Security Directorate'
'Private hospital in Baghdad' 'Hajarun Jamiri' 'Journalists'
'Kenyan guard at Indorama' 'Power poles in Chandravata.'
'Government soldiers'
'Iraqi Police Forces at a police checkpoint in Anbar' 'Soldiers'
'Bus stand' 'Shopping Center' 'Small eatery'
'Commercial shops and businesses within the market' 'Shops in the market'
'Rudy Villaflor' 'Security forces in Matta'
"Civilians at two hotels in Narathiwat's Sungai Kolok municipality"
'Afghan security' 'Teacher' 'Vehicle'
'Telecommunication installations in Tanout' 'Police vehicle'
"Civilians in the vicinity of the city of N'Djamena" 'Nayagarh armory'
'American soldiers' 'Indiscriminate Afghan civilians' 'Iraqi Civilians'
'US Embassy' 'A Hyundai car was targeted.'
'A foreign teacher was targeted.'
'The building housing the Apostolic Nuncio was targeted.'
'Hospital ambulances were also targeted.' 'Sudanese Civilians.'
'The Ethiopian Foreign Ministry building was also suspected to be targeted.'
'An Afghan civilian, the driver of French national Johann Freckhaus who heads the French company Gohan Sreckhaus, was also targeted.'
'Three houses belonging to Benoi-Vedeno residents were also targeted.'
'The target was the security guards.' 'A tribal elder was targeted.'
'The attack targeted various villages in Georgia.'
'Caf\xe9 employees and patrons were also targeted.'
'A policeman from Uganda was killed in the attack.'
'Target was 2 motorcycles.'
'Two Ukrainian crew members of the Hercules were targeted.'
'The target was the police officers.' 'Civilians were targeted.'
'A female British-Canadian International Rescue Committee aid worker was targeted.'
'A military fortification was targeted.'
'Tangcal city policemen were also targeted.'
'Abdifatah Mohammed Elmi, Somali photo-journalist and two Somali drivers'
'Government vehicles were targeted in the attack.'
'Algerian soldiers on a search operation in Boumerd\xe8s'
'Foreign civilians were targeted.'
'Rival cartel members were also targeted.'
'A Zone of Peace and Development building was targeted.'
'The third car belonged to a private citizen.'
'One target was the office of the village chieftain and local council.'
'Several United Nations High Commissioner for Refugees workers were targeted.'
'A driver was kidnapped.' 'One Bulgarian national was killed.'
'Electricity lines were targeted.'
'A civilian was the target of the attack.'
'Offices of the Pakistan Air Force were targeted.'
'A Chinese engineer was targeted in the incident.' 'Edwin Dyer'
'A German tourist was targeted.'
'Several civilian residences were also targeted.'
'Chruhatpat villagers were targeted.' 'Three civilians were wounded.'
'Military responders' 'The VBIED targeted a nearby Shiite mosque.'
'A community hall was targeted.' 'A prosecutor was targeted.'
'A store that sells military uniforms was targeted.'
'The additional target were police officers.'
'The target was a community hall.' 'A police station was targeted.'
'A South Korean citizen was targeted.'
'The assailants attacked a CPI-M member.'
'Firefighters that responded to the first explosion in Hazama'
'One aid worker was targeted.'
'The assailants detonated an improvised explosive device (IED) targeting a communications antenna.'
'A Filipino soldier was targeted.'
'Seven school were targeted in the attack.'
'A Venezuelan soccer player member of the team Los Maniceros was targeted.'
'A unknown number of schools were targeted.'
'An unknown terrorist was targeted.'
'An Indian engineer was the target of the attack.'
'The target of this attack was a police officer.'
'The mobile column Teofilo Forero Castro, who placed a powerful explosive to detonate the passage of police and army patrols and even civilians who passes by this area constantly.'
'A photographer in Ain Sebt' 'The attacked damaged seven vehicles.'
'A radio station was targeted in this attack.'
'Several un-named official government buildings in Popayan were targeted.'
'Military soldiers responding to the attack were also targeted.'
'The headquarters of the Emergency Police 3rd Regiment was targeted in the attack.'
'Shia pilgrims were targeted.'
'An Indian construction engineer was also targeted in the attack.'
'Twelve trucks, including eight of a private construction company, were targeted in the attack.'
'One German humanitarian worker was targeted.'
'Civilians were targeted in the attack.'
'The Spanish Embassy was targeted.'
'Fifteen COBRA commandos were targeted.'
'The Chintalamma and Koyyur ghat roads were targeted in the attack.'
'Special police personnel were also targeted in the attack.'
'Civilians and civilian property in the vicinity of the device in Baghlia'
'Bomb Disposal Squad members were targeted.'
'Seven business were also targeted in the attack.'
'One teacher was targeted.'
'A forest guest house was also targeted in the attack.'
'Police officers were targeted.'
'A judicial housing complex was targeted in the attack.'
'One Georgian aid worker with the International Medical Corps was targeted in the attack.'
'A Congolese pilot was targeted.'
"The Lieutenant Colonel's wife was targeted."
"A Forest Department subdivision ranger's quarter was targeted in the attack."
'One Malagasy worker was targeted.' 'A driver was targeted.'
'A civilian was targeted.' 'Policemen were targeted.'
'Yemeni Soldiers were targeted.' 'A policeman was targeted.'
'Civilians at Domodedovo Airport were targeted in the attack.'
'The Home Secretary, Akbar Hussain Durrani, was targeted in the attack.'
'Afghan soldiers were targeted.' 'A construction worker was targeted.'
'Four Congolese soldiers were targeted.'
'Jharkhand Armed Police (JAP) personnel were targeted.' 'Unidentified'
'Toribio policemen were targeted.'
'German soldier, including General Markus Kneip, were also targeted.'
'Italian soldiers were also targeted in the attack.'
'A joint team of Central Reserve Police Force (CRPF) personnel, Jharkhand Jaguar and District Police, were targeted.'
"The hacienda's timekeeper, Christopher Gerza, was also targeted."
'Police members of a bomb disposal unit were also targeted in the attack.'
'An undetermined number of villagers were also targeted in the attack.'
'Another civilian, Golamani Chakma, was also targeted in the attack.'
'A security guard was targeted in the attack.'
'Four schools were targeted.'
'A Lashkar-e-Jhangvi commander was targeted.' 'Afghani civilians'
'An unknown number of government office buildings were also targeted.'
"It is unknown if the target of the attack was the regional hospital, the governor's office or the Interior and Local Government Secretary, Jesse Robredo, was targeted."
'An unspecified number of government offices were also targeted.'
'Construction workers at the airport were targeted.'
'The targets were PT Freeport security management unit employees.'
'Four Afghani civilians' 'First responder emergency response teams'
'A police officer staffing a security checkpoint outside of a mosque'
"Police officers who were in the vicinity of the district governor's office"
'Civilians in the vicinity of the courthouse'
'Civilians in the vicinity of the assailant in a weapons store'
'Civilian onlookers in Maiduguri'
'Civilians in the vicinity of the market and the mosque'
'Three civilians in the vicinity of a military patrol in Mosul'
'Soldiers providing security in the vicinity of a Sunni mosque in Abu Ghraib area'
"Civilians in the vicinity of the girls' school in Mardan"
'Civilians in the vicinity of the medical center and police station'
'Civilians in the market' 'A Safaricom mast in Arabia village'
'Civilians and civilians homes in the vicinity of the residence of Ali Mehdi Sadiq'
'Young Boy' 'Civilians leaving the mosque' 'Private Homes' 'Civilian'
'Police' 'Four defense volunteers and three civilians'
'At least 2 civilians' 'Birdwatcher: Ivan Sarenas' 'Firefighters'
'Aid Worker: David Savage' 'Vehicles' 'Bar' 'Security Personnel'
'Officers' 'Banker'
'Excise and Taxation Minister: Mir Mohammad Ameen Umrani' 'Farm'
'Civilian: Somchit' 'Member: Mohamed Hirsi Dhunkal' 'Telephone Booth'
'Employee' 'Members' 'Offices' 'Private Garage; Civilians'
'84th Infantry Battalion' 'Checkpoint' 'Building' 'Officer'
'Commissioner: Sahibzada Anees' 'Refugees' 'Base' 'Embassy' 'Marketplace'
'Civilians: Muhammad Irfan Thaheem' 'Cell Phone Tower' 'Driver' 'Cart'
'Town' 'Intelligence Agents' 'Passenger Buses' 'Residences'
'Business Premises' 'Market' 'Hospital' 'Forces' 'Employees'
'Escort Patrol' 'Provincial Council Candidate' 'Houses'
'Worshippers Outside Al-Quds Sunni Mosque' 'Construction Workers'
'Tribal Sheiks' 'Convoy' 'Buildings' 'Photojournalist' 'Polio Worker'
'New Year Celebration' 'Kismayo Airport' 'Somali Workers'
'Chief: Awad Majwar al-Awlaqi' 'Translator: Andrey Mironov' 'Academic'
'Stone Crushing Plant Employee' 'Children' 'Engineer: Miljazin Gafuri'
'Health Center' 'Residential Areas' 'Residence' 'Workers'
'Tomb of Former President: Saddam Hussein' 'Plaza'
'39th Battalion Soldiers' 'Food Aid Convoy' 'Communications Masts'
'Former Militia Members' 'Kurdish Civilian' 'Town Entrance'
'Houses of Clan Leaders' 'Former Engineer' 'Polio Vaccination Team'
'House' 'Hospital Residential Compound' 'Funeral of Tribal Elder' 'Banks'
'Camera Operator: Zubair Hatami' 'Divisional Police Station' 'Truck'
'Cook' 'Village' 'Civilians: Saleem Bazai, Noor-ul-Ameen, Qureshi' 'Car'
'Deputy Sports Secretary: Golam Baki Chowdhury' 'Shop' 'Volunteers'
'Village Chief' 'Posts' 'Dam' 'Vendors' 'Shops' 'Rescue Workers'
'Clergy Members' 'Motorcycle' 'Consultant: Farhiya Bashir Nur'
'Christian Civilians' 'Security Guard' 'Patrol' 'Students'
'Celebration of Imam Ali' 'Officer: Ahmed Ali'
'Utility Worker: Mandy Retiro' 'Censes Director: Niamatullah'
'Medical Center' 'Bus' 'Village Watchman' 'Mosque'
'Christian Civilian: Ibrahim Adeola' 'Officer: Yona Francis' 'Tea Shop'
'Tea House' 'Kenyan Soldiers' 'Chief' 'Prime Minister Yacouba Isaac Zida'
'Civilian: Maritess Flor' 'Apartments' 'Officials' 'Trainer'
'Civilian: Shadi Arafa' 'Bar Owner' 'Tuareg Civilian'
'Convoy of Aden Security Director: Brigadier General Shalal Ali Shayyeh'
'Tourist: Sammie Olovsson' 'Convoy of Chief: Abdul Habib Syedkhel'
'Houses of Pro-Government Supporters' 'University' 'Civil Activists'
'Bakery' 'Office' 'Catholic Priest: Tom Uzhunnalil' 'Crewmembers'
'Watchperson' 'Rally' 'District' 'Airboats' 'Joint Convoy'
'Translator: Zabihullah Tamanna'
'Second Chief of General Staff: General Yasar Guler'
'Civilian: Daniela Gonzales' 'Water Plant Employee' 'Teachers' 'Spy Chief'
'Truck Drivers' 'School' 'Civilian: Chayanan Intharat' 'Joint Patrol'
'Suspected Informant' 'Shiite Muslim Procession' 'Member' 'Ambulance'
'Drinking Water Factory' 'Provincial Intelligence Chief'
'Soldier: Rifleman Moalosi Albert Mokhothu' 'Airport']
========
natlty3
<type 'numpy.float64'>
105
[ nan 217. 216. 110. 233. 53. 185. 45. 61. 92.
199. 209. 94. 83. 32. 75. 15. 231. 160. 98.
6. 195. 38. 422. 69. 159. 106. 96. 362. 144.
183. 21. 198. 236. 235. 182. 177. 42. 76. 95.
4. 186. 167. 55. 90. 93. 104. 99. 11. 51.
60. 155. 8. 14. 222. 147. 175. 139. 999. 151.
65. 19. 184. 74. 229. 141. 84. 205. 153. 213.
97. 101. 86. 34. 59. 47. 200. 142. 5. 41.
130. 78. 146. 334. 63. 16. 54. 62. 221. 119.
228. 103. 123. 173. 113. 137. 210. 118. 37. 214.
1004. 166. 33. 138. 102.]
========
natlty3_txt
<type 'float'>
105
[nan 'United States' 'Great Britain' 'Lebanon' 'Northern Ireland' 'Cyprus'
'Spain' 'Colombia' 'El Salvador' 'India' 'Switzerland' 'Turkey' 'Iran'
'Guatemala' 'Bulgaria' 'Germany' 'Austria' 'Zimbabwe' 'Philippines'
'Italy' 'Algeria' 'Sudan' 'Canada' 'International' 'France' 'Peru'
'Kuwait' 'Ireland' 'West Germany (FRG)' 'New Zealand' 'South Africa'
'Belgium' 'Sweden' 'Czechoslovakia' 'Yugoslavia' 'Somalia' 'Sierra Leone'
'Chad' 'Ghana' 'Iraq' 'Afghanistan' 'Sri Lanka' 'Russia' 'Denmark'
'Hungary' 'Indonesia' 'Kenya' 'Ivory Coast' 'Argentina' 'Cuba' 'Egypt'
'West Bank and Gaza Strip' 'Angola' 'Australia' 'Venezuela' 'Nigeria'
'Serbia-Montenegro' 'Namibia' 'Multinational' 'Norway' 'Ethiopia'
'Bangladesh' 'South Korea' 'Georgia' 'Democratic Republic of the Congo'
'Nepal' 'Guinea' 'Thailand' 'Pakistan' 'Uganda' 'Israel' 'Japan' 'Guyana'
'Burundi' 'Ecuador' 'Republic of the Congo' 'Syria' 'Netherlands'
'Albania' 'Central African Republic' 'Mexico' 'Greece' 'Niger' 'Asian'
'Eritrea' 'Azerbaijan' 'Czech Republic' 'Equatorial Guinea' 'Vatican City'
'Madagascar' 'Yemen' 'Kazakhstan' 'Mali' 'Saudi Arabia' 'Libya'
'Mozambique' 'Turkmenistan' 'Macedonia' 'Cameroon' 'Ukraine' 'South Sudan'
'Romania' 'Burkina Faso' 'Myanmar' 'Jordan']
========
gname
<type 'str'>
3454
['MANO-D' '23rd of September Communist League' 'Unknown' ...,
'The Independent Military Wing of the Syrian Revolution Abroad'
'Haji Fateh' 'Al-Fateh Al-Jadid']
========
gsubname
<type 'float'>
1099
[nan 'FALN-R' 'Palestinian Liberation Army (military wing)' ...,
'Afzal Guru Squad' 'Naga Army' 'Massina Brigade']
========
gname2
<type 'float'>
384
[nan 'Armed Revolutionary Independence Movement (MIRA)'
'Popular Front for the Liberation of Palestine (PFLP)' 'Carlos the Jackal'
'Palestine Liberation Organization (PLO)' 'Puerto Rican Nationalists'
'Organization of Volunteers for the Puerto Rican Revolution'
'Revolutionary Student Movement (MER)' 'Jewish Action Movement'
'Abu Baker Martyr Group' 'National Liberation Army of Colombia (ELN)'
"People's Revolutionary Army (ERP) (El Salvador)"
'Armed Forces of National Resistance (FARN)' 'Ex-Somoza National Guard'
'Revolutionary Armed Forces of Colombia (FARC)'
'Justice Commandos for the Armenian Genocide' 'The Mukti Bahini'
'Palestinians' 'Moro National Liberation Front (MNLF)'
'M-19 (Movement of April 19)'
'Vietnamese Organization to Exterminate Communists and Restore the Nation'
'Popular Liberation Army (EPL)' "Al-Gama'at al-Islamiyya (IG)"
"Al-Da'wah Party" 'Democratic Revolutionary Front (FDR)'
'Boricuan Armed Anti-Imperialist Commandos' 'Armed Struggle Organization'
'Zairean Socialist Party' 'Red Brigades' 'Quintin Lame' 'Hezbollah'
'Lebanese National Resistance Front'
'Ricardo Franco Front (Dissident FARC)' 'Red Army Faction (RAF)'
'America Battalion' 'Tupac Amaru Revolutionary Movement (MRTA)'
'Movement of the Revolutionary Left (MIR) (Peru)'
'Omar Torrijos Commando for Latin American Dignity'
'Patriotic Morazanista Front (FPM)' 'Karen National Union'
'The Extraditables' '1 May' 'Popular Militia (Chile)'
'Afrikaner Resistance Movement (AWB)' 'Force 17'
"Revolutionary People's Struggle (ELA)" 'Shining Path (SL)'
'Montoneros (Argentina)' 'Recompras' 'Cali Narcotics Cartel'
'Fatherland for the Poor' 'Turkish Communist Party/Marxist (TKP-ML)'
'Hizbul Mujahideen (HM)' 'Bougainville Revolutionary Army (BRA)'
'Shia Muslim extremists' 'West Nile Bank Front (WNBF)'
'Earth Liberation Front (ELF)' 'Palestinian Islamic Revolutionary Army'
'Revolutionary Bolivariano Movement 200' 'Harkat ul Ansar'
'Muslim Mujahideen' 'Animal Liberation Front (ALF)'
'Moro Islamic Liberation Front (MILF)' 'Fighting Guerrillas of May'
'Forest Brothers' 'Hamas (Islamic Resistance Movement)'
'Armed Forces Revolutionary Council (AFRC)' 'Chechen Rebels' 'Unknown'
'White Wolves (UK)' 'Aitarak Militia' 'Nationalsocialistisk Front (NSF)'
'Al-Badr' 'Revolutionaries of the Streets'
'Grupo de Combatientes Populares' 'Abu Sayyaf Group (ASG)'
'Oromo Liberation Front' 'Jamiat ul-Mujahedin (JuM)'
"United People's Democratic Solidarity (UPDS)" 'Al-Aqsa Martyrs Brigade'
'United Liberation Front of Assam (ULFA)' 'Jaish-e-Mohammad (JeM)'
'Lashkar-e-Taiba (LeT)' 'Palestinian Hezbollah' 'Mayi Mayi'
'Palestinian Islamic Jihad (PIJ)'
'Salafist Group for Preaching and Fighting (GSPC)'
'Albanian Liberation Army' "People's Revolutionary Army (ERP)"
"People's Army's Pioneers" 'Hutu extremists' 'Armed Islamic Group (GIA)'
'Ulster Freedom Fighters (UFF)' 'Asif Raza Commandos' 'Al-Qaida'
'Al-Fatah' 'Al-Mansoorian' 'Ulster Volunteer Force (UVF)' 'Al-Madina'
'Dima Halao Daoga (DHD)' 'Adan Abyan Islamic Army (AAIA)'
'Riyadus-Salikhin Reconnaissance and Sabotage Battalion of Chechen Martyrs'
'Taliban' 'Harkatul Jihad-e-Islami' 'Save Kashmir Movement'
'Hizb-I-Islami' "People's Revolutionary Militias (MRP)"
"New People's Army (NPA)" 'Harakat ul-Mujahidin (HuM)'
'Lashkar-e-Fidayan-e-Islam' 'Jemaah Islamiya (JI)'
'Tehrik-e-Jehad-e-Islami'
'National Council for Defense of Democracy (NCDD)'
'Free Aceh Movement (GAM)' 'Forces for the Defense of Democracy (FDD)'
'Great Eastern Islamic Raiders Front (IBDA-C)' 'Ansar al-Islam'
'Jamaat-E-Islami (India/Pakistan)' 'Maoist Communist Party (MKP)'
'Islamic Movement of Uzbekistan (IMU)'
'National Democratic Front of Bodoland (NDFB)' 'Egyptian Tawhid and Jihad'
'Colonel Karuna Faction' 'Ansar al-Sunna'
'Islamic Army in Iraq (al-Jaish al-Islami fi al-Iraq)'
"Jihad Martyr's Companies in Iraq" 'Black Banner Brigade'
"Kurdistan Workers' Party (PKK)" 'Al-Arifeen'
'Takfir wal-Hijra (Excommunication and Exodus)'
'Shan State Army - South (SSA-S)'
"Al-Ahwaz Arab People's Democratic Front" 'Islamic Front'
'Democratic Front for the Liberation of Palestine (DFLP)'
'Lashkar-e-Jhangvi' 'Islamic Jihad Front'
'Houthi extremists (Ansar Allah)' 'Popular Resistance Committees'
'Liberation Tigers of Tamil Eelam (LTTE)'
'Janatantrik Terai Mukti Morcha- Goit (JTMM-G)'
"Niger Delta People's Volunteer Force (NDPVF)"
'Karbi Longri North Cachar Liberation Front (KLNLF)'
"Minawi's faction forces." "Nepal People's Army"
'Irish National Liberation Army (INLA)' 'Mujahideen Youth Movement (MYM)'
'Jaish al-Muslimin (Army of the Muslims)' 'Other'
'Janatantrik Terai Mukti Morcha- Jwala Singh (JTMM-J)'
'Madhesi Mukti Tigers (MMT)' 'Jund al-Sham for Tawhid and Jihad'
"People's United Liberation Front (PULF)" 'Hizbul al Islam (Somalia)'
'8 March Coalition'
'National Socialist Council of Nagaland-Khaplang (NSCN-K)'
'United Self Defense Units of Colombia (AUC)'
'Janatantrik Terai Mukti Morcha- Ranbir Singh (JTMM-RS)'
'Niger Delta Patriotic Force' 'Black Widows'
'Students Islamic Movement of India (SIMI)' 'Madhesi Liberation Front'
'Armed Revolutionary Action (ENEDRA)' 'Young Communist League'
'Ahlu-sunah Wal-jamea (Somalia)'
'National Liberation Front of Tripura (NLFT)' 'Los Rastrojos (Colombia)'
'Revolutionary Nuclei' 'Mahdi Army'
'Communist Party of India - Maoist (CPI-Maoist)' "Asa'ib Ahl al-Haqq"
'Terai Janatantrik Party (TJP)'
"People's Committee against Police Atrocities (PCPA)"
'Democratic Front for the Liberation of Rwanda (FDLR)'
'Ogaden National Liberation Front (ONLF)'
'Tehrik-i-Taliban Pakistan (TTP)' 'Terrorists Guerrilla Group'
'Revolutionary Struggle'
'Janatantrik Terai Mukti Morcha- Rajan Mukti (JTMM-R)'
'Jharkhand Mukti Morcha (JMM)' 'Ansar Al Sunnah (Palestine)'
'Informal Anarchist Federation' 'Islamic State of Iraq (ISI)'
'Al-Qaida in Iraq' "Sudan People's Liberation Army (SPLA)" 'Laqmush'
'Janjaweed' "Al-Shabaab al-Mu'minin" 'Khatm-e-Nabuwat (KeN)'
'Amr Bil Maroof Wa Nahi Anil Munkir' 'Baloch Liberation Front (BLF)'
'Achik National Volunteer Council (ANVC)' 'Indian Mujahideen'
'Zeliangrong United Front' 'Red Sea Afar Democratic Organization (RSADO)'
"People's Liberation Army (India)" 'Boko Haram'
'Abu Hafs Katibatul al-Ghurba al-Mujahideen' 'February 12 Movement'
'United Ethnic Liberation Front (UELF)' 'Jundallah (Pakistan)'
'Lashkar-e-Islam (Pakistan)' 'Al-Qaida in the Islamic Maghreb (AQIM)'
'Al-Qaida in the Arabian Peninsula (AQAP)' 'Garo National Liberation Army'
'Fulani extremists' 'Liwa al-Islam'
'United National Liberation Front (UNLF)' 'Al-Nusrah Front'
'Free Syrian Army' 'Jamaah Ansharut Tauhid (JAT)' 'Islamic Front (Syria)'
'Convention of Patriots for Justice and Peace' 'Ahrar al-Sham'
'Circle of Violators/Nucleus Lovers of Anomy'
'Instigators of Social Explosion' 'United Achik Liberation Army (UALA)'
"Kata'ib Hezbollah" 'Al-Qaida in the Indian Subcontinent'
'Loyalist Volunteer Forces (LVF)' 'International Revolutionary Front'
'Ansar al-Dine (Mali)' 'Bangsamoro Islamic Freedom Movement (BIFM)'
'Syrian Resistance'
"Al-Mua'qi'oon Biddam Brigade (Those who Sign with Blood)" 'Jaish Usama'
'Jamat al-Tawhid wal-Qisas' 'Ansar al-Sharia (Tunisia)'
'Kilafah Islamic Movement' "Sudan People's Liberation Movement - North"
'Haqqani Network' 'Jaish al-Muhajireen wal-Ansar (Muhajireen Army)'
'Baloch Nationalists' 'Ansar Bayt al-Maqdis (Ansar Jerusalem)'
'All Coppers Are Bastards (ACAB)' 'Mahaz Fedai Tahrik Islami Afghanistan'
'Jund al-Islam' 'Ahrar Al-Jalil (Free People of the Galilee)' 'Al-Shabaab'
'Murle Tribe' 'Rabha National Security Force' 'Al-Shuda Brigade'
'Sipah-I-Mohammed' 'Tribesmen' 'Mujahideen Ansar' 'Maoists'
'Island Brigade (Libya)' 'Achik National Volunteer Council-B (ANVC-B)'
'Hadramawt Tribes Alliance' 'Abdullah Azzam Brigades'
'Greater Damascus Operations Room' 'Southern Front'
'Baloch Waja Liberation Army (BWLA)'
'Movement for Oneness and Jihad in West Africa (MUJAO)'
'Islamic State of Iraq and the Levant (ISIL)'
'Baloch Liberation Army (BLA)'
'Movement for the Actualization of the Sovereign State of Biafra (MASSOB)'
'Muslim Brotherhood' 'Sudan Liberation Army-Minni Minawi (SLA-MM)'
'United Baloch Army (UBA)' 'Baloch Republican Army (BRA)'
'Liwa Ahrar al-Sunna' 'Southern Mobility Movement (Yemen)'
"Achik Songna An'pachakgipa Kotok (ASAK)"
'November 17 Revolutionary Organization (N17RO)' 'Al-Furqan Brigades'
'Lashkar-e-Jarrar' "Karbi People's Liberation Tigers (KPLT)"
'Ansar al-Sharia (Libya)' 'Mombasa Republican Council (MRC)'
'Balochistan Liberation United Front (BLUF)' 'Libya Shield Force'
'Abu Baker al-Siddiq Brigade' 'Democratic Union Party (PYD)' 'Loyalists'
'Al-Sawaiq Brigade' 'Al-Naqshabandiya Army' 'Halqa-e-Mehsud'
'Tehrik-e-Khilafat' 'Bru Democratic Front of Mizoram (BDFM)' 'Seleka'
'Al-Qaqa Brigade' 'Anti-Balaka Militia' 'Jamaat-ul-Ahrar'
'Military Council of the Tribal Revolutionaries (MCTR)'
"Odua Peoples' Congress (OPC)" 'Ansar al-Din Front'
'Popular Resistance Movement (Egypt)' 'Jamaat-E-Islami (Bangladesh)'
'Waning Abdusalam Group (WAG)'
'Azawad National Liberation Movement (MNLA)'
"Jama'atul Mujahideen Bangladesh (JMB)"
'Khorasan Chapter of the Islamic State' "Abu Salim Martyr's Brigade"
'Tuareg extremists' 'Okba Ibn Nafaa Brigade'
'Barqa Province of the Islamic State' 'Jund al-Aqsa'
'Shura Council of Benghazi Revolutionaries'
'Supporters of Abd Rabbuh Mansur Hadi'
'National Socialist Council of Nagaland-Isak-Muivah (NSCN-IM)'
'Jaysh al-Islam (Syria)' 'Supporters of the Islamic State in Jerusalem'
'Ajnad Misr' 'Al-Sham Legion' 'Arab Movement of Azawad (MAA)'
'Devrimici Halk Kurtulus Cephesi (DHKP/C)'
"A'chik Matgrik Elite Force (AMEF)" 'Mai Mai Bakata Katanga Militia'
'Kanglei Yawol Kanna Lup (KYKL)' 'Al-Islah Party'
'Macina Liberation Front (FLM)' 'Sinai Province of the Islamic State'
'Nyatura Militia' 'Democratic Front of the Central African People (FDPC)'
'Army of the Tribes' 'Bahir Eldeen Brigade' 'Komala'
'Ansarullah Bangla Team' "People's Defense Unit (Turkey)" 'Grey Wolves'
'Black Bloc' 'Lashkar-e-Islam (India)'
'Shura Council of Ajdabiya Revolutionaries'
"People's Liberation Front of India" 'Pentagon Kidnap Group' 'Al-Khobar'
'Democratic Force for the Defense of Human Rights (FDDH)'
'Tehrik al-Mojahedin' 'Misrata Brigades' 'Uzair Baloch Gang'
'White extremists' 'Syrian Turkmen Brigades'
'Ansar Al-Mujahideen (Pakistan)' 'Tripoli Province of the Islamic State'
'Free Papua Movement (OPM-Organisasi Papua Merdeka)' 'Gaddafi loyalists'
'The New Irish Republican Army' 'Badr Brigades' 'Jaish-e-Islam'
'Mujahidin Indonesia Timur (MIT)' 'Saraya al-Salam'
'Adan-Abyan Province of the Islamic State'
'Revolutionary Punishment Movement' 'Nduma Defense of Congo (NDC)'
'United Freedom Forces (BOG)' 'Lahij Province of the Islamic State'
'Maute Group' 'Shamiya Front'
'Alliance of Patriots for a Free and Sovereign Congo (APCLS)'
'Lekagak Tenggamati' 'Majlis-e-Lashkari' 'Runda Kumpulan Kecil (RKK)'
'Abdul Ghani Kikli Militia' 'Barisan Revolusi Nasional (BRN)'
'Imam al-Bukhari Brigade' 'Kuki National Front (KNF)' 'Ajnad al-Sham'
'Civil Protection Units (YPS)' 'Allied Democratic Forces (ADF)'
'Jaish al-Adl'
"Sudan People's Liberation Movement in Opposition (SPLM-IO)"
'Niger Delta Volunteers (NDV)' 'Kurdish Islamic Group (KIG)'
'Al-Nasir Army (Syria)' 'United Democratic Liberation Army (UDLA)'
'Fetullah Terrorist Organization'
'National Alliance for the Protection of the Fulani Identity and the Restoration of Justice (ANSIPRJ)'
'Jaish al-Mujahideen (Syria)' 'Muslim extremists'
'Niger Delta Avengers (NDA)' 'Ahfad al-Sahaba-Aknaf Bayt al-Maqdis'
'Islamic State in the Greater Sahara (ISGS)'
'All Nepal National Free Student Union-Revolutionary'
'Ahle Sunnat Wal Jamaat (ASWJ-Pakistan)'
'Rohingya Solidarity Organization' 'Free Idlib Army' 'Arakan Army (AA)'
'National Democratic Alliance Army (NDAA-ESSA)'
'Kachin Independence Army (KIA)' "Ta'ang National Liberation Army (TNLA)"
'Ansar Al-Khilafa (Philippines)' 'Jeay Sindh Qaumi Mahaz (JSQM)'
'Jaish al-Fatah (Syria)' 'Khasavyurt Group']
========
gsubname2
<type 'float'>
59
[nan 'Islamic Jihad' 'The Family' 'Abu Ali Mustafa Brigades'
'Izz-al-Din al-Qassam Brigades'
'Forces for the Defense of Democracy (FDD)' 'al-Quds Brigades'
'Kongra-Gel' 'National Resistance Brigades'
"The National Resistance Brigades-Martyr Sa'id Hajuj Groups"
'Al Nasir Salah al-Din Brigades' 'Los Rastrojos' 'Fidayeen'
'Tritiya Prastuti Committee (TPC)' 'Islamic Shiite Resistance in Iraq'
'Frente 30' 'Frente 55' 'Jund al-Sham for Tawhid and Jihad'
'Jacobo Arenas Mobile Column' 'Manuel Cepeda Varga Urban Front'
'Al Quds Brigades' 'Alirio Torres Mobile Column'
"Revolutionary People's Front" 'Ahrar al-Sham' 'Intact Revolutionary Cell'
'Junood-ul-Hifsa' 'Al-Nusrah Front in Lebanon' 'Marwan Hadid Brigades'
'Ajnad al-Sham' 'Sangbojit faction' 'Jund al-Aqsa' 'Damascus Prefecture'
'South Indian Mujahideen' 'Ansar al-Sharia in Benghazi'
'Central Libya Shield' 'Intifadat Ahrar al-Iraq' 'Division 13'
'Suqour al-Sham' 'Jaish al-Muhajireen wal-Ansar (Muhajireen Army)'
'Ezzedine al-Qassam Brigades' '101st Battalion'
"Turkish Workers and Peasants' Liberation Army (TIKKO)"
'Yahya Ayyash Brigade' 'Naeem Bukhari Group' 'Supremacists'
'Khorasan Wing' 'Nehlun' 'Homs Liberation Movement' 'Jamaat-ul-Ahrar'
'Ansar al-Islam' 'Islami Chhatra Shibir (ICS)' 'Al-Rahman Corps'
'Jaish al-Tahrir' 'First Army' 'Al-Izzah'
'The Fastaqim Kama Umirta Gathering'
'Liwa al-Sultan Murad; Central Division' 'Al-Alami' '252 Mobile Battalion']
========
gname3
<type 'float'>
104
[nan 'Guerrilla Column 29 September' 'Lebanese Resistance Group'
'Armed Revolutionary Nuclei (NAR)' 'M-19 (Movement of April 19)'
'Armed Forces of Popular Resistance (FARP)'
'November 17 Revolutionary Organization (N17RO)' 'SKIF Detachment'
'Unknown' 'Umar al-Mukhtar Martyr Forces' 'Harkatul Jihad-e-Islami'
'Al-Aqsa Martyrs Brigade' 'Al-Fatah'
'Popular Front for the Liberation of Palestine (PFLP)'
'Jamiat ul-Mujahedin (JuM)'
'Democratic Front for the Liberation of Palestine (DFLP)'
'Achik National Volunteer Council (ANVC)' 'Al-Barq'
'Islamic International Peacekeeping Brigade (IIPB)'
'Palestinian Islamic Jihad (PIJ)' 'Hizb-I-Islami' 'Tanzim'
'Hizb al-Tahrir al-Islami (HT)'
'Jamaa Al-Islamiya Al-Alamiya (World Islamist Group)'
'Mutassim Bellah Brigade' 'Popular Resistance Committees'
'Rajah Solaiman Revolutionary Movement' 'Farzandan-e-Millat'
'Karenni National Progressive Party' 'Armed Renaissance Group of Ahvaz'
'Jaish-e-Mohammad (JeM)' 'Sirri Powz' 'Other' 'Lashkar-e-Taiba (LeT)'
'Al-Qassam Brigades' '313 Brigade' 'Conspiracy of Cells of Fire'
'Terai Army' 'United National Liberation Front (UNLF)' 'Free Syrian Army'
'Jamaat-E-Islami (Bangladesh)' 'Tehrik-i-Taliban Pakistan (TTP)'
'Boko Haram' 'Moro Islamic Liberation Front (MILF)' 'Ahrar al-Sham'
'Liwa al-Islam' 'Bangsamoro Islamic Freedom Movement (BIFM)'
'Ansar al-Dine (Mali)' 'Zwai Tribe' 'Lashkar-e-Jhangvi' 'Misrata Brigades'
'Rafallah al-Sahati Brigade' 'Islamic Front (Syria)'
'Azawad National Liberation Movement (MNLA)' 'Halqa-e-Mehsud' 'Taliban'
'Libya Shield Force' 'Lashkar-e-Balochistan' 'Jundallah (Pakistan)'
'Haftar Militia' 'Military Council of the Tribal Revolutionaries (MCTR)'
'Al-Nusrah Front' 'Lashkar-e-Islam (Pakistan)' 'Shamiya Front'
'Ansar al-Sharia (Libya)' 'United Liberation Front of Assam (ULFA)'
'Ansar al-Din Front' 'Jund al-Aqsa' 'Al-Sham Legion'
'Kangleipak Communist Party (KCP)' 'Muslim Brotherhood'
'Hamas (Islamic Resistance Movement)' 'Macina Liberation Front (FLM)'
'Kurdistan Free Life Party' 'Eastern Turkistan Islamic Movement (ETIM)'
'Bangladesh Nationalist Party (BNP)' 'Islamic State in Bangladesh'
'Al-Qaida in the Islamic Maghreb (AQIM)'
'Islamic State of Iraq and the Levant (ISIL)'
'Al-Muthana Islamic Movement'
'Democratic Front for the Liberation of Rwanda (FDLR)'
'Abu Sayyaf Group (ASG)' 'Jaysh al-Islam (Syria)'
'Northern Homs Countryside Operations Room'
'Al-Qaida in the Indian Subcontinent' 'Baloch Republican Army (BRA)'
'Sindhu Desh Liberation Army (SDLA)' 'Turkestan Islamic Party'
"Jama'atul Mujahideen Bangladesh (JMB)" "Lord's Resistance Army (LRA)"
'Al-Nasir Army (Syria)' 'Southern Front' 'Mai Mai Mazembe Militia'
'Maute Group' 'Maoist Communist Central of Nepal (MCCN)' 'Ajnad al-Sham'
'Free Idlib Army' 'Authenticity and Development Front'
'Jaish al-Mujahideen (Syria)' 'Kurdistan Freedom Hawks (TAK)'
"People's Liberation Army (India)"
'National Democratic Alliance Army (NDAA-ESSA)'
'Kachin Independence Army (KIA)' 'Fetullah Terrorist Organization']
========
gsubname3
<type 'float'>
14
[nan 'Commander Ibn al-Khattab' 'Jihad Jibril' 'Ahrar al-Sham'
'Paresh Barua' 'Jaish al-Muhajireen wal-Ansar (Muhajireen Army)'
'Ezzedine al-Qassam Brigades' 'Al-Rahman Corps'
'Turkistan Islamic Party (Syria)' 'Islami Chhatra Shibir (ICS)'
'Al-Izzah; Jaish al-Tahrir' 'Al-Alami'
'The Fastaqim Kama Umirta Gathering' 'Shehryar Mehsud Group']
========
motive
<type 'float'>
13034
[nan 'To protest the Cairo Illinois Police Deparment'
'To protest the War in Vietnam and the draft' ...,
'The specific motive is unknown; however, sources noted that Qari Zubai was the brother of an Afghan Local Police (ALP) officer.'
'The specific motive is unknown; however, sources noted that Manzurul Islam Liton was critical of Jamaat-E-Islami (Bangladesh).'
"The specific motive is unknown; however, sources posited that the civilians were abducted in order to transport stolen goods for the Lord's Resistance Army (LRA)."]
========
guncertain1
<type 'numpy.float64'>
3
[ 0. 1. nan]
========
guncertain2
<type 'numpy.float64'>
3
[ nan 1. 0.]
========
guncertain3
<type 'numpy.float64'>
3
[ nan 0. 1.]
========
individual
<type 'numpy.int64'>
2
[0 1]
========
nperps
<type 'numpy.float64'>
113
[ nan 7.00000000e+00 -9.90000000e+01 3.00000000e+00
1.00000000e+00 5.00000000e+00 2.00000000e+00 4.00000000e+00
6.00000000e+00 4.20000000e+01 2.20000000e+01 9.00000000e+00
2.50000000e+01 1.60000000e+01 1.10000000e+01 1.20000000e+01
8.00000000e+00 0.00000000e+00 1.50000000e+01 1.00000000e+01
1.80000000e+01 1.70000000e+01 2.00000000e+02 3.00000000e+01
6.00000000e+01 2.00000000e+01 5.00000000e+01 1.30000000e+01
2.40000000e+01 7.00000000e+01 4.00000000e+01 1.00000000e+02
1.40000000e+01 1.40000000e+02 8.00000000e+01 3.20000000e+01
4.00000000e+02 1.00000000e+03 2.50000000e+02 3.50000000e+01
1.50000000e+02 3.00000000e+02 7.50000000e+01 5.00000000e+02
6.00000000e+02 4.40000000e+01 4.50000000e+01 3.80000000e+01
9.00000000e+01 1.20000000e+02 3.40000000e+01 2.70000000e+01
1.80000000e+02 9.00000000e+02 1.20000000e+03 3.70000000e+02
1.30000000e+02 7.50000000e+02 4.80000000e+01 7.00000000e+02
7.20000000e+01 3.30000000e+01 3.90000000e+01 4.90000000e+01
2.60000000e+01 1.90000000e+01 2.90000000e+02 6.80000000e+01
1.60000000e+02 2.04000000e+02 2.80000000e+01 3.60000000e+01
2.10000000e+01 2.50000000e+04 2.90000000e+01 1.50000000e+03
2.50000000e+03 1.90000000e+02 4.70000000e+01 1.00000000e+04
1.38000000e+02 2.00000000e+04 3.50000000e+02 5.10000000e+01
5.50000000e+01 5.60000000e+01 8.00000000e+02 3.20000000e+03
5.00000000e+03 3.10000000e+01 4.50000000e+02 4.10000000e+01
8.70000000e+01 3.00000000e+03 2.00000000e+03 8.40000000e+01
5.20000000e+01 -9.00000000e+00 2.30000000e+02 1.56000000e+02
5.50000000e+02 1.25000000e+02 5.30000000e+01 2.30000000e+01
1.73000000e+02 2.07000000e+02 5.40000000e+01 5.90000000e+01
6.40000000e+01 1.01000000e+02 8.60000000e+01 5.80000000e+01
3.01000000e+02]
========
nperpcap
<type 'numpy.float64'>
51
[ nan -99. 1. 2. 0. 4. 3. 6. 5. 7. 8.
9. 10. 26. 24. 13. 14. 45. 12. 11. 2.5
25. 32. 27. -9. 15. 43. 21. 50. 406. 17. 100.
60. 87. 55. 20. 29. 76. 40. 271. 28. 16. 19.
30. 200. 41. 18. 126. 23. 22. 63. ]
========
claimed
<type 'numpy.float64'>
4
[ nan 0. 1. -9.]
========
claimmode
<type 'numpy.float64'>
11
[ nan 1. 10. 3. 9. 8. 5. 2. 7. 4. 6.]
========
claimmode_txt
<type 'float'>
11
[nan 'Letter' 'Unknown' 'Call (pre-incident)' 'Other' 'Personal claim'
'Note left at scene' 'Call (post-incident)'
'Posted to website, blog, etc.' 'E-mail' 'Video']
========
claim2
<type 'numpy.float64'>
4
[ nan 0. 1. -9.]
========
claimmode2
<type 'numpy.float64'>
10
[ nan 2. 10. 1. 5. 9. 7. 4. 8. 6.]
========
claimmode2_txt
<type 'float'>
10
[nan 'Call (post-incident)' 'Unknown' 'Letter' 'Note left at scene' 'Other'
'Posted to website, blog, etc.' 'E-mail' 'Personal claim' 'Video']
========
claim3
<type 'numpy.float64'>
3
[ nan 1. 0.]
========
claimmode3
<type 'numpy.float64'>
9
[ nan 1. 9. 2. 10. 7. 6. 8. 4.]
========
claimmode3_txt
<type 'float'>
9
[nan 'Letter' 'Other' 'Call (post-incident)' 'Unknown'
'Posted to website, blog, etc.' 'Video' 'Personal claim' 'E-mail']
========
compclaim
<type 'numpy.float64'>
4
[ nan 0. 1. -9.]
========
weaptype1
<type 'numpy.int64'>
12
[13 6 8 5 2 7 9 11 10 3 12 1]
========
weaptype1_txt
<type 'str'>
12
['Unknown' 'Explosives/Bombs/Dynamite' 'Incendiary' 'Firearms' 'Chemical'
'Fake Weapons' 'Melee' 'Sabotage Equipment'
'Vehicle (not to include vehicle-borne explosives, i.e., car or truck bombs)'
'Radiological' 'Other' 'Biological']
========
weapsubtype1
<type 'numpy.float64'>
30
[ nan 16. 5. 2. 19. 20. 4. 18. 11. 15. 28. 17. 10. 14. 1.
9. 3. 21. 29. 7. 23. 8. 22. 12. 24. 30. 27. 26. 13. 6.]
========
weapsubtype1_txt
<type 'str'>
30
[nan 'Unknown Explosive Type' 'Unknown Gun Type' 'Automatic Weapon'
'Molotov Cocktail/Petrol Bomb' 'Gasoline or Alcohol'
'Rifle/Shotgun (non-automatic)' 'Arson/Fire'
'Projectile (rockets, mortars, RPGs, etc.)' 'Vehicle' 'Dynamite/TNT'
'Other Explosive Type' 'Pressure Trigger' 'Time Fuse' 'Poisoning'
'Letter Bomb' 'Handgun' 'Blunt Object' 'Sticky Bomb' 'Grenade'
'Knife or Other Sharp Object' 'Land Mine' 'Hands, Feet, Fists'
'Remote Trigger' 'Rope or Other Strangling Device' 'Explosive'
'Unknown Weapon Type' 'Suffocation'
'Suicide (carried bodily by human being)' 'Other Gun Type']
========
weaptype2
<type 'numpy.float64'>
12
[ nan 5. 9. 8. 6. 12. 11. 2. 7. 13. 10. 1.]
========
weaptype2_txt
<type 'float'>
12
[nan 'Firearms' 'Melee' 'Incendiary' 'Explosives/Bombs/Dynamite' 'Other'
'Sabotage Equipment' 'Chemical' 'Fake Weapons' 'Unknown'
'Vehicle (not to include vehicle-borne explosives, i.e., car or truck bombs)'
'Biological']
========
weapsubtype2
<type 'numpy.float64'>
29
[ nan 3. 5. 23. 20. 2. 7. 18. 19. 4. 22. 16. 14. 26. 21.
11. 24. 9. 28. 8. 27. 17. 12. 6. 13. 10. 1. 30. 15.]
========
weapsubtype2_txt
<type 'float'>
29
[nan 'Handgun' 'Unknown Gun Type' 'Knife or Other Sharp Object'
'Gasoline or Alcohol' 'Automatic Weapon' 'Grenade' 'Arson/Fire'
'Molotov Cocktail/Petrol Bomb' 'Rifle/Shotgun (non-automatic)'
'Hands, Feet, Fists' 'Unknown Explosive Type' 'Time Fuse' 'Suffocation'
'Blunt Object' 'Projectile (rockets, mortars, RPGs, etc.)'
'Rope or Other Strangling Device' 'Letter Bomb' 'Dynamite/TNT' 'Land Mine'
'Unknown Weapon Type' 'Other Explosive Type' 'Remote Trigger'
'Other Gun Type' 'Suicide (carried bodily by human being)'
'Pressure Trigger' 'Poisoning' 'Explosive' 'Vehicle']
========
weaptype3
<type 'numpy.float64'>
11
[ nan 13. 5. 9. 8. 6. 12. 7. 11. 10. 2.]
========
weaptype3_txt
<type 'float'>
11
[nan 'Unknown' 'Firearms' 'Melee' 'Incendiary' 'Explosives/Bombs/Dynamite'
'Other' 'Fake Weapons' 'Sabotage Equipment'
'Vehicle (not to include vehicle-borne explosives, i.e., car or truck bombs)'
'Chemical']
========
weapsubtype3
<type 'numpy.float64'>
24
[ nan 23. 2. 16. 7. 11. 3. 21. 5. 4. 17. 18. 19. 28. 26.
8. 20. 24. 12. 22. 6. 15. 27. 1.]
========
weapsubtype3_txt
<type 'float'>
24
[nan 'Knife or Other Sharp Object' 'Automatic Weapon'
'Unknown Explosive Type' 'Grenade'
'Projectile (rockets, mortars, RPGs, etc.)' 'Handgun' 'Blunt Object'
'Unknown Gun Type' 'Rifle/Shotgun (non-automatic)' 'Other Explosive Type'
'Arson/Fire' 'Molotov Cocktail/Petrol Bomb' 'Dynamite/TNT' 'Suffocation'
'Land Mine' 'Gasoline or Alcohol' 'Rope or Other Strangling Device'
'Remote Trigger' 'Hands, Feet, Fists' 'Other Gun Type' 'Vehicle'
'Unknown Weapon Type' 'Poisoning']
========
weaptype4
<type 'numpy.float64'>
6
[ nan 6. 9. 5. 8. 12.]
========
weaptype4_txt
<type 'float'>
6
[nan 'Explosives/Bombs/Dynamite' 'Melee' 'Firearms' 'Incendiary' 'Other']
========
weapsubtype4
<type 'numpy.float64'>
17
[ nan 16. 11. 21. 2. 7. 5. 8. 23. 4. 27. 18. 3. 14. 20.
17. 28.]
========
weapsubtype4_txt
<type 'float'>
17
[nan 'Unknown Explosive Type' 'Projectile (rockets, mortars, RPGs, etc.)'
'Blunt Object' 'Automatic Weapon' 'Grenade' 'Unknown Gun Type' 'Land Mine'
'Knife or Other Sharp Object' 'Rifle/Shotgun (non-automatic)'
'Unknown Weapon Type' 'Arson/Fire' 'Handgun' 'Time Fuse'
'Gasoline or Alcohol' 'Other Explosive Type' 'Dynamite/TNT']
========
weapdetail
<type 'str'>
18247
[nan 'Explosive' 'Incendiary' ...,
'Swords and sticks were used in the attack.'
'Grenades, rockets, and another explosive device were used in the attack.'
'Multiple 40-mm rocket-propelled grenades (RPGs) and automatic firearms were used in the attack.']
========
nkill
<type 'numpy.float64'>
200
[ 1.00000000e+00 0.00000000e+00 nan 7.00000000e+00
4.70000000e+01 2.00000000e+00 3.60000000e+01 5.00000000e+00
3.00000000e+00 4.00000000e+00 2.50000000e+01 1.50000000e+01
2.60000000e+01 8.00000000e+00 8.10000000e+01 6.00000000e+00
9.00000000e+00 1.60000000e+01 3.00000000e+01 3.10000000e+01
1.20000000e+01 2.10000000e+01 1.10000000e+01 1.40000000e+01
8.80000000e+01 1.00000000e+01 2.70000000e+01 1.80000000e+01
2.20000000e+01 1.90000000e+01 9.20000000e+01 1.30000000e+01
7.30000000e+01 1.00000000e+02 4.20000000e+01 4.30000000e+01
1.70000000e+01 9.80000000e+01 4.22000000e+02 4.80000000e+01
3.40000000e+01 5.40000000e+01 5.00000000e+01 3.50000000e+01
2.00000000e+01 4.10000000e+01 3.70000000e+01 2.80000000e+01
4.00000000e+01 3.20000000e+01 7.60000000e+01 2.30000000e+01
3.00000000e+02 6.00000000e+01 2.40000000e+01 5.80000000e+01
7.00000000e+01 8.70000000e+01 4.50000000e+01 3.80000000e+01
2.90000000e+01 7.40000000e+01 8.30000000e+01 9.00000000e+01
6.60000000e+01 8.00000000e+01 6.70000000e+01 5.10000000e+01
3.90000000e+01 1.14000000e+02 1.24000000e+02 8.90000000e+01
3.30000000e+01 7.50000000e+01 5.70000000e+01 6.20000000e+01
4.60000000e+01 5.60000000e+01 6.30000000e+01 1.20000000e+02
1.02000000e+02 7.80000000e+01 7.90000000e+01 5.20000000e+01
7.70000000e+01 2.00000000e+02 4.90000000e+01 1.11000000e+02
1.65000000e+02 4.40000000e+01 2.41000000e+02 6.40000000e+01
1.08000000e+02 6.50000000e+01 1.32000000e+02 2.70000000e+02
2.28000000e+02 1.10000000e+02 1.36000000e+02 1.80000000e+02
2.50000000e+02 9.30000000e+01 1.30000000e+02 5.90000000e+01
9.40000000e+01 5.30000000e+01 1.46000000e+02 3.29000000e+02
9.70000000e+01 7.10000000e+01 2.40000000e+02 2.27000000e+02
1.26000000e+02 1.06000000e+02 3.88000000e+02 6.80000000e+01
8.40000000e+01 8.20000000e+01 1.71000000e+02 1.07000000e+02
5.50000000e+01 1.12000000e+02 7.20000000e+01 9.60000000e+01
1.40000000e+02 6.10000000e+01 1.05000000e+02 1.50000000e+02
1.15000000e+02 1.18000000e+03 1.70000000e+02 8.50000000e+01
1.68000000e+02 1.21000000e+02 3.75000000e+02 9.10000000e+01
3.04000000e+02 1.23000000e+02 1.35000000e+02 2.56000000e+02
1.09000000e+02 2.71000000e+02 2.06000000e+02 1.04000000e+02
3.20000000e+02 2.75000000e+02 2.24000000e+02 1.18000000e+02
1.29000000e+02 9.50000000e+01 2.59000000e+02 1.38300000e+03
1.38200000e+03 1.89000000e+02 1.19000000e+02 1.01000000e+02
1.16000000e+02 5.18000000e+02 3.44000000e+02 1.60000000e+02
1.88000000e+02 1.03000000e+02 2.02000000e+02 1.45000000e+02
1.53000000e+02 1.27000000e+02 6.90000000e+01 1.41000000e+02
1.34000000e+02 4.00000000e+02 8.60000000e+01 1.84000000e+02
2.10000000e+02 1.42000000e+02 2.12000000e+02 2.87000000e+02
3.15000000e+02 1.51000000e+02 6.70000000e+02 1.50000000e+03
3.10000000e+02 2.98000000e+02 5.00000000e+02 5.17000000e+02
2.01000000e+02 1.22000000e+02 1.58000000e+02 1.17000000e+02
1.44000000e+02 1.52000000e+02 2.30000000e+02 2.80000000e+02
1.74000000e+02 1.43000000e+02 3.83000000e+02 2.83000000e+02
1.54000000e+02 2.84000000e+02 1.90000000e+02 4.33000000e+02]
========
nkillus
<type 'numpy.float64'>
31
[ nan 0.00000000e+00 2.00000000e+00 1.00000000e+00
4.00000000e+00 3.00000000e+00 8.00000000e+00 7.00000000e+00
3.00000000e+01 1.10000000e+01 5.00000000e+00 1.70000000e+01
2.41000000e+02 6.00000000e+00 3.10000000e+01 1.89000000e+02
1.68000000e+02 1.90000000e+01 6.00000000e+01 1.20000000e+01
1.50000000e+01 1.35800000e+03 1.32500000e+03 1.81000000e+02
3.80000000e+01 9.00000000e+00 1.40000000e+01 1.60000000e+01
2.00000000e+01 1.30000000e+01 4.40000000e+01]
========
nkillter
<type 'numpy.float64'>
91
[ nan 0. 2. 1. 3. 4. 5. 15. 85. 7. 6. 9.
12. 14. 10. 18. 11. 8. 20. 17. 60. 34. 23. 24.
21. 35. 16. 41. 13. 80. 100. 300. 47. 70. 50. 64.
25. 30. 19. 48. 62. 40. 500. 27. 32. 52. 53. 36.
22. 26. 45. 28. 151. 29. 31. 38. 58. 57. 207. 200.
51. 110. 346. 59. 101. 81. 201. 180. 116. 33. 143. 123.
55. 54. 86. 73. 156. 136. 46. 65. 90. 39. 43. 63.
102. 72. 67. 250. 140. 56. 301.]
========
nwound
<type 'numpy.float64'>
234
[ 0.00000000e+00 nan 1.00000000e+00 2.00000000e+00
7.00000000e+00 9.00000000e+00 1.70000000e+01 5.00000000e+00
3.00000000e+00 1.00000000e+01 1.20000000e+01 2.00000000e+01
4.00000000e+00 1.10000000e+01 2.70000000e+01 1.30000000e+01
1.90000000e+01 1.30000000e+02 5.60000000e+01 2.40000000e+01
6.00000000e+00 7.20000000e+01 2.38000000e+02 5.50000000e+01
1.50000000e+01 8.00000000e+00 1.80000000e+01 5.00000000e+01
3.40000000e+01 1.40000000e+01 7.00000000e+01 4.10000000e+01
4.80000000e+01 3.60000000e+01 2.50000000e+01 8.10000000e+01
5.40000000e+01 5.30000000e+01 1.00000000e+02 4.50000000e+01
3.30000000e+01 4.00000000e+01 6.20000000e+01 7.40000000e+01
2.20000000e+01 3.10000000e+01 1.60000000e+01 3.00000000e+01
2.85000000e+02 2.30000000e+01 4.20000000e+01 4.30000000e+01
7.60000000e+01 4.40000000e+01 5.20000000e+01 4.60000000e+01
4.90000000e+01 1.60000000e+02 3.70000000e+01 2.10000000e+01
6.00000000e+01 7.80000000e+01 2.60000000e+01 2.80000000e+01
3.90000000e+01 3.80000000e+01 3.50000000e+01 3.20000000e+01
8.00000000e+01 4.70000000e+01 1.88000000e+02 2.15000000e+02
8.50000000e+01 7.50000000e+01 1.61000000e+02 9.00000000e+01
3.00000000e+02 9.50000000e+01 1.35000000e+02 6.10000000e+01
1.38000000e+02 7.10000000e+01 7.00000000e+02 6.60000000e+01
1.36000000e+02 1.20000000e+02 2.17000000e+02 3.19000000e+02
1.33000000e+02 6.80000000e+01 7.30000000e+01 2.90000000e+01
7.51000000e+02 2.00000000e+02 1.12000000e+02 2.50000000e+02
8.20000000e+01 1.32000000e+02 2.30000000e+02 1.07000000e+02
1.14000000e+02 8.40000000e+01 1.40000000e+02 1.50000000e+02
9.60000000e+01 5.10000000e+01 5.80000000e+01 6.40000000e+01
2.95000000e+02 1.06000000e+02 1.25000000e+02 6.90000000e+01
5.90000000e+01 5.70000000e+01 1.22000000e+02 1.09000000e+02
8.80000000e+01 1.15000000e+02 1.76000000e+02 2.20000000e+02
9.70000000e+01 6.50000000e+01 8.00000000e+02 1.73000000e+02
9.20000000e+01 5.00000000e+02 2.36000000e+02 9.80000000e+01
2.86000000e+02 1.41000000e+02 5.50000000e+03 6.50000000e+02
6.71000000e+02 8.60000000e+01 1.04000000e+02 8.30000000e+01
1.01000000e+02 1.27200000e+03 1.05000000e+02 3.86000000e+02
3.91000000e+02 1.10000000e+02 1.49000000e+02 8.90000000e+01
9.10000000e+01 1.19000000e+02 7.70000000e+01 1.18000000e+02
6.70000000e+01 1.70000000e+02 1.94000000e+02 1.92000000e+02
2.27000000e+02 2.60000000e+02 4.00000000e+03 1.80000000e+02
1.84000000e+02 9.90000000e+01 9.40000000e+01 1.37000000e+02
7.36600000e+03 7.36500000e+03 1.71000000e+02 1.21000000e+02
1.62000000e+02 1.97000000e+02 1.51000000e+02 2.24000000e+02
1.34000000e+02 2.33000000e+02 1.67000000e+02 4.50000000e+02
2.16000000e+02 1.45000000e+02 6.30000000e+01 7.27000000e+02
1.82000000e+02 1.59000000e+02 1.08000000e+02 1.28000000e+02
3.40000000e+02 1.63000000e+02 5.42000000e+02 8.70000000e+01
1.02000000e+02 1.55000000e+02 8.17000000e+02 2.57000000e+02
1.48000000e+02 1.23000000e+02 2.46000000e+02 1.27000000e+02
1.03000000e+02 3.47000000e+02 1.78000000e+02 1.68000000e+02
2.07000000e+02 1.83000000e+02 1.17000000e+02 7.50000000e+02
1.47000000e+02 1.00100000e+03 9.30000000e+01 1.54000000e+02
2.35000000e+02 1.58000000e+02 2.11000000e+02 1.16000000e+02
2.76000000e+02 5.52000000e+02 3.60000000e+02 1.13000000e+02
1.57000000e+02 1.75000000e+02 3.01000000e+02 1.31000000e+02
4.00000000e+02 3.70000000e+02 1.69000000e+02 2.01000000e+02
1.11000000e+02 1.43000000e+02 1.53000000e+02 1.24000000e+02
7.90000000e+01 2.70000000e+02 1.52000000e+02 2.96000000e+02
2.45000000e+02 1.50000000e+03 3.51000000e+02 6.00000000e+02
4.33000000e+02 1.77000000e+02]
========
nwoundus
<type 'numpy.float64'>
45
[ nan 0. 1. 2. 7. 17. 5. 3. 10. 12. 20. 27.
8. 50. 4. 36. 11. 22. 9. 75. 25. 18. 751. 14.
64. 6. 15. 48. 650. 78. 37. 109. 19. 24. 38. 33.
13. 57. 60. 31. 77. 101. 151. 16. 29.]
========
nwoundte
<type 'numpy.float64'>
43
[ nan 0. 1. 4. 2. 3. 5. 6. 50. 10. 16. 20.
9. 13. 11. 200. 7. 15. 31. 8. 12. 25. 30. 38.
14. 21. 24. 18. 62. 17. 150. 22. 23. 33. 19. 40.
51. 101. 60. 35. 53. 26. 100.]
========
property
<type 'numpy.int64'>
3
[ 0 1 -9]
========
propextent
<type 'numpy.float64'>
5
[ nan 3. 2. 4. 1.]
========
propextent_txt
<type 'str'>
5
[nan 'Minor (likely < $1 million)'
'Major (likely > $1 million but < $1 billion)' 'Unknown'
'Catastrophic (likely > $1 billion)']
========
propvalue
<type 'numpy.float64'>
641
[ nan 2.25000000e+04 6.00000000e+04 0.00000000e+00
3.05000000e+02 2.00000000e+06 1.70000000e+04 2.50000000e+03
2.20000000e+03 5.00000000e+03 8.80000000e+03 3.00000000e+03
4.18900000e+03 2.00000000e+05 1.00000000e+03 1.00000000e+06
8.00000000e+03 3.50000000e+05 4.50000000e+02 1.00000000e+05
3.00000000e+06 2.00000000e+03 5.00000000e+02 2.00000000e+02
3.20000000e+05 2.50000000e+04 4.00000000e+03 1.05000000e+05
7.00000000e+05 1.50000000e+04 5.00000000e+04 3.00000000e+04
2.50000000e+05 7.50000000e+04 2.00000000e+04 4.00000000e+04
3.33000000e+02 1.00000000e+04 9.00000000e+03 1.60000000e+03
6.00000000e+05 2.50000000e+06 2.31000000e+05 1.50000000e+05
3.00000000e+05 7.00000000e+03 1.50000000e+03 2.35000000e+04
6.00000000e+02 5.00000000e+05 2.75000000e+03 1.50000000e+06
1.60000000e+05 5.00000000e+06 6.00000000e+03 4.00000000e+02
7.00000000e+02 7.50000000e+03 5.02500000e+05 7.00000000e+04
1.10000000e+04 1.20000000e+04 2.50000000e+02 5.50000000e+03
1.75000000e+05 5.00000000e+01 1.50000000e+02 3.50000000e+03
8.50000000e+03 2.40000000e+03 9.40000000e+03 3.00000000e+02
1.00000000e+02 1.18000000e+05 1.80000000e+04 7.00000000e+06
3.70000000e+03 -9.90000000e+01 8.00000000e+04 4.40000000e+05
1.30000000e+04 1.00000000e+07 1.20000000e+05 4.50000000e+05
5.20000000e+04 2.60000000e+04 9.00000000e+06 2.20000000e+04
1.30000000e+05 5.30000000e+04 1.20000000e+03 1.35000000e+05
3.50000000e+04 9.00000000e+02 4.50000000e+03 7.40000000e+04
3.59400000e+03 3.20000000e+04 4.63610000e+04 2.80000000e+04
1.26060000e+04 1.25000000e+05 5.10000000e+04 3.20000000e+03
2.30000000e+03 1.66000000e+05 1.10000000e+03 2.80000000e+05
1.30000000e+03 3.90000000e+04 3.00000000e+07 4.20000000e+03
8.00000000e+02 7.50000000e+06 6.00000000e+06 4.00000000e+05
1.37853000e+05 1.13000000e+04 1.55600000e+06 1.38000000e+04
5.90000000e+03 3.60000000e+04 3.50000000e+02 6.20000000e+04
8.50000000e+04 2.60000000e+03 3.50000000e+06 1.25000000e+07
1.80000000e+03 7.50000000e+02 1.40000000e+04 2.55000000e+05
2.10000000e+04 5.60000000e+06 1.70000000e+02 2.10000000e+02
3.75000000e+04 2.70000000e+05 3.75000000e+03 1.20000000e+06
4.28000000e+05 9.00000000e+04 1.70000000e+03 2.40000000e+04
1.60000000e+04 3.25000000e+02 4.50000000e+04 1.10000000e+05
9.00000000e+05 8.38000000e+03 4.27000000e+04 1.40000000e+05
2.85700000e+03 7.14000000e+02 8.50000000e+02 5.28000000e+05
1.40000000e+06 3.30000000e+05 4.28570000e+04 3.33000000e+05
5.71420000e+04 5.25000000e+05 1.12500000e+04 4.30000000e+04
6.80000000e+05 4.00000000e+06 1.70000000e+05 1.25000000e+03
5.75000000e+05 1.90000000e+04 2.10000000e+03 2.92656300e+06
2.40000000e+06 1.72000000e+05 1.15000000e+05 3.70000000e+06
7.50000000e+05 5.29000000e+05 9.99000000e+02 6.50000000e+06
1.18000000e+06 8.00000000e+06 1.66058000e+05 1.90000000e+06
7.78000000e+00 7.80000000e+03 6.50000000e+05 8.50000000e+05
2.37603900e+06 5.00000000e+07 4.50000000e+07 5.85000000e+02
8.42100000e+04 2.09000000e+05 3.48000000e+05 5.90000000e+04
3.80000000e+04 1.80000000e+05 2.92000000e+05 5.33330000e+04
4.90000000e+04 8.90000000e+04 2.82550000e+04 6.25000000e+05
2.75000000e+05 6.25000000e+02 3.10000000e+01 4.70000000e+04
6.24100000e+04 4.99300000e+03 2.62120000e+04 1.88000000e+05
6.60000000e+04 1.93730000e+04 3.13101700e+06 5.71400000e+01
1.90000000e+03 6.40000000e+04 6.24100000e+03 6.89770000e+04
5.52900000e+03 4.69653000e+05 1.20000000e+07 1.90000000e+05
8.40000000e+03 8.19600000e+03 6.14940000e+04 4.88511300e+06
1.22000000e+05 3.40000000e+05 1.95000000e+05 4.80000000e+05
2.25700000e+05 5.48000000e+08 1.57000000e+06 1.07000000e+08
5.71500000e+03 1.64000000e+04 3.12000000e+05 3.70000000e+04
1.40350000e+05 1.23000000e+02 2.40000000e+05 9.50000000e+04
2.60000000e+05 8.20000000e+04 1.92000000e+05 6.84660000e+04
5.87000000e+05 6.01200000e+03 8.82000000e+05 1.61500000e+03
1.00210000e+04 1.15800000e+03 4.70000000e+05 8.30000000e+06
1.00400000e+03 1.00000000e+00 1.65000000e+05 7.78000000e+02
1.50000000e+07 1.57000000e+05 3.69100000e+02 1.95000000e+02
2.65000000e+05 4.40000000e+04 3.40000000e+04 8.73800000e+03
1.42857000e+05 3.60000000e+03 7.70000000e+01 1.21200000e+05
4.12500000e+05 1.70000000e+06 4.33450000e+04 4.84000000e+02
4.25000000e+06 5.36000000e+05 2.90000000e+01 1.28200000e+04
6.34100000e+03 1.47400000e+03 1.97500000e+05 3.00000000e+00
2.30000000e+05 3.60000000e+06 1.96000000e+04 2.60550000e+04
3.50000000e+01 2.78000000e+03 4.32000000e+05 4.84000000e+03
1.61335000e+05 9.66000000e+03 1.61000000e+05 1.62500000e+05
8.75000000e+04 8.60000000e+04 6.53750000e+04 4.00000000e+01
3.87000000e+02 5.00700000e+03 5.40000000e+06 6.40000000e+05
6.50000000e+04 1.70360000e+04 5.50000000e+04 1.30000000e+06
4.12000000e+04 8.00000000e+05 7.11750000e+05 2.20000000e+01
3.55000000e+05 1.50300000e+03 1.53000000e+05 1.92932700e+06
3.21260000e+04 2.64000000e+04 1.34110500e+06 9.47500000e+03
1.05200000e+03 5.25150000e+04 2.18650000e+04 1.68000000e+05
2.90000000e+04 4.20000000e+05 5.54500000e+04 2.82000000e+03
1.27000000e+02 4.30000000e+05 9.80000000e+04 1.35000000e+04
3.27000000e+04 9.88000000e+02 1.45000000e+04 4.80000000e+03
2.32600000e+05 8.20000000e+05 1.85000000e+05 4.50000000e+01
1.60000000e+07 1.39000000e+05 1.60000000e+06 3.80000000e+05
2.70000000e+04 3.85714000e+05 4.67741000e+05 3.62000000e+05
4.30000000e+06 2.73000000e+05 4.22500000e+03 1.27000000e+05
1.69000000e+05 7.00000000e+07 2.70000000e+06 1.00600000e+04
1.66666700e+04 1.10000000e+06 5.95000000e+05 3.10000000e+05
1.14600000e+04 1.90000000e+07 7.08880000e+04 1.49500000e+05
3.70700000e+03 4.16666667e+04 2.10600000e+06 3.70000000e+05
3.30000000e+03 5.70000000e+02 1.06000000e+06 5.16000000e+02
9.30000000e+05 1.06000000e+05 2.16000000e+05 2.14000000e+05
5.40000000e+04 2.14000000e+07 5.80000000e+04 1.87500000e+05
6.60700000e+06 2.10000000e+05 9.60000000e+04 2.00000000e+07
2.33380000e+05 9.27550000e+04 1.14390000e+04 2.70000000e+09
3.79000000e+05 5.82200000e+03 4.18000000e+05 2.20000000e+05
8.40000000e+04 7.14280000e+04 8.92800000e+03 7.20000000e+04
1.13207600e+06 5.71400000e+03 2.25000000e+06 1.66700000e+05
5.70000000e+05 1.62600000e+06 3.40000000e+06 1.02180000e+04
4.40000000e+03 8.82350000e+04 1.18900000e+04 2.87000000e+03
3.73000000e+05 3.40000000e+03 7.90600000e+03 3.01440000e+04
7.10000000e+05 1.89000000e+04 1.78000000e+05 7.10000000e+04
6.52000000e+08 1.66060000e+04 9.84500000e+03 1.42000000e+05
7.40000000e+03 1.55000000e+08 6.60000000e+03 2.37000000e+03
1.42230000e+04 1.07912000e+09 7.90000000e+04 6.75400000e+04
2.02600000e+04 2.95000000e+07 1.74750000e+04 1.86401900e+06
2.15000000e+04 2.10000000e+07 9.50000000e+03 4.65000000e+03
1.86046500e+06 1.21138800e+06 2.32558000e+05 4.02400000e+03
1.61031000e+05 6.19075000e+05 1.93098000e+05 2.40000000e+07
9.90220000e+05 1.32000000e+05 1.17700000e+06 5.13000000e+05
1.68959300e+06 1.26000000e+05 8.60000000e+01 2.87000000e+04
1.75000000e+03 1.04169600e+06 1.35000000e+02 9.59000000e+05
9.94412000e+05 3.31243400e+06 3.50000000e+08 2.04415950e+05
4.68010000e+02 2.23813790e+05 1.34228000e+05 2.37183000e+03
2.90000000e+06 2.07497000e+05 7.30000000e+07 6.66666666e+04
9.35000000e+05 6.20000000e+03 3.66000000e+05 9.25900000e+04
1.32000000e+04 6.60000000e+06 1.30000000e+07 1.26000000e+06
6.40000000e+06 2.87000000e+07 1.81077400e+06 1.30325000e+05
3.24200000e+03 5.22309260e+05 2.00566800e+04 2.08160000e+04
2.22971900e+04 1.46000000e+04 1.72061000e+03 6.50398500e+04
5.10000000e+03 7.49793800e+04 4.78797000e+05 8.46000000e+05
5.01250000e+04 6.00875130e+05 7.68400000e+04 2.26000000e+02
1.12900000e+03 1.36301000e+05 2.28650000e+04 9.24600000e+03
1.15393000e+05 3.32341000e+05 2.23278000e+05 9.32840000e+04
4.40020000e+04 3.80904000e+05 1.15154500e+04 2.07278000e+05
2.23000000e+04 1.11501000e+05 1.86393000e+05 1.04913000e+05
5.64200000e+03 6.52000000e+05 3.29272000e+04 1.81890240e+05
3.64927000e+03 1.63000000e+06 2.70000000e+03 1.22579000e+05
6.29250000e+02 2.83902000e+03 4.76000000e+05 3.68088080e+05
1.24550000e+06 9.02936000e+03 3.41507000e+06 1.32626000e+05
1.02000000e+05 2.57000000e+05 2.45000000e+03 9.04560000e+04
1.66792000e+04 1.37470000e+05 1.22576300e+06 2.25530000e+04
8.03450000e+06 6.45640000e+06 1.00000100e+06 2.23337400e+04
1.37460000e+02 3.01400000e+03 8.84173000e+03 2.21240000e+04
6.58164000e+05 1.78064000e+05 1.29352000e+03 1.62485200e+04
2.35904000e+05 2.26350000e+05 2.43000000e+05 1.34244000e+04
1.60922000e+04 4.94320000e+02 8.33200000e+05 6.86656000e+04
9.21375900e+04 2.96364000e+04 3.13972100e+06 1.23240000e+04
1.01940000e+02 3.03600000e+03 2.41429350e+05 5.72738000e+05
5.40540200e+04 3.13676500e+05 1.00000010e+07 2.25784900e+05
6.02413000e+06 2.44200000e+03 1.20286400e+04 9.30882000e+03
1.20710000e+04 1.49417800e+04 3.11596200e+04 1.12479000e+03
4.46200000e+02 1.10316700e+06 3.78530000e+04 1.34167000e+05
5.30475000e+03 6.70900000e+04 1.32594554e+06 7.65900000e+03
2.89000000e+02 4.52442800e+05 1.00000000e+08 7.96994000e+05
5.57724750e+05 4.55000000e+04 1.16500000e+05 1.39606500e+04
3.13230600e+04 6.71208500e+04 1.56031000e+03 6.55600000e+03
8.86000000e+03 4.48040000e+02 7.48917800e+04 5.61925000e+04
6.41867400e+04 1.50858000e+03 2.15185000e+05 7.48890000e+02
7.23649270e+05 1.06340500e+04 4.20000000e+04 1.08075000e+05
1.08075000e+03 2.16000000e+04 8.63166000e+03 3.71963330e+05
2.10931000e+03 1.67383500e+04 8.00000000e+01 9.90000000e+01
4.46828100e+05 6.33916000e+03 6.68851600e+04 1.43512800e+04
3.30000000e+06 1.83000000e+06 3.35190000e+05 2.46000000e+04
1.68093750e+06 6.00000000e+07 5.99785200e+05 2.02934000e+04
3.33333000e+05 1.40490900e+06 2.24391440e+05 6.70918500e+05
2.12681000e+04 2.85714284e+07 2.75500000e+03 1.88177200e+04
7.70000000e+04 5.74400000e+03 1.53481200e+04 1.53692500e+04
1.99554940e+06]
========
propcomment
<type 'float'>
18345
[nan 'Three transformers were damaged.'
'Basketball courts, weight room, swimming pool, gymnastic equipment, and lockers were destroyed.'
..., 'A truck and electric post were damaged in this attack.'
'A town was damaged in this attack.'
'A tetrapylon and part of a Roman theatre were damaged in the attack.']
========
ishostkid
<type 'numpy.float64'>
4
[ 0. 1. nan -9.]
========
nhostkid
<type 'numpy.float64'>
203
[ nan 1.00000000e+00 5.00000000e+00 1.30000000e+01
1.29000000e+02 6.00000000e+01 2.00000000e+00 5.50000000e+01
-9.90000000e+01 1.55000000e+02 1.75000000e+02 3.00000000e+00
4.40000000e+01 4.00000000e+00 6.00000000e+00 2.40000000e+01
1.87000000e+02 6.10000000e+01 1.20000000e+01 2.00000000e+01
1.10000000e+01 1.00000000e+01 4.00000000e+01 1.40000000e+02
5.00000000e+01 3.00000000e+01 1.40000000e+01 7.00000000e+00
1.60000000e+01 1.02000000e+02 1.80000000e+01 8.00000000e+00
3.50000000e+01 5.30000000e+01 2.60000000e+01 3.10000000e+01
8.70000000e+01 2.50000000e+01 2.57000000e+02 9.20000000e+01
9.00000000e+01 1.10000000e+02 6.40000000e+01 2.42000000e+02
1.46000000e+02 1.00000000e+02 4.50000000e+01 3.40000000e+01
7.00000000e+01 5.60000000e+01 1.20000000e+03 2.50000000e+02
1.30000000e+02 8.20000000e+01 1.30000000e+03 1.70000000e+01
3.60000000e+01 2.30000000e+01 4.00000000e+03 1.35000000e+02
1.86000000e+02 2.00000000e+02 5.00000000e+02 1.50000000e+01
2.10000000e+01 2.70000000e+01 9.00000000e+00 5.40000000e+01
1.13000000e+02 2.15000000e+02 1.19000000e+02 3.90000000e+01
1.17000000e+02 4.80000000e+01 2.63000000e+02 1.28000000e+02
2.70000000e+02 2.80000000e+01 6.90000000e+01 7.30000000e+01
6.20000000e+01 3.80000000e+01 1.00000000e+03 3.90000000e+02
1.89000000e+02 5.00000000e+03 1.00000000e+04 1.70000000e+04
1.50000000e+02 7.70000000e+01 1.42000000e+02 6.00000000e+02
2.64000000e+02 7.90000000e+01 1.18000000e+02 1.20000000e+02
1.31000000e+02 1.27000000e+02 8.00000000e+01 1.61000000e+02
2.20000000e+01 3.30000000e+01 9.70000000e+01 7.40000000e+01
1.53000000e+02 4.20000000e+02 4.90000000e+01 9.80000000e+01
1.70000000e+02 4.00000000e+02 5.70000000e+01 3.20000000e+01
3.70000000e+01 4.30000000e+01 1.56000000e+02 1.12000000e+02
1.90000000e+01 1.60000000e+02 2.07000000e+02 1.25000000e+02
1.04000000e+02 2.90000000e+01 1.37000000e+02 1.44000000e+02
1.05000000e+02 8.80000000e+01 1.15000000e+02 4.60000000e+01
8.30000000e+01 1.39000000e+02 3.00000000e+02 7.80000000e+01
7.20000000e+01 1.64000000e+02 4.20000000e+01 8.50000000e+01
1.07000000e+02 2.00000000e+03 3.64000000e+02 2.98000000e+02
1.94000000e+02 1.16000000e+02 1.99000000e+02 2.01000000e+02
7.50000000e+01 2.32000000e+02 1.58000000e+02 5.03000000e+02
4.70000000e+01 4.10000000e+01 1.68000000e+02 7.50000000e+02
1.51000000e+02 3.29000000e+02 1.65000000e+02 9.10000000e+01
1.74000000e+02 1.90000000e+02 5.90000000e+01 9.12000000e+02
2.67000000e+02 6.50000000e+01 1.69000000e+02 1.83000000e+02
1.03000000e+02 3.25000000e+02 3.50000000e+02 6.30000000e+01
9.50000000e+01 0.00000000e+00 1.43000000e+02 7.00000000e+02
1.20100000e+03 5.20000000e+01 8.80000000e+02 9.90000000e+01
2.76000000e+02 1.93000000e+02 1.68600000e+03 1.01000000e+02
5.10000000e+01 6.70000000e+01 6.80000000e+01 7.10000000e+01
1.85000000e+02 2.43000000e+02 8.90000000e+01 2.34000000e+02
1.21000000e+02 1.72000000e+02 2.80000000e+02 8.60000000e+01
1.82000000e+02 3.01000000e+02 2.30000000e+02 8.40000000e+01
1.26000000e+02 1.50000000e+03 9.60000000e+01 3.00000000e+03
2.84000000e+02 1.95000000e+02 8.00000000e+02]
========
nhostkidus
<type 'numpy.float64'>
28
[ nan 0. 1. 13. -99. 2. 4. 11. 50. 3. 30. 6. 9. 70. 10.
66. 5. 8. 21. 19. 35. 15. 7. 56. 86. 54. 38. 17.]
========
nhours
<type 'numpy.float64'>
36
[ nan 0.00000000e+00 2.20000000e+01 1.70000000e+01
2.00000000e+00 1.80000000e+01 -9.90000000e+01 1.50000000e+01
1.00000000e+00 5.00000000e+00 3.00000000e+01 8.00000000e+00
1.00000000e+01 2.50000000e-01 6.00000000e+00 3.00000000e+00
4.00000000e+00 1.20000000e+01 9.99000000e+02 7.20000000e+01
3.70000000e+01 1.40000000e+01 5.00000000e-01 3.60000000e+01
1.60000000e+01 2.40000000e+01 1.90000000e+01 2.60000000e+01
9.00000000e+00 2.00000000e+01 7.00000000e+00 -9.00000000e+00
2.30000000e+01 1.10000000e+01 1.30000000e+01 2.10000000e+01]
========
ndays
<type 'numpy.float64'>
314
[ nan 2.00000000e+00 4.00000000e+00 1.70000000e+01
1.00000000e+00 5.00000000e+00 0.00000000e+00 3.00000000e+00
7.00000000e+00 6.00000000e+00 2.02000000e+02 1.00000000e+01
8.00000000e+00 5.90000000e+01 2.30000000e+01 4.20000000e+01
1.41000000e+02 2.10000000e+01 1.20000000e+01 6.30000000e+01
4.00000000e+01 1.30000000e+01 1.54000000e+02 1.80000000e+02
9.50000000e+01 1.35000000e+02 4.10000000e+01 8.00000000e+01
2.60000000e+01 1.90000000e+01 2.70000000e+01 6.20000000e+01
2.90000000e+02 3.00000000e+01 8.90000000e+01 1.17000000e+02
3.50000000e+01 1.91000000e+02 6.10000000e+01 2.90000000e+01
1.50000000e+01 1.62000000e+02 6.00000000e+01 1.20000000e+02
3.65000000e+02 4.80000000e+01 1.07000000e+02 7.52000000e+02
2.80000000e+01 2.58000000e+02 1.01000000e+02 1.80000000e+01
8.50000000e+01 3.80000000e+01 2.00000000e+01 2.20000000e+01
1.09000000e+02 8.80000000e+01 2.40000000e+01 5.50000000e+01
3.70000000e+01 1.40000000e+01 9.30000000e+01 1.61000000e+02
5.00000000e+01 5.20000000e+01 2.16000000e+02 4.50000000e+01
8.70000000e+01 9.10000000e+01 1.24000000e+02 9.00000000e+00
4.30000000e+01 1.02000000e+02 1.10000000e+01 3.20000000e+01
3.30000000e+01 4.70000000e+01 9.90000000e+01 5.67000000e+02
3.80000000e+02 2.45400000e+03 -9.90000000e+01 1.14000000e+02
1.93500000e+03 9.00000000e+01 3.37000000e+02 1.75900000e+03
1.60000000e+01 6.10000000e+02 3.15000000e+02 1.72000000e+02
5.29000000e+02 2.49000000e+02 3.93000000e+02 1.73000000e+02
6.70000000e+01 5.60000000e+01 8.40000000e+01 1.92000000e+02
6.50000000e+01 1.47000000e+02 1.19000000e+02 6.40000000e+02
3.10000000e+01 4.40000000e+01 5.40000000e+01 6.90000000e+01
1.87000000e+02 4.90000000e+01 7.50000000e+01 5.10000000e+01
5.70000000e+01 8.10000000e+01 4.60000000e+01 4.92000000e+02
5.16000000e+02 1.06000000e+02 3.10000000e+02 1.00000000e+02
2.12000000e+02 1.13000000e+02 5.02000000e+02 5.31000000e+02
2.20000000e+02 1.28000000e+02 2.47000000e+02 1.40000000e+02
2.85000000e+02 2.05000000e+02 1.53000000e+02 7.80000000e+01
6.40000000e+01 2.50000000e+01 1.03000000e+02 2.64000000e+02
2.61000000e+02 3.90000000e+01 2.44000000e+02 3.30000000e+02
9.40000000e+01 1.79000000e+02 2.08000000e+02 1.22000000e+02
1.15000000e+02 2.32000000e+02 3.40000000e+01 1.50000000e+02
1.97000000e+02 6.80000000e+01 3.60000000e+02 1.12000000e+02
3.60000000e+01 4.50000000e+02 7.00000000e+01 1.38000000e+02
7.10000000e+01 2.28000000e+02 3.73000000e+02 2.69000000e+02
3.70000000e+02 1.68000000e+02 9.70000000e+01 2.70000000e+02
1.47400000e+03 3.79000000e+02 4.10000000e+02 3.11000000e+02
1.67000000e+02 8.20000000e+01 1.94000000e+02 1.94100000e+03
5.24000000e+02 5.30000000e+01 9.40000000e+02 2.52000000e+02
1.26000000e+02 1.04000000e+02 4.59000000e+02 1.31000000e+02
2.23000000e+02 2.19000000e+02 2.38000000e+02 1.70000000e+02
1.10000000e+02 6.23000000e+02 1.79600000e+03 1.28200000e+03
7.70000000e+01 1.08000000e+02 5.80000000e+01 1.55000000e+02
1.34000000e+03 1.45100000e+03 1.12900000e+03 1.87900000e+03
1.74000000e+02 6.13000000e+02 4.40000000e+02 2.99000000e+02
1.90000000e+02 3.01000000e+02 1.25000000e+03 1.27000000e+02
9.19000000e+02 6.43000000e+02 8.74000000e+02 1.11100000e+03
1.09100000e+03 9.76000000e+02 4.63000000e+02 8.60000000e+01
2.66000000e+02 3.50000000e+02 1.06900000e+03 2.18000000e+02
8.77000000e+02 4.14000000e+02 5.14000000e+02 5.40000000e+02
1.52000000e+02 6.94000000e+02 1.59000000e+02 3.95000000e+02
1.51000000e+02 1.27100000e+03 6.74000000e+02 1.25000000e+02
2.63000000e+02 3.33000000e+02 2.10000000e+02 2.21000000e+02
7.40000000e+01 2.42000000e+02 5.50000000e+02 7.45000000e+02
5.56000000e+02 1.09700000e+03 3.98000000e+02 1.18000000e+02
3.39000000e+02 7.61000000e+02 5.58000000e+02 7.90000000e+01
1.88000000e+02 1.29000000e+02 2.43000000e+02 5.92000000e+02
3.94000000e+02 5.55000000e+02 9.52000000e+02 4.44000000e+02
1.11000000e+02 1.11000000e+03 4.11000000e+02 2.31000000e+02
3.47000000e+02 5.08000000e+02 9.60000000e+01 2.81000000e+02
1.32000000e+02 7.30000000e+01 2.04000000e+02 1.64000000e+02
7.20000000e+01 2.67000000e+02 2.36000000e+02 7.60000000e+01
1.75000000e+02 4.60000000e+02 1.36000000e+02 7.13000000e+02
7.38000000e+02 2.65000000e+02 9.93000000e+02 7.07000000e+02
1.05000000e+02 1.60000000e+02 1.30000000e+02 2.37000000e+02
1.89000000e+02 9.80000000e+01 6.89000000e+02 1.63000000e+02
2.33000000e+02 6.60000000e+01 7.05000000e+02 1.76000000e+02
1.93000000e+02 4.19000000e+02 2.82000000e+02 2.98000000e+02
2.60000000e+02 3.63000000e+02 4.86000000e+02 1.84000000e+02
3.13000000e+02 1.48000000e+02 2.25000000e+02 2.13000000e+02
2.29000000e+02 3.45000000e+02 4.13000000e+02 1.58000000e+02
1.39000000e+02 5.32000000e+02 3.62000000e+02 9.20000000e+01
3.07000000e+02 3.06000000e+02 2.41000000e+02 1.83000000e+02
2.51000000e+02 2.06000000e+02]
========
divert
<type 'float'>
144
[nan 'Beirut' 'Cambodia' 'South Korea' 'Jordan' 'Egypt' 'England'
'Arrested before boarding' 'Iraq' 'Libya' 'China' 'Yemen' 'Bulgaria'
'Lod Airport in Israel' 'Spain' 'Cuba' 'United Arab Emirates' 'Kuwait'
'Netherlands' 'Tunisia' 'Iran' 'Zamboanga Philippines' 'Uganda' 'Paris'
'Qatar' 'Peru' 'Italy' 'Algeria' 'Somalia' 'Singapore' 'Cyprus'
'Stockholm' 'San Jose, Costa Rica' 'Ireland' 'Cologne' 'Malta' 'Teheran'
'Cuba, Havana' 'unknown' 'Diyarbakir, Turkley for refueling'
'Brussels (to a broadcasting centre)' 'Cuba (Havana)'
'Higuerote, 110km NE of Caracus' 'Havana, Cuba' 'Cucuta'
'no (police foiled operation)' 'Kabul, Afghanistan- Damascus, Syria'
'Managua Nicaragua to Panama' 'Bangkok, Thailand' 'France'
'Tangiers, Morocco' 'Tel Aviv' 'Lakore, Pakistan'
'Guajira Peninsula in N. Colombia' 'Colombia'
'Costa Rica, Juan Santamaria Airport' 'Costa Rica, San Jose' 'Durban, SA'
'Lebanon' 'Guatemala city, Panama, Havana' 'Bogota, Cali'
'Nairobi, Kenya, Jidda, Saudi Arabia, Athens, *' 'Tegucigalpa'
'Amristar, India' 'Djibouti, Africa' 'Mexico'
'Greece, Athens-Ellinikon Airport' 'Larnaca, Cyprus' 'Paris, France'
'Beneva, Sicily, Damascus, Teheran' 'West Bank and Gaza Strip'
'Pakistan, Lahore' 'Trinidad-This; Aruba-12 hrs; Curacas'
'Pakistan (Lahore, Karachi) Dubai' 'Baghdad' 'Teheran, Iran'
'Addis Ababa, Ethiopia (Bole international airport)' 'Tehran airport'
'Vienna, Austria' 'Amalfi' 'Kasese' 'Prague to Karolovy Vary Flight'
'En route Nickerie to Paramaribo' 'Fukuoka, Japan' 'Bandar Abbas'
'Finland' 'Calcutta, India' 'Lima' 'Medellin' 'Singapore s Changi Airport'
'United States' 'strip near Neiva' 'Djibouti' 'Saudi Arabia' 'Russia'
'Madrid' 'Nairobi, Kenya' 'Moscow' 'Ho Chi Minh City' 'Afghanistan'
'Rome, Italy' 'Taiwan' 'Alicante, Spain' 'Luxor, Egypt' 'Sanaa, Yemen'
'Salonika' 'Estonia' 'not stated' 'Marseilles' 'Port Sudan' 'Sudan'
'Johannesburg, South Africa' 'Geneva' 'Greece' 'Unknown'
'Miami, Florida, USA' 'Great Britain' 'Varna, Bulgaria' 'Germany' 'India'
'Tanzania' 'Angola' 'Uzbekistan' 'Bangladesh' 'Philippines' 'Sierra Leone'
'Ethiopia' 'Burundi' 'Congo' 'Gambia' 'Mali' 'Bolivia' 'Georgia' 'Nigeria'
'Nepal' 'Turkey' 'Israel' 'Palestine' 'Pakistan' 'Chad' 'Niger' 'Syria'
'Central African Republic' 'South Sudan']
========
kidhijcountry
<type 'float'>
218
[nan 'Mexico' 'Beirut' 'Venezuela' 'Spain' 'Guatemala' 'Brazil' 'Ethiopia'
'Cambodia' 'Dominican Republic' 'Argentina' 'South Korea' 'Jordan'
'Colombia' 'Bolivia' 'Greece' 'Nicaragua' 'Uruguay' 'Egypt' 'England'
'Great Britain' 'Arrested before boarding' 'Canada' 'Iraq' 'Iran' 'Zambia'
'Libya' 'Turkey' 'Costa Rica' 'China' 'Northern Ireland' 'Yemen'
'Bulgaria' 'Lod Airport in Israel' 'United States' 'France' 'Cuba'
'West Germany (FRG)' 'Haiti' 'Myanmar' 'Austria' 'United Arab Emirates'
'Kuwait' 'Italy' 'Netherlands' 'Chad' 'Thailand' 'Lebanon' 'Japan'
'East Germany (GDR)' 'Tunisia' 'Somalia' 'Tanzania' 'Ireland'
'Philippines' 'Morocco' 'Portugal' 'Zamboanga Philippines' 'Uganda'
'El Salvador' 'Paris' 'Republic of the Congo' 'Mauritania'
'Democratic Republic of the Congo' 'Qatar' 'Peru' 'Algeria' 'Ecuador'
'Djibouti' 'Singapore' 'Cyprus' 'Rhodesia' 'Belgium' 'Western Sahara'
'Indonesia' 'Jamaica' 'Afghanistan' 'Stockholm' 'Namibia'
'San Jose, Costa Rica' 'Israel' 'Cologne' 'Malta' 'Puerto Rico' 'Corsica'
'Teheran' 'Cuba, Havana' 'Honduras' 'unknown'
'Diyarbakir, Turkley for refueling' 'Brussels (to a broadcasting centre)'
'Cuba (Havana)' 'Higuerote, 110km NE of Caracus' 'Havana, Cuba' 'Syria'
'Cucuta' 'no (police foiled operation)'
'Kabul, Afghanistan- Damascus, Syria' 'Managua Nicaragua to Panama'
'Bangkok, Thailand' 'Guyana' 'Tangiers, Morocco' 'Tel Aviv'
'Lakore, Pakistan' 'Guajira Peninsula in N. Colombia'
'Costa Rica, Juan Santamaria Airport' 'Costa Rica, San Jose' 'Durban, SA'
'Guatemala city, Panama, Havana' 'Mozambique' 'Bogota, Cali'
'Nairobi, Kenya, Jidda, Saudi Arabia,' 'Tegucigalpa' 'Zimbabwe'
'Amristar, India' 'Angola' 'Djibouti, Africa'
'Greece, Athens-Ellinikon Airport' 'Sudan' 'Larnaca, Cyprus'
'Paris, France' 'Beneva, Sicily, Damascus, Teheran' 'India'
'West Bank and Gaza Strip' 'Sri Lanka' 'Chile' 'Pakistan, Lahore'
'Trinidad-This; Aruba-12 hrs; Curacas' 'Pakistan (Lahore, Karachi) Dubai'
'Baghdad' 'Teheran, Iran' 'Addis Ababa, Ethiopia (Bole internati'
'Tehran airport' 'Vienna, Austria' 'Saudi Arabia' 'Amalfi' 'Kasese'
'Swaziland' 'Suriname' 'Pakistan' 'Switzerland' 'New Caledonia'
'Bangladesh' 'Lesotho' 'South Africa' 'Laos' 'Czechoslovakia'
'Prague to Karolovy Vary Flight' 'En route Nickerie to Paramaribo'
'Fukuoka, Japan' 'Bandar Abbas' 'Papua New Guinea' 'Liberia' 'Panama'
'Soviet Union' 'Finland' 'Calcutta, India' 'Lima' 'Medellin'
'Singapore s Changi Airport' 'Sierra Leone' 'Belize' 'Yugoslavia'
'Georgia' 'strip near Neiva' 'Azerbaijan' 'Togo' 'Kazakhstan' 'Niger'
'Russia' 'Madrid' 'Nairobi, Kenya' 'Moldova' 'Nigeria' 'Moscow' 'Senegal'
'Madagascar' 'Ho Chi Minh City' 'Tajikistan' 'Bosnia-Herzegovina'
'Rome, Italy' 'Germany' 'Taiwan' 'Alicante, Spain' 'Ivory Coast'
'Luxor, Egypt' 'Sanaa, Yemen' 'New Zealand' 'Hong Kong' 'Norway'
'Salonika' 'Estonia' 'not stated' 'Marseilles' 'Port Sudan' 'Cameroon'
'Eritrea' 'Denmark' 'Johannesburg, South Africa' 'Geneva' 'Benin'
'Guadeloupe' 'Miami, Florida, USA' 'Ukraine' 'Varna, Bulgaria' 'Vanuatu'
'Paraguay' 'Albania' 'Unknown' 'United Kingdom' 'International' 'Burundi'
'Congo' 'Russian Federation' 'Palestine' 'Nepal' 'Mali'
'Central African Republic']
========
ransom
<type 'numpy.float64'>
4
[ 0. 1. nan -9.]
========
ransomamt
<type 'numpy.float64'>
396
[ nan 8.00000000e+05 1.10000000e+05 0.00000000e+00
7.00000000e+05 1.20000000e+04 1.50000000e+04 2.50000000e+05
1.00000000e+05 4.00000000e+05 8.00000000e+04 5.00000000e+06
1.00000000e+06 2.20000000e+05 5.00000000e+05 4.00000000e+04
1.05000000e+05 3.20000000e+05 2.50000000e+04 1.00000000e+07
2.00000000e+04 1.50000000e+06 2.00000000e+05 1.68000000e+05
1.14500000e+06 1.42000000e+07 3.00000000e+06 6.21000000e+05
6.10000000e+07 1.33000000e+04 2.70000000e+04 2.00000000e+07
3.40000000e+06 3.00000000e+05 3.75000000e+05 4.08000000e+05
2.80000000e+04 1.40000000e+05 1.30000000e+06 5.07000000e+06
1.40000000e+07 4.37000000e+05 2.10000000e+06 1.94000000e+05
5.00000000e+04 1.35000000e+06 4.77950000e+05 6.00000000e+06
3.50000000e+05 1.50000000e+07 6.00000000e+05 2.20000000e+06
1.07000000e+07 5.30000000e+04 7.40000000e+05 6.00000000e+04
1.30000000e+05 3.10000000e+05 4.00000000e+06 1.40000000e+06
1.50000000e+05 2.60000000e+05 8.20000000e+07 1.30000000e+07
1.00000000e+09 7.50000000e+04 2.10000000e+04 2.00000000e+06
8.70000000e+04 4.40000000e+04 1.25000000e+05 8.00000000e+06
2.30000000e+06 3.60000000e+04 5.90000000e+05 1.42000000e+05
4.50000000e+05 1.10000000e+06 1.00000000e+04 7.50000000e+05
1.54000000e+05 2.40000000e+05 4.15000000e+05 1.20000000e+06
5.00000000e+07 1.25000000e+04 4.35000000e+05 4.30000000e+06
9.26000000e+05 9.00000000e+05 3.00000000e+07 8.34000000e+05
2.50000000e+06 1.20000000e+05 9.99000000e+02 5.00000000e+03
7.50000000e+06 2.50000000e+07 3.90000000e+05 2.40000000e+06
8.40000000e+06 2.40000000e+04 1.70000000e+07 4.60000000e+04
3.30000000e+06 2.80000000e+06 5.10700000e+06 2.18000000e+05
3.57000000e+04 1.79000000e+05 3.55000000e+05 1.00000000e+00
7.10000000e+04 1.15000000e+05 3.42000000e+05 6.20000000e+04
1.72000000e+03 1.00000000e+08 1.80000000e+06 2.12000000e+05
7.00000000e+06 5.80000000e+06 3.70000000e+05 4.61500000e+05
1.80600000e+05 1.28000000e+06 3.00000000e+04 4.16660000e+04
3.20000000e+04 2.07641000e+05 6.30000000e+05 1.93000000e+04
1.94332000e+05 2.60000000e+07 3.10000000e+03 3.90000000e+03
7.80000000e+04 1.90000000e+06 1.70000000e+04 5.72210000e+04
4.00000000e+03 5.80000000e+05 1.20000000e+07 5.55000000e+05
3.85000000e+04 3.84000000e+05 1.91000000e+05 2.00000000e+03
6.82000000e+05 2.62000000e+06 5.70600000e+03 3.85000000e+05
1.92000000e+05 3.55000000e+04 5.65000000e+04 1.15384000e+05
4.71920000e+04 5.66300000e+04 1.90440000e+05 2.65836000e+05
5.79000000e+05 1.23000000e+06 5.80000000e+07 1.86000000e+03
9.00000000e+03 1.02500000e+07 8.24640000e+04 9.43430000e+04
2.42317000e+05 8.07750000e+04 1.43000000e+05 2.61136000e+05
4.50000000e+03 1.10000000e+07 8.10000000e+03 -9.90000000e+01
1.03300000e+05 1.98000000e+06 1.50000000e+03 2.00000000e+08
1.20000000e+03 4.76190000e+05 1.17000000e+05 2.30600000e+05
2.25174000e+05 1.60000000e+06 -9.00000000e+00 3.40000000e+04
1.27621000e+05 6.15260000e+04 1.03300000e+03 2.12800000e+05
1.88400000e+06 1.78000000e+05 2.04883000e+05 1.01250000e+05
6.60000000e+04 1.06400000e+05 1.17900000e+05 5.24000000e+05
7.30000000e+04 1.27388500e+06 7.46268600e+06 2.43540000e+06
2.50207700e+04 6.25519200e+04 7.98400000e+04 2.65440000e+04
2.59000000e+05 1.97156700e+04 6.64000000e+05 2.72720000e+04
4.75000000e+07 4.43066100e+04 6.37000000e+03 2.00000000e+01
6.64000000e+04 2.51109200e+04 4.25980000e+04 1.19365000e+03
3.44392200e+05 2.10000000e+07 2.35000000e+05 9.76117500e+05
5.93870000e+04 1.60000000e+04 1.67100000e+03 2.32550000e+04
1.10076000e+05 5.76968250e+05 2.23000000e+04 3.03498000e+05
1.04913000e+05 1.66623600e+05 4.00000000e+07 7.95550000e+04
2.02737200e+06 2.18956160e+05 1.92975000e+07 1.84230000e+05
1.50000000e+08 3.03774600e+05 1.32000000e+08 2.48600000e+05
1.67630000e+05 5.09550000e+06 1.01910000e+04 1.55980000e+04
3.77000000e+05 9.47688000e+06 3.30000000e+07 3.48150000e+05
1.38040000e+06 1.06636800e+05 1.11570000e+06 7.60000000e+05
3.35645500e+04 1.92139000e+05 3.01279000e+05 6.60000000e+06
5.09400000e+05 3.35260000e+06 8.36100000e+04 3.02902000e+06
3.34335000e+05 8.34725000e+05 3.33890000e+04 1.66182000e+05
1.66945000e+05 1.62285000e+05 3.07787500e+04 1.11185400e+04
3.31071000e+04 1.22820000e+04 3.04329300e+05 6.14628000e+04
1.66530700e+04 6.87286200e+04 1.15620450e+07 3.08737500e+05
1.45917900e+05 5.06073000e+05 5.58347500e+06 4.35790000e+04
8.10386080e+06 6.28516500e+05 1.23000000e+04 2.02373000e+06
5.05830000e+05 1.96083200e+05 4.51569800e+05 6.13686000e+04
2.81175450e+06 8.17675160e+05 9.84026000e+05 4.89680000e+04
6.15926600e+04 4.10010000e+04 3.28000000e+04 7.32874410e+05
2.09000000e+03 3.05110630e+06 1.60000000e+05 1.40536000e+03
5.50000000e+06 1.09298570e+05 8.70000000e+02 3.26370800e+04
1.62900000e+03 3.24201800e+05 1.62100900e+05 3.23926000e+05
3.33556200e+05 6.74876400e+04 9.30710000e+04 4.72920000e+04
1.02014800e+05 1.60667200e+04 4.82160000e+03 1.47096200e+04
1.42000000e+04 7.88377000e+04 7.88265000e+03 3.36836550e+05
1.56684700e+04 2.21388400e+05 2.51334900e+04 2.24719000e+05
1.33005000e+06 2.21806600e+04 3.28396500e+07 4.38000000e+04
2.43960300e+04 6.86296366e+06 1.92077000e+04 1.41284000e+05
2.25950000e+02 7.55745000e+03 5.06657200e+04 2.80000000e+07
3.27600000e+03 1.74200000e+04 8.02426800e+07 3.17713000e+05
6.43267100e+04 1.63000000e+04 5.60000000e+06 3.67840000e+05
6.36360000e+04 2.44600000e+04 1.51400000e+04 5.67774698e+06
1.14000000e+04 2.99325400e+04 7.46882000e+03 3.19050000e+04
3.28000000e+03 2.95000000e+02 1.90794200e+05 1.06043550e+06
7.46168250e+06 1.08254010e+05 3.82897000e+03 1.58604500e+04
4.11862730e+05 1.04182190e+05 2.96263200e+04 1.63000000e+03
7.40901000e+03 2.42116190e+06 6.35426000e+03 6.02775300e+05
2.03321900e+04 1.11639000e+07 3.73995000e+03 1.48130400e+05
2.50000000e+03 9.92880000e+04 2.22401700e+04 8.90000000e+02
6.00000000e+03 4.01372800e+04 4.80000000e+04 4.27704000e+06
2.28571430e+05 5.02460000e+02 8.19675000e+03 1.00573000e+03
3.63000000e+05 1.02745400e+04 5.23835200e+04 1.13780000e+05
6.05000000e+05 4.88520000e+04 2.20690080e+05 9.77997000e+04]
========
ransomamtus
<type 'numpy.float64'>
23
[ nan 2.00000000e+04 0.00000000e+00 -9.90000000e+01
4.00000000e+05 6.00000000e+04 1.00000000e+05 2.00000000e+05
3.00000000e+06 5.00000000e+06 6.00000000e+06 2.00000000e+06
3.00000000e+05 1.88400000e+06 1.50000000e+07 2.00000000e+07
8.00000000e+06 1.19365000e+03 1.50000000e+04 1.50000000e+06
1.32000000e+08 6.60000000e+06 1.00000000e+04]
========
ransompaid
<type 'numpy.float64'>
137
[ nan 1.10000000e+05 1.20000000e+04 1.50000000e+04
1.00000000e+05 4.00000000e+05 8.00000000e+04 0.00000000e+00
2.20000000e+05 4.00000000e+04 2.50000000e+04 1.00000000e+07
2.00000000e+04 1.00000000e+06 7.00000000e+05 5.00000000e+06
1.50000000e+06 1.15000000e+06 1.42000000e+07 5.00000000e+05
6.21000000e+05 4.10000000e+07 1.33000000e+04 2.70000000e+04
2.00000000e+06 4.08000000e+05 1.40000000e+05 1.30000000e+06
8.57140000e+04 5.07000000e+06 2.10000000e+06 5.10000000e+05
2.20000000e+06 1.07000000e+07 5.30000000e+04 5.71420000e+04
1.25000000e+05 7.50000000e+04 5.00000000e+04 4.50000000e+04
8.00000000e+05 2.30000000e+06 3.60000000e+04 3.85000000e+04
1.40000000e+06 6.60000000e+04 9.99000000e+02 1.20000000e+05
2.40000000e+04 2.00000000e+00 2.50000000e+06 3.57000000e+04
6.00000000e+06 7.50000000e+06 6.20000000e+04 3.00000000e+07
8.00000000e+06 2.40000000e+05 7.40000000e+03 2.63250000e+04
1.95000000e+05 3.85000000e+05 1.95000000e+07 2.00000000e+05
1.91000000e+05 2.62000000e+06 1.30000000e+03 9.00000000e+04
4.12320000e+05 9.43430000e+04 2.42317000e+05 -9.90000000e+01
4.80000000e+04 2.60000000e+04 2.30600000e+05 -9.00000000e+00
3.69000000e+06 1.70000000e+06 1.00000000e+04 1.72500000e+03
1.01250000e+05 7.86000000e+04 6.00000000e+04 3.39703000e+05
4.88000000e+03 2.43540000e+06 7.96800000e+04 4.50000000e+03
1.90000000e+07 6.37000000e+03 1.20000000e+07 1.19365000e+03
1.01237700e+04 1.15393650e+05 2.30494000e+03 7.95550000e+04
7.89000000e+04 2.36975000e+05 1.87020000e+04 3.00000000e+06
4.07640000e+03 8.11715000e+06 9.42500000e+04 1.92139000e+05
5.09400000e+05 3.00000000e+05 6.45160500e+04 3.90672800e+05
1.11185400e+04 2.37262200e+05 8.27678000e+03 6.03066000e+03
4.01000000e+04 1.12892400e+04 2.91652400e+05 4.19430000e+04
1.22685000e+06 4.47728000e+03 1.40536000e+03 2.21806600e+04
6.38000000e+05 4.50800000e+03 1.00303350e+06 2.51229800e+04
2.96600000e+03 2.00000000e+02 8.20000000e+02 3.81697600e+04
1.06043550e+06 6.02775300e+05 3.73995000e+03 9.92880000e+04
1.18614000e+03 2.28571430e+05 5.02460000e+02 1.00573000e+03
6.51360000e+02]
========
ransompaidus
<type 'numpy.float64'>
9
[ nan 0.00000000e+00 2.63250000e+04 4.00000000e+04
6.50000000e+02 -9.90000000e+01 4.80000000e+04 -9.00000000e+00
1.00000000e+04]
========
ransomnote
<type 'float'>
346
[nan
'A note, with a sticker of the Black Liberation Army, demanded $20,000 for the safe return of the bartender. However, the perpetrators left the bartender alone and he was able to escape.'
'Perpetrators demanded support by the Dutch in the UN for independence for the Moluccan Islands.'
'The gunmen demanded the release of 21 South Moluccans jailed in the Netherlands on terrorism charges. They also demanded a plane to transport themselves and the jailed individuals to an unspecified location.'
'Demand access to the airport.'
'Assailants demanded the release of prisoners'
'The perpetrators demanded that Russians forces stop shelling the town of Pervomayskaya.'
'Reports on whether or not ransom was paid were conflicting.'
'Two ransoms were demanded in this incident, for a total of $2,500,000 ($500,000 for hostage number one, Edward Leonard, and $2 million for hostage number 2, Norbert Reinhart).'
'The note, left in an envelope, said the plane would be blown up unless a ransom of 621,000 rubles ($100,000) was placed in the toilet and the aircraft belonging to East-Line Airlines allowed to fly out of Russia. The note said there were several remote-control bombs on the plane, while the hijacker was armed with a grenade.'
'5 Million Philippine Pesos [converted to 2009 USD]'
'The ransom was only demanded for one of the Spanish hostages.'
'This kidnapping was a financing operation for ELN and FARC. No specific information was given on the ransom.'
'This kidnapping was a financing operation for FARC. No specific information was given on the ransom.'
'The ransom note was sent to the family for 5 million Philippine Pesos. [converted to 2009 USD]'
'The perpetrators demanded the release of Islamic extremists held in Uzbek prisons.'
"While Downey's body was found 15 hours after his abduction, it is unclear when he died and hence how long the kidnapping incident lasted."
'It was not known whether a ransom was demanded.'
'The ransom was never paid.'
'Reports did not specify the amount of ransom requested.' 'No'
'One hostage was killed on day 1. Ransom demand included $200 million (U.S.), the body of a dead comrade, and the release of a Muslim cleric and 35 other militants held in Indian jails. They settled for the release of three prominent militants: Maulana Masood Azhar, Mohammad Omar Syed, and Mushtaq Ahmad Zarzar. One of the released was a cleric who leads a group seeking independence for Indian-held Kashmir.'
'None' 'Unknown'
'The victim was told that she was on a death list, as was four other journalists.'
'The ransom note, demanding 10 million rupees, was sent by way of release of other hostages'
'In addition to money, the abductors also made a variety of political demands, including the release of prisoners'
"Drummond Company stated during the kidnapping that they would not pay any ransom. However, there was no mention of ransom paid in reports of the hostages' releases."
'Azad made a list of seven demands: 1) eradicate corruption from society, 2) salary and wage rises for the Police Force, 3) execution for Policemen found taking bribes, 4) closing all tobacco industries and advertisements in Bangladesh, 5) a fine of Taka 1'
"The kidnapper's demands included the implementation of two drinking water projects and the reinstatement of tribe members to the civil and military jobs, from which they had been dismissed."
'The abductors demanded the release of prisoners'
'The group also demanded a halt to logging by the firm and the removal of police forces from the region.'
'The captors asked for employment in return for the the release of the captive.'
'The captors asked for schools and development projects in return for the the release of the captive.'
'The hostages were only held a few hours before they were killed.' '0'
'-9'
'The assailants demanded the removal of government troops from Congo in exchange for the release of the hostages.'
'Gracia Burham later stated that although ransom was paid for her and her husband, the ASG refused to release them.'
'Philippino President Gloria Arroyo refused to pay any ransom from the very beginning of the conflict, although it is possible that ransom was paid for some of the hostages by their relatives: $100000 - 200000 per person. Many of those taken hostage in the initial attack escaped or were freed during government offensives during the following year.'
'Philippino President Gloria Arroyo refused to pay any ransom for hostages taken in the attck, although it is possible that ransom was paid for some of the hostages by their relatives: $100000 - 200000 per person.'
'Ransom: 30 million dinar.'
'One of the people who had to collect the money demanded by the kidnappers warned the military, which immediately proceeded to carry out the rescue operation, according to the military report.'
'160,000 Cdn [converted to 2009 USD]'
'Chechen law-enforcement carried out search operations.'
'A letter was mailed to the provincial governor with the ransom demand.'
'The assailants demanded the release of ten of their people'
'P50,000 [converted to 2009 USD]'
'Whether any ransom had been asked or paid was not reported.'
'It was reported that the perpetrators demanded one million dollars for each hostage.'
'The assailants demanded that a rival paramilitary leader be killed'
'The kidnappers demanded that six Taliban members be freed from prison.'
"The kidnapper called Francis Ngajokpa stating that he would release the minister's daughter for an undisclosed ransom amount."
'N260,000,000'
'The group released one hostage a head of the rest to relay the demand.'
'The kidnappers were demanding the release of two Taliban fighters in exchange for the hostages.'
'Ransom was not in a nominal amount. It was for the immediate removal of Italian forces in Southern Iraq, specifically around Nasiriyah.'
'Ansar E-Din wanted the release of Muslim prisoners in Iraq who were detained by US led coalition.'
'The ransom was not paid by Indonesia or Malaysia.'
'The "ransom" demanded on video was the departure of the Turkish truck driver\'s company from Iraq.'
'In addition to the ransom, the kidnappers demanded the release of at least four prisoners from Abu Ghraib prison in Iraq.'
'The group demanded the resignation of President Alejandro Toledo.'
'Demanded release of one thousand Palestinian prisoners in exchange for her release.'
"The perpetrators placed a call to the local Catholic diocese from Monsignor Casmoussa's mobile phone."
"The perpetrators wanted the Berjani Group to cease all business in Iraq in exchange for Gebrayel Adib Azar's safety."
'On the website, the groups each demanded that Italy withdraw their troops.'
'Demand was not a specific quantity but was services such as water, good roads, schools, etc., that the oil company had failed to deliver.'
'Reports did not state that Al Hamrah had paid the ransom amount. The actual ransom demand was for 60,000 Kuwaiti Dinars. The U.S. dollar amount appearing under "Total Ransom Amount Demanded" is the exchange rate for the 60,000 Kuwaiti Dinars as of March 2009.'
"Reports indicated that Zaein's captors had demanded a ransom, but did not indicate how much they wanted in exchange for his life."
'Reports indicated that Jawid was released after having paid his abductors ransom. However, reports did not disclose the amount asked for and paid.'
'Ransom Amount: 750 million centimes'
'The perpetrators were caught by Colombia\'s Gaula Police Unified Action Groups to Rescue Kidnap Victims. The actual ransom demand was for 70 million Columbian Pesos (COP). The U.S. dollar amount appearing under "Total Ransom Amount Demanded" is the exchange rate for the 70 million COP as of March 2009.'
'The Yemeni tribesman/kidnappers demanded the release of their relatives held on suspicion of traveling to Iraq to fight the U.S.-led coalition.'
'Al-Qa ida demanded that Sudan withdraw its Embassy in Iraq. They complied and the hostages were set free.'
'Video footage was taken of the victims.'
'The perpetrators demanded the release of all female Iraqi prisoners in US custody.'
'Ransom Amount: 500 million centime'
'Perpetrators were seeking the release of Taliban fighters rather than monetary gain.'
'Ransom Amount: 800 million centimes'
'The perpetrators called for the closure of the UAE embassy in Baghdad and of the television station Al-Fayhah, but no money. The victims family offered to pay a ransom.'
'The perpetrators were seeking the release of two suspected militants who were arrested earlier in the day in connection with a shooting at two Thai marines. Eleven teachers were taken hostage and all were released that same day, but two sustained critical injuries.'
'The perpetrators released Shalit in exchange for the release of over 1,000 prisoners from Israeli jails.'
'Ransom Amount: 900 million centime'
"The assailants called the victim's father and told him that if the ransom was not paid in five days, his son would be killed. Ransom demanded: 4 billion centimes."
'The Taliban demanded the release of Taliban prisoners from Afhan custody.'
'Demanded release of Muslim prisoners in British custody'
'Ransom was in the form of Italian withdrawal of military forces from Afghanistan rather than monetary.'
'NPR 5,000,000 converted to USD'
'Kidnappers demanded the release of 15 of their extremist comrades in return for the 4 kidnapped policemen.'
'Kidnappers demanded that British forces withdraw from Iraq'
'Ranson demand sent in a text message to a senior Indorama manager on June 7.'
'Militants wanted to swap the soldiers for detained militants.'
"This incident was reportedly 'all about the money.' One source states that the perpetrators demanded $1,000,000 dollars, but in fact received nothing for Gouil's release."
'The militants demanded that some of their own be freed.'
'Families refused to pay ransom'
'The release of certain prisoners in Algeria and Tunisia, realease of two militants in Vienna and 5 million euros.'
'Wanted to be driven to nearest airport.'
'N12 Million ($79,680 USD) was paid for the release of the children.'
'A ransom ranging from $27,272 to $681,818 US dollars was demanded by the kidnappers. A "Board and Lodging" fee of $2,250 U.S. dollars was paid by the negotiator twice for the release of the cameraman and again for the release of the remaining hostages.'
'"board and lodging fee"'
'Sources indicate that a ransom was paid but do not specify the amount.'
"The assailants sent a letter to Abdol Ahad's house, saying that unless $100,000 was paid to them in three days, they would kill Abdol Ahad."
'It is unknown if a ransom was paid.'
'Bowe Bergdahl was released in exchange for the freedom of five Taliban members being held in Guantanamo prison.'
'A cash ransom as well as the release of a militant commander is sought.'
'Family failed to pay the USD235,000 ransom.'
'There was a ransom demand of an unspecified amount.'
'The perpetrators demanded the release of a member of their group who was in custody.'
"The kidnappers initially demanded 2.7 million (59,387 USD) for the candidate's release which they later reduced to one million (21,995 USD)."
'The Taliban demanded 800,000 Afghanis for the release of the observers.'
'The militants demanded P1 million (23,255 USD) in ransom for the release of Cecilia Sosas.'
'The kidnapper demanded 200,00 dollars for one of the engineers.'
"The EPP demanded from Pereira's family one million USD for his release or as an alternative demanded that the Paraguayan government release Miguel Lopez Perito, leader of Gabinete and the 10 de Abril Movement in exchange for Pereira"
'The hostage was released unharmed in exchange for the release of at least five imprisoned Communist Party of India-Maoist (CPI-M) cadres.'
'The assailants initially demanded a ransom of $110,076 USD but then reduced the amount to $33,023 USD.'
'Authorities claim the kidnappers demanded compensation from the government for the 45 families who were killed by a suspected U.S. airstrike against a supposed Al Qaeda training camp in Al-Majala district of Abyan in late 2009 among other unstated non-monetary demands.'
'The assailants later lowered their ransom demand to $461,574.60'
"In a video released by the captors, McManus asks the British government to meet the demands of al Qa'ida. Sources do not indicate what the demands were."
'The assailants demanded that the hostages refrain from leaking information to the police.'
"The Tehrik-e-Taliban Pakistan's (TTP) commander has claimed they will free the hostages if the United States releases Aafia Siddiqu, a Pakistani woman convicted of trying to kill Americans."
'NLFT-BM set a ransom notice of one million Indian rupees for the release of eight tribal villagers on 07/20/2011.'
"In December 2011, Zawahiri stated that Weinstein would be released in exchange for the release of all al Qa'ida and Taliban prisoners, as well as the 1993 World Trade Center attackers and members of Osama bin Laden's family, the closing down of U.S. military prisons, including at Guantanamo Bay, Cuba, ending all bombing in Pakistan, Afghanistan, Yemen, Somalia, and Gaza, and allowing movement of people and trade between Egypt and Gaza."
'MUJAO demanded 30 million euros and the release of two Sahrawis arrested for their role in the kidnapping. They stated that their demands had been met, but the amount of ransom paid was unspecified.'
'The militants demanded a sizeable ransom, the amount was not released.'
'The perpetrator did not make a ransom demand in this case. However, he did request that the incident be shown on television.'
'The assailants did not demand any money for the release of the victim. Instead, they demanded that government forces be removed from Garo Hills.'
'The demands for release were not reported' 'No ransom demand reported'
'No information regarding ransom given.'
'No information regarding ransom demand'
'No ransom was demanded. The hostages were let go almost immediately.'
'No mention of ransom demanded.'
'No information given beyond the statement that five soldiers had been taken hostage. As of December 19, 2011, efforts were still underway to locate the missing soldiers.'
'No reported information on a ransom'
'No information available regarding ransom'
'5 million Nigerian Naira (approximately $32,000 U.S.) was demanded for the release of the victim in this case. The ransom was not paid.'
'No report of ransom demand'
"It is unknown if a ransom was paid for the victim's release."
"The perpetrators demanded that China pressure the government of Sudan to allow humanitarian aid into the country's restive northern region in exchange for the release of the hostages."
"The perpetrators demanded the release of one of their relatives in exchange for the victims' release."
'It could not be determined if the victim was released after negotiations or due to payment of a ransom.'
'The assailants later lowered their ransom demand to $70,958.02.'
'The perpetrators demanded that the government release all Maoist rebels from prison and that they disband all police and paramilitary camps in exchange for the release of the victims in this incident.'
'The perpetrators demanded Rs 1.2 crore. It was not reported whether the perpetrators were paid any ransom amount.'
'Reports indicate that the perpetrators made demands, but those demands were not identified.'
'The assailants have demanded an undisclosed amount of money and the release of prisoners in exchange for the release of the victim.'
'In addition to demanding 15 million Euro, the perpetrators also demanded the release of prisoners in exchange for the release of the diplomats.'
'The kidnap victims in this incident were released after the Afghan government agreed to release the relatives of a Taliban commander that had been jailed.'
"Sources stated that the abductors called Faizul Islam's family members demanding 1 crore ransom for his release."
'The perpetrator demanded that the relatives of the victims in this incident leave their government jobs in exchange for the release of the abductees.'
'The perpetrators reportedly demanded the release of anti-Assad prisoners being held in Syria and Lebanon in exchange for the release of the victims.'
'There were no monetary demands. The kidnappers demanded the release of their relatives who were jailed for involvement in terrorists activities.'
'The perpetrators in this incident demanded an unspecified number of weapons in exchange for the release of the abductees.'
'The perpetrators stated that the purpose of the abduction was to secure the release of 11 Lebanese pilgrims being held by Syrian opposition groups.'
'Perpetrators demanded money for the release of their fellow member, and return of land they claimed they had won.'
'The perpetrators in this incident demanded jobs in the police force in exchange for the release of the abductees.'
'The hostages were released in exchange for the release of 2130 prisoners being held in Syrian prisons.'
'The hostage victim was released by the perpetrators on October 7, 2012 in exchange for the promise of the release of a jailed kinsman of the Yemeni tribesmen who abducted the hostage victim.'
'The assailants demanded the release of Taliban prisoners in exchange for the release of the hostages.'
'The assailants later increased their ransom demanded to $25,000,000.'
'The assailants originally demanded $700,000 in exchange for the release of the three hostage victims. The hostage victims were later released on February 3, 2013 in exchange for the release of an unknown number of affiliated militants'
'An unknown amount was demanded for the release of the victim; however, the ransom was not paid. Instead, as a condition of his release, the victim was forced to sign a document stating that he would not seek a seat in an upcoming election.'
'The assailants demanded the release of Khaled Suleiman, an imprisoned Saudi Arabian national, in exchange for the return of the hostage.'
'The release of prisoners Omar Abdel and Aafia Siddiqui was demanded.'
'The perpetrators demanded that the construction of a local bridge stop in exchange for the release of the victims.'
'In addition to a monetary demand, the perpetrators also asked for the release of prisoners being held in Cameroon and Nigeria. An unspecified number of prisoners were reportedly released by both countries.'
'The assailants originally demanded $167,630 for the release of the victims, but later reduced the sum to $83,610.'
'The release of Taliban prisoners was demanded in this attack.'
'A ransom was paid for only one of the hostage victims.'
'The perpetrators demanded that citizens not participate in upcoming elections in exchange for the release of the kidnap victims.'
'The amount that was demanded for the release of the victim conflicts across sources. Following GTD protocol, the lowest estimate is reported here.'
'The assailants demanded the release of their imprisoned accomplices in exchange for the safe release of the hostages.'
'It is unknown if ransom was demanded in this kidnapping.'
'The perpetrators demanded the release of an unknown number of prisoners in exchange for the release of the kidnap victims.'
'It is unknown if ransom was requested in this kidnapping.'
'The perpetrators demanded that military activities in two contested areas be suspended in exchange for the release of the kidnap victims.'
'The kidnappers demanded the release of their jailed relatives from the central prison in Abyan.'
'The perpetrators demanded the release of prisoners in exchange for the kidnap victims.'
'Sources conflict on whether the assailants originally demanded $500,000 or $106,636.80.'
'Three prisoners were released in exchange for the release of the abductees.'
'The assailants demanded the release of two prisoners in exchange for the release of the victim.'
'The assailants demanded $33,526 from Nirajoy Tripura, a legislator, and $38.55 from an unknown number of families for the release of the victims.'
'The assailants originally demanded $301,279 for the release of the hostage victims. They later lowered the demands to $37,660.'
'The perpetrators demanded the release of Taliban prisoners and their family members in exchange for the release of the hostages.'
'The assailants demanded that a Manobo tribal chieftain be freed in exchange for the safe release of the hostage.'
'The assailants originally demanded $300,000 for the release of the hostage victim. They later increased their demands to $ 1,500,000 for his release.'
'It is unknown if a ransom was demanded in this kidnapping.'
"The assailants demanded the deactivation of 50 newly appointed government militia members and the withdrawal of military forces in exchange for the hostages' release."
'It is unknown if any ransom was demanded in this kidnapping.'
'It is unknown if any ransom was demanded in this attack.'
'The assailants demanded that electricity be extended to their village.'
'The assailants agreed to free the hostages on the condition that the Pakistani government stop sending polio vaccination teams into the area.'
'The perpetrators demanded the release of 1,000 female detainees from Syrian prisons.'
'The perpetrators demanded the release of individuals imprisoned in political and national security prisons without any charges or legal cases against them.'
'It is unknown if any ransom was demanded.'
'The assailants later reduced the demanded ransom amount to $116,861.'
'Although family sources reported that an undisclosed amount of money was paid for the release of the hostages, the police denied that any ransom was paid to the assailants.'
'A ransom was paid for only three of the hostages.'
'The assailants demanded six AK-47 rifles in exchange for the release of the hostage.'
"The assailants demanded the release of Sha'ban Hadiyah, the head of the Libya Revolutionaries' Operation Room (LROR), in exchange for the hostage."
'The ransom amount paid for this incident conflicted across sources. Following GTD protocol, the majority reliable estimates are reported here.'
"It is unknown whether the ransom was paid. While an intelligence official asserted that the ransom was paid, the victim's family denied paying the ransom demand."
'The total ransom amount demanded for this incident conflicts across sources. Following GTD protocol, the lowest reliable estimate is reported here.'
'The soldiers will be returned in exchange for the evacuation of all military camps in the governorate and the transfer of military leadership to soldiers from Hadramout.'
'The total ransom amount demanded for this incident conflicts across sources. Following GTD protocol, the majority reliable estimates are reported here.'
'While one source reported that the assailants demanded that the hostages resign from the Afghan National Army (ANA) in return for their safe release, another stated that the assailants demanded the return of the deceased bodies of two of their cohorts in exchange for the hostages.'
'The assailants demanded the release of two Libyan terror suspects in exchange for the safe return of the hostage.'
'It is unknown if a ransom was paid in exchange for the release of the hostage.'
'It is unknown whether a ransom was demanded or not.'
"The hostage's family paid $500,000 ransom and donated $50,000 worth of food to impoverished communities as demanded by the assailants."
'Prisoners were also exchanged for the release of the hostages.'
'The assailants demanded the release of imprisoned pro-Russian separatists in exchange for the safe return of the hostages.'
'It is unknown if this ransom was paid.'
'The perpetrators demanded the acquittal and release of Justice and Equality Movement (JEM) members who are currently facing life in prison and death penalty charges in connection with the May 10, 2008 attack on Omdurman.'
'The assailants also demanded that the German government discontinue its support of the recent airstrikes against the Islamic State of Iraq and the Levant (ISIL).'
'The assailants demanded the release of an imprisoned relative in exchange for the safe return of the hostage.'
'The assailants demanded the return of 20 slain perpetrators in exchange for the release of the hostage.'
'The assailants demanded the release of imprisoned pro-Russian supporters in exchange for the safe return of the hostages.'
'The assailants demanded that one of the hostages resign from his local government position in exchange for his safe release.'
'The perpetrators demanded the release of Aung Soe, the removal of existing fence work, and no additional erecting of fencing on land whose owners rejected land subsidy from the government. Later, they demanded the total halting of the Letpadaung project.'
'The assailants demanded the release of prisoners in exchange for the safe return of the hostages.'
'The assailants later lowered their demand to $158,049.43 and then to $67,735.47.'
'The assailants demanded cattle in exchange for the release of the hostages.'
'A ransom was paid for only one of the hostages.'
'The assailants demanded the release of thousands of prisoners in exchange for the safe return of the hostages.'
"Prior to the ransom demand, the assailants originally demanded that the victim's son resign as Bayelsa State Commissioner in exchange for her release. The assailants also demanded that the victim's family provide them with four Nokia handsets in exchange for her release."
'The assailants later lowered their ransom demand to $842626.05.'
'The assailants later lowered their ransom demand to $109,931.16.'
'A ransom was paid for only two of the hostages.'
'It is unknown how much ransom was paid.'
'It is unknown if the $5,500,000 ransom was paid in this incident.'
'The kidnappers asked the victim to pay Rs 1 lakh when she got home.'
'The kidnap victims were released in a hostage swap.'
'The assailants later lowered their ransom demand to $8,105.05.'
'The assailants demanded that the military suspend its operations in Bukidnon in exchange for the release of the hostages.'
'The assailants demanded the release of prisoners in exchange for the return of the hostage.'
"The assailants demanded the release of two Donetsk People's Republic members in exchange for the safe return of the hostages."
'In exchange for the hostages, the assailants demanded that their organization be removed from the United Nations (UN) terror list; humanitarian aid be delivered to Damascus; and they receive compensation for the deaths of three of their fellow members.'
'The assailants demanded the release of 11 of their imprisoned members, including a leader, in exchange for the safe return of the hostages.'
'In addition to the ransom demand, the assailants also demanded the release of two of their imprisoned members and permission to move unimpeded in Maghrib Ans district in exchange for the safe return of the hostages.'
'The assailants demanded the release of their imprisoned relatives in Egypt in exchange for the safe return of the hostages.'
'The assailants demanded the release of their imprisoned leader in exchange for the safe return of the hostage.'
'The assailants demanded the release of their imprisoned leader in exchange for the safe return of the hostages.'
'The assailants later demanded the release of Sajida al-Rishawi, a woman imprisoned in Jordan on terrorism charges, in exchange for the safe return of the hostage.'
"One of the hostage victims was released in a prison exchange between the People's Protection Units (YPG) and the Islamic State of Iraq and the Levant (ISIL)."
'The assailants demanded the release of Sajida al-Rishawi, a woman imprisoned in Jordan on terrorism charges, in exchange for the safe return of the hostage.'
'The assailant demanded that security forces allow Cherif Kouachi and Said Kouachi, who were involved in another hostage situation on the same day, to go free in exchange for the release of the hostages.'
'The hostage victim was released by the assailants in exchange for the release of two individuals, one Russian fighting for the separatists and a civilian who was accused of supporting the separatists (Oksana Lytovchenko).'
'The hostages were released in a prisoner swap.'
'The assailants demanded an unknown amount for the release of the hostage victims.'
"The assailants reportedly demanded the release of anti-Balaka commander Rodrigue Nagibona in exchange for the kidnap victim's freedom."
'The victims were released after the assailants were promised party funds.'
"The assailants originally demanded $23647.95 but later lowered this amount to $7882.65 and ten women's watches and two mobile handsets."
'The assailants demanded a ransom of $20,000 (50 million pesos) for each of the two hostages.'
'The assailants demanded the removal of military personnel from an army camp, the incorporation of 200 Radfan locals into the 201st Armored Brigade, the reinstatement of forcibly-retired military personnel from 1994, and the removal of five recently-established checkpoints in exchange for the safe release of the hostages.'
'There are conflicting reports regarding ransom demands. On May 5, 2015, it was reported that the assailants demands $100,000 for each prisoner, totaling $23,000,000 (Cross Map 05/05/2015). On October 9, 2015, it was reported that the assailants demanded $50,000 for each prisoner, totaling $14,000,000 (Christian Post, 10/19/2015). Later, reports noted that the assailants demanded $18,000,000 for the release of the hostage victims (San Francisco Chronicle, 2/22/2016). Finally, it was noted that less than $9,000,000 was paid for the release of the hostage victims (San Francisco Chronicle, 2/22/2016).'
'The assailants demanded the release of comrades held by the Afghan government in exchange for the hostages.'
'The assailants originally demanded $221388.40 for the release of the hostages. They later reduced their ransom demands to $21891.42.'
'The assailants demanded $150,000 for the release of the hostage victims. In addition, the assailants demanded three trucks loaded with food and relief aid.'
'The assailants demanded a live confession of police officers who killed Berkin Elvan in March 2014. Additionally, the assailants demanded that these police officers be put on trial before a "people\'s" court.'
'The assailants requested either a ransom or the apples stocked in the truck.'
'Hostage was released after diplomatic negotiations.'
'The assailants demanded the release of two civilians in exchange for the release of the hostage victims.'
'Other sources noted that the assailants demanded a ransom of $68,629.64. The ransom was later decreased to $2,156,428. It was then decreased to $215,642. Finally, it was decreased to $64,693.'
'$7610.36 might have been paid to kidnappers.'
"The assailants demanded $638,000 for the release of the hostage victims. In addition to monetary ransoms, the assailants demanded medicine from the victims' families."
'The assailants demanded a ransom of $5,000 for the release of one of the fourteen hostage victims.'
'The assailants demanded the release of four foreign prisoners in exchange for the hostages.'
'The assailants later decreased the ransom demanded to $4534.47.'
'The assailants demanded $50665.72 (70,000 Libyan Dinars) for the release of the hostage victims.'
'Al Nusra Front demanded an unknown ransom for the release of the hostage victim.'
'The assailants demanded an unspecified ransom for the release of hostage victims.'
'The assailants demanded the release of female prisoners in exchange for the release of the hostage victims.'
'Two sources note that the assailants demanded $40,000; however, the coding reflects the lowest reliable information, $20,000 as a ransom.'
'Assailants demanded the release of fifty Salafi jihadists who are being held by HAMAS. Additionally, the assailants desire the assurance that these people will not be abducted in the future.'
'The assailants demanded the release of two individuals imprisoned by the Keerom Police in exchange for the hostage victims.'
'The assailants demanded $4355 (300000 Afghani dinars) for each hostage victim in exchange for the release of the four hostage victims.'
'A ransom of four billion Philippine pesos ($80,242,680 USD) was demanded for the release of the four hostages. Fifty million Philippine pesos ($1,003,033.50 USD) was paid for the release of the Norwegian victim.'
'The assailants initially demanded $317,713 (100 million Nigerian Naira), but later reduced the demands to $285,941.70 (90 million Nigerian Naira). A ransom of $25,122.98 (5 million Nigerian Naira) was paid for the release of the victim.'
'The assailants demanded $64326.71 (Tk 50 lakh) for the release of the hostage victims. The ALP later claimed that no ransom was demanded.'
'The assailants demanded $16,300 for the release of the hostage victims. It is unknown if the ransom was paid.'
'The assailants took hostages to protest against bauxite mining in the area.'
'The assailants demanded an unknown ransom amount for the release of the hostage victim. While the assailants were paid a ransom for the release of the victim, it is unknown how much was paid for the ransom.'
'The assailants demanded the release of government-held prisoners.'
'The hostage was used as leverage for perpetrators against government threats.'
'The assailants initially demanded $367840 dollars (500,000 Libyan dinars). The assailants later reduced their ransom demands to $220,178.41 (300,000 Libyan dinars). The ransom amount paid to the assailants is unknown.'
'The assailants demanded $2,000.00 per hostage for the release of the hostage victims. Reports conflict on whether or not a ransom was paid.'
'The assailants demanded an unknown ransom for the release of the hostage victims.'
'The assailants demanded $63636 (210 million pesos) for the release of the hostage victims. A source of unknown validity (Bogota Caracol Radio Online) reported that a ransom of 30 million pesos (approx. $10,000.00) was paid.'
'The assailants demanded $24,460 (SDG150,000) in exchange for the hostages. It is unknown if any ransom was paid for the release of the hostages.'
'It is unknown if any ransom was requested in this attack.'
'The assailants demanded an unknown amount for the release of the hostage victims. $2966 (Rs 2 lakh) was given as ransom for their release.'
'The assailants demanded the release of certain prisoners held in France.'
'The assailants demanded the return of four hundred sheep in exchange for the release of the hostage victims.'
'The assailants demanded an unknown amount for the release of the hostage victim. The hostage victim was released after an unknown ransom amount was paid.'
'The assailants demanded an unknown amount for the release of the hostage victim. The hostage victim was released after the assailants were paid an unknown amount.'
'The assailants demanded $15,140.00 (Rs 10 lakh) for the release of the hostage victims. The ransom demands were not paid.'
'The assailants demanded $5677746.98 (5 million euros) as a ransom for the release of the hostage victim; however, no ransom was paid.'
'The assailants demanded the release of Sheikh Nimr Baqir al-Nimr from Saudi custody in exchange for the safe release of the hostages.'
'The assailants demanded a blanket, clothes, and perfume for the release of the hostage victim.'
'The abductors are demanding the release of Hannibal Gaddafi in exchange for the release of the hostages.'
'The assailants also demanded the release of Nnamdi Kanu, an imprisoned separatist leader, in exchange for the release of the hostages.'
'One hostage was released after paying $200 USD'
'The assailants initially demanded a ransom of an unknown amount for the release of the hostage victims; however, they released 108 of the 110 victims after viewing their identity cards.'
'A ransom of $10635 (approximately 500,000 Philippine pesos) was demanded for each of the hostage victims. The ransom was increased to $21270 (approximately 1,000,000 Philippine pesos); however, two of the three hostage victims were released without the ransom being paid.'
'The assailants demanded $3280 for the release of the hostage victims. The family of the victims paid $820 for the release of the victims and promised to pay the remainder later.'
'Assailants demanded $295 (INR 20,000) from a journalist.'
'The release of the "Captain," presumed to be Hannibal Gadhafi, was demanded for the release of the hostage victim.'
'There is conflicting information on whether $286,724.70 was paid for the release of the hostages.'
'One source reported that the assailants demanded $95,397.10, while a more recent source indicated that a $190,794.20 ransom was demanded. The final three hostages were relased after $38,169.76 (4 million Pakistani Rupees) was paid.'
'An undisclosed amount of ransom was paid.'
'The hostage victims were released on the condition that they promise to not deliver any merchandise to the eastern areas.'
"The abductors demanded the release of their colleague from Tajikistan's custody for the release of the two kidnappees."
'$1060436 (50 million Philippine pesos) was demanded as ransom for the hostages.'
'$108254.01 (150000 Libyan dinars) was demanded as a ransom for the hostages.'
'There was an unconfirmed report that $2,147,561 was paid for the release of the hostages.'
'The assailants demanded the release of one of their captured members in exchange for the release of the hostages.'
'A ransom of $15,860.45 (5 million Naira) was demanded. A source stated that a ransom of $2,220.46 (700,000 Naira) was paid; however, authorities denied that the payment was made.'
'A ransom of $411,862.73 (SDG2.5 million) was demanded for the release of the hostages.'
'A ransom of $29,626.32 USD (2 million INR) was demanded for the release of the hostage.'
'An unspecified monetary payment was made in exchange for the release of the hostage.'
'Assailants demanded payment on May 18, 2016 and abducted victims when it was not received.'
'A ransom of $7,409.01 USD (500,000 INR) was demanded for the release of the hostage.'
'Ransom numbers represent a division of a cumulative ransom amount across incidents 201606200018 and 201606200019.'
'A ransom of $6,354.29 USD (2 million Nigerian Naira) was demanded.'
'A ransom of $602,775.30 USD (30,000,000 PHP) was paid in exchange for the release of the three hostages.'
'The initial ransom demand of $2,000,000 USD was lowered to $500,000 USD.'
'The assailants demanded $11,163,900 (10 million EUR) for the release of the hostage.'
'A ransom of $3,739.95 (300,000 BDT) was paid for the release of the hostage.'
'A ransom of $148,130.40 USD (10,000,000 INR) was demanded for the release of the hostage.'
'Two hostages were freed after a $19,856 ransom payment was made for each victim. The final hostage was released in exchange for a $59,576 payment.'
'The assailants demanded a ransom of $22,240.17 USD (1,500,000 INR). $1,186.14 USD (80,000 INR), a laptop, and a printer were paid in exchange for the release of the hostage.'
'A ransom of $1,000 per hostage was demanded.'
'A ransom of $40,137.28 USD (2,000,000 Philippine pesos) was demanded for the release of the hostages.'
'A ransom of $4,277,040 USD (4,000,000 EUR) was demanded for the release of the hostages.'
'A ransom of $228,571.43 USD (LD 320,000) was paid in exchange for the release of the hostages.'
'A ransom of $502.46 USD (25,000 Philippine Pesos) was demanded and paid in exchange for the release of the hostages.'
'A handgun was also included in the ransom demand.'
'A ransom of $363,000 (500,000 Libyan dinars) was demanded for the release of the hostage.'
'The assailants demanded the release of six prisoners in exchange for 11 of the hostages.'
'A ransom of $52,383.52 USD (3.5 miliion Indian Rupees) was demanded for the release of the hostage.'
'All ransom demands so far have been deemed fake.'
'The assailants demanded 15 sheep for the release of the hostage.'
'A ransom of $32,568.00 USD (10 million NGN) was demanded for the release of one hostage. A ransom of $16,284.00 USD (5 million NGN) was demanded for the release of the other two hostages.'
'The assailants demanded between two and three million NGR for the release of each hostage. Following GTD protocol, the loweset estimate of 2 million NGR ($6,519.98 USD) per hostage was used to estimate the total ransom demanded.'
'The assailants demanded between two and three million Nigerian Naira for the release of each hostage.']
========
hostkidoutcome
<type 'numpy.float64'>
8
[ nan 2. 5. 4. 3. 7. 6. 1.]
========
hostkidoutcome_txt
<type 'float'>
8
[nan 'Hostage(s) released by perpetrators' 'Successful Rescue'
'Hostage(s) killed (not during rescue attempt)'
'Hostage(s) escaped (not during rescue attempt)' 'Unknown' 'Combination'
'Attempted Rescue']
========
nreleased
<type 'numpy.float64'>
151
[ nan 1.00000000e+00 5.00000000e+00 6.00000000e+01
1.00000000e+01 1.55000000e+02 1.75000000e+02 3.00000000e+00
4.00000000e+00 6.00000000e+00 2.60000000e+01 1.87000000e+02
1.05000000e+02 2.00000000e+00 8.20000000e+01 1.30000000e+01
4.80000000e+01 -9.90000000e+01 1.60000000e+01 8.00000000e+00
2.30000000e+01 2.50000000e+01 9.20000000e+01 7.00000000e+00
1.20000000e+01 7.00000000e+01 5.60000000e+01 1.40000000e+01
3.40000000e+01 0.00000000e+00 6.60000000e+01 4.40000000e+01
3.00000000e+01 1.37000000e+02 1.80000000e+01 1.10000000e+02
1.47000000e+02 4.30000000e+01 5.00000000e+01 5.40000000e+01
1.13000000e+02 2.15000000e+02 7.90000000e+01 3.80000000e+01
1.02000000e+02 1.38000000e+02 1.00000000e+02 9.00000000e+01
9.00000000e+00 2.10000000e+01 1.14000000e+02 3.90000000e+02
1.89000000e+02 2.64000000e+02 4.60000000e+01 1.18000000e+02
1.31000000e+02 1.27000000e+02 1.57000000e+02 3.30000000e+01
9.70000000e+01 7.10000000e+01 1.61000000e+02 1.52000000e+02
2.20000000e+01 1.25000000e+02 1.51000000e+02 1.29000000e+02
4.20000000e+01 3.10000000e+01 3.20000000e+01 1.62000000e+02
8.80000000e+01 1.44000000e+02 1.15000000e+02 1.90000000e+01
4.00000000e+01 1.10000000e+01 1.30000000e+02 1.39000000e+02
1.56000000e+02 2.70000000e+01 1.64000000e+02 6.90000000e+01
3.60000000e+01 1.07000000e+02 1.99000000e+02 2.01000000e+02
1.50000000e+01 8.00000000e+01 4.70000000e+01 2.00000000e+01
1.70000000e+01 8.30000000e+01 2.40000000e+01 6.40000000e+01
2.30000000e+02 8.10000000e+01 1.88000000e+02 7.50000000e+02
3.90000000e+01 4.96000000e+02 1.65000000e+02 9.10000000e+01
1.72000000e+02 1.04000000e+02 5.10000000e+01 1.90000000e+02
4.10000000e+01 2.80000000e+01 6.20000000e+01 2.90000000e+01
6.10000000e+01 7.80000000e+02 2.67000000e+02 1.83000000e+02
8.56000000e+02 2.07000000e+02 9.90000000e+01 2.00000000e+02
1.03000000e+02 3.25000000e+02 3.50000000e+01 6.30000000e+01
9.50000000e+01 1.28000000e+02 4.00000000e+02 7.00000000e+02
1.26000000e+02 1.20100000e+03 4.50000000e+01 4.90000000e+01
7.30000000e+01 8.37000000e+02 9.30000000e+01 1.67000000e+02
1.53000000e+02 8.50000000e+01 2.16000000e+02 1.92000000e+02
2.31000000e+02 3.00000000e+02 1.01000000e+02 3.01000000e+02
1.70000000e+02 5.70000000e+01 1.08000000e+02 1.40000000e+02
5.50000000e+01 6.00000000e+02 7.96000000e+02]
========
addnotes
<type 'float'>
14151
[nan
'The Cairo Chief of Police, William Petersen, resigned as a result of the attack.'
'Damages were estimated to be between $20,000-$25,000.' ...,
'The victims included Commander Shakoor, Noorullah, and Attiqullah.'
"There is doubt that this incident meets terrorism-related criteria. Sources noted that the attack may have been related on the victim's reporting on corruption and organized crime."
'There is doubt that this incident meets terrorism-related criteria. Witnesses stated that the attack was started by government forces and other sources suspected that the incident may have started due to a disagreement between residents and security forces.']
========
scite1
<type 'float'>
75888
[nan '"Police Chief Quits," Washington Post, January 2, 1970.'
'Committee on Government Operations United States Senate, "Riots, Civil, and Criminal Disorders," U.S. Government Printing Office, August 6, 1970.'
...,
'"15 soldiers killed, 19 injured in Niger terror attack," Hindustan Times, February 24, 2017.'
'"Gunmen shoot at home of Mexican indigenous rights reporter," Big News Network, January 10, 2017.'
'"Rebels To Blame For Nierteti Killing: Central Darfur Governor," Radio Dabanga Online, January 2, 2017.']
========
scite2
<type 'float'>
56563
[nan
'"Cairo Police Chief Quits; Decries Local \'Militants\'," Afro-American, January 10, 1970.'
'Christopher Hewitt, "Political Violence and Terrorism in Modern America: A Chronology," Praeger Security International, 2005.'
...,
'"Asia: US Army ASD Philippine Terrorist Media Weekly Wrap-up 25 - 31 December 2016," Summary, January 4, 2017.'
'"\x96 Gunmen shoot at home of Mexican indigenous rights reporter," Human Rights Network For Journalists - Uganda, January 10, 2017.'
'"Security deteriorates in West Darfur alongside attacks by Sudanese forces and local militias," African Centre for Justice and Peace Studies, January 13, 2017.']
========
scite3
<type 'float'>
32563
[nan
'Christopher Hewitt, "Political Violence and Terrorism in Modern America: A Chronology," Praeger Security International, 2005.'
'The Wisconsin Cartographers\' Guild, "Wisconsin\'s Past and Present: A Historical Atlas," The University of Wisconsin Press, 2002.'
...,
'"10-year-old girl used as human bomb in Nigeria attack," Nigeria Sun, January 1, 2017.'
'"28 killed in Baghdad double suicide bombing 2 minutes ago," UPI, December 31, 2016.'
'"Dozens Killed In Baghdad Blasts Claimed By Islamic State," Radio Free Europe, December 31, 2016.']
========
dbsource
<type 'str'>
26
['PGIS' 'Hewitt Project' 'Hijacking DB' 'CBRN Global Chronology' 'CAIN'
'HSI' 'Disorders and Terrorism Chronology'
'State Department 1997 Document' 'UMD Miscellaneous'
'UMD Encyclopedia of World Terrorism 2012' 'Hyland' 'Armenian Website'
'UMD Sri Lanka 2011' 'UMD South Africa' 'Anti-Abortion Project 2010'
'UMD Assassinations Project' 'Eco Project 2010' 'UMD Algeria 2010-2012'
'CETIS' 'Leuprecht Canadian Data' 'UMD Schmid 2012'
'UMD Black Widows 2011' 'Sageman' 'UMD JTMM Nepal 2012' 'ISVG'
'START Primary Collection']
========
INT_LOG
<type 'numpy.int64'>
3
[ 0 -9 1]
========
INT_IDEO
<type 'numpy.int64'>
3
[ 0 1 -9]
========
INT_MISC
<type 'numpy.int64'>
3
[ 0 1 -9]
========
INT_ANY
<type 'numpy.int64'>
3
[ 0 1 -9]
========
related
<type 'float'>
20830
[nan '197001300001, 197001300002' '197001300002, 197001300001' ...,
'201612310006, 201612310007, 201612310008' '201612310027, 201612310028'
'201612310034, 201612310035, 201612310036, 201612310037']
========
In [12]:
# Get rid of the rows without geolocation details
df.longitude.dropna(axis = 0, inplace=True)
In [13]:
df_ = df[['iyear','imonth','iday', 'region', 'region_txt', 'country','country_txt','provstate',
'city', 'latitude', 'longitude', 'location', 'attacktype1',
'attacktype1_txt', 'target1', 'targtype1_txt', 'targsubtype1',
'motive','nkill','nwound','weaptype1']]
df_.shape
Out[13]:
(170350, 21)
In [14]:
df_.rename(index = str, columns = {'iyear':'year','imonth':'month', 'iday':'day' }, inplace=True)
#Replace dates where day is 0 to 1
df_['day'] = df_.day.replace(0, 1)
#Drop those lines where month is 0
df_ = df_[df_.month != 0]
# Turn Year/Month/Day into a Date
df_['Date'] = pd.to_datetime(df_[['year', 'month', 'day']])
# Set Date as index
df_ = df_.set_index('Date')
# Let's check what we have
df_.head()
/Users/baurjansafi/anaconda/lib/python2.7/site-packages/pandas/core/frame.py:2844: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy **kwargs) /Users/baurjansafi/anaconda/lib/python2.7/site-packages/ipykernel_launcher.py:4: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy after removing the cwd from sys.path.
Out[14]:
| year | month | day | region | region_txt | country | country_txt | provstate | city | latitude | ... | location | attacktype1 | attacktype1_txt | target1 | targtype1_txt | targsubtype1 | motive | nkill | nwound | weaptype1 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Date | |||||||||||||||||||||
| 1970-07-02 | 1970 | 7 | 2 | 2 | Central America & Caribbean | 58 | Dominican Republic | NaN | Santo Domingo | 18.456792 | ... | NaN | 1 | Assassination | Julio Guzman | Private Citizens & Property | 68.0 | NaN | 1.0 | 0.0 | 13 |
| 1970-01-01 | 1970 | 1 | 1 | 5 | Southeast Asia | 160 | Philippines | Tarlac | Unknown | 15.478598 | ... | NaN | 1 | Assassination | Employee | Journalists & Media | 54.0 | NaN | 1.0 | 0.0 | 13 |
| 1970-01-01 | 1970 | 1 | 1 | 8 | Western Europe | 78 | Greece | Attica | Athens | 37.983773 | ... | NaN | 3 | Bombing/Explosion | U.S. Embassy | Government (Diplomatic) | 46.0 | NaN | NaN | NaN | 6 |
| 1970-01-01 | 1970 | 1 | 1 | 4 | East Asia | 101 | Japan | NaN | Fukouka | 33.580412 | ... | NaN | 7 | Facility/Infrastructure Attack | U.S. Consulate | Government (Diplomatic) | 46.0 | NaN | NaN | NaN | 8 |
| 1970-01-01 | 1970 | 1 | 1 | 1 | North America | 217 | United States | Illinois | Cairo | 37.005105 | ... | NaN | 2 | Armed Assault | Cairo Police Headquarters | Police | 22.0 | To protest the Cairo Illinois Police Deparment | 0.0 | 0.0 | 5 |
5 rows × 21 columns
In [15]:
%matplotlib inline
df_.groupby("year").month.count().plot(figsize=(12,8),
title= 'Yearly Attacks',
fontsize=14,
)
plt.ylabel('Number of Attacks per Year')
Out[15]:
<matplotlib.text.Text at 0x1209b87d0>
In [16]:
%matplotlib inline
df_.groupby("month").month.count().plot(figsize=(12,8),
title= 'Monthly Attacks',
fontsize=14)
df_.groupby("month").month.count()
Out[16]:
month 1 14036 2 12975 3 14284 4 14213 5 15771 6 14258 7 15247 8 14802 9 13246 10 14728 11 14064 12 12706 Name: month, dtype: int64
In [38]:
df_.to_csv('data/gup_.csv')
In [18]:
%matplotlib inline
l = df_.attacktype1_txt.unique()
for i in l:
df_[df_.attacktype1_txt == i].groupby("year").attacktype1_txt.count().plot(figsize=(12,8),
title= "Yearly Attacks by Type of Attack",
fontsize=14)
_ = plt.legend(df_.attacktype1_txt.unique())
In [19]:
df_.region_txt.value_counts().plot(figsize=(12,8),
kind = 'bar',
title = "Number of Attacks by Region",
fontsize = 14
)
# let's see what regions have for terror attacks for the past 46 years.
Out[19]:
<matplotlib.axes._subplots.AxesSubplot at 0x120a98ed0>
Sandbox. Playing with other datasets. Like urban population and oil prices¶
In [21]:
# import urban population data for each country in the past 46 years.
# resource is World Bank
df_pop= pd.read_csv('data/global_urban_population.csv')
In [22]:
# Convert the imported file into mergeable data
z = pd.DataFrame()
x = 0
for i in range(df_pop.shape[0]):
for j in range(1,df_pop.shape[1]):
z.set_value(x,'Country_Year', (df_pop['Country Name'][i] +"_" + str(df_pop.columns[j])))
z.set_value(x,'Urban_Pop', df_pop.iloc[i][j])
x += 1
z.head()
Out[22]:
| Country_Year | Urban_Pop | |
|---|---|---|
| 0 | Aruba_1970 | 29900.0 |
| 1 | Aruba_1971 | 30082.0 |
| 2 | Aruba_1972 | 30275.0 |
| 3 | Aruba_1973 | 30470.0 |
| 4 | Aruba_1974 | 30605.0 |
In [23]:
# I found the date with global population and wanted to get an idea if the global terrorism
# is also a sign of overpopultion. Needed to convert it into a mergeable form for the Tableau visualization
z.to_csv('data/gup_zz.csv')
In [24]:
oilprice = pd.read_csv('data/OilPrice.csv')
In [25]:
oilprice.set_index(['year'], inplace = True)
In [32]:
oilprice.plot(kind = 'line', color = 'black', figsize = (12,8), fontsize = 14)
plt.xlabel('Year 1970 - 2016', fontsize = 14)
plt.ylabel('Price for Oil $/barrel', fontsize = 14)
Out[32]:
<matplotlib.text.Text at 0x1209e5550>
In [33]:
for i in df.region_txt.unique():
print i, df.region[df.region_txt == i].mean()
Central America & Caribbean 2.0 North America 1.0 Southeast Asia 5.0 Western Europe 8.0 East Asia 4.0 South America 3.0 Eastern Europe 9.0 Sub-Saharan Africa 11.0 Middle East & North Africa 10.0 Australasia & Oceania 12.0 South Asia 6.0 Central Asia 7.0
Part Two: Bayesian Inference¶
Terror attacks are a ripe area of research for Bayesian inference. Given their infrequency, it is (thankfully) difficult for us to assume a high number of samples that approach some normal distribution. Because of this, we should construct a prior about the amount of terror a given area has seen and update that prior with new information (like a new year of attacks or a contrasting country from within the same region). You should compare two populations of your choosing using Bayesian inference. We want to know if the amount of terror one area has seen differs in a significant way than another area (or time period!) For example, if you are interested in knowing if one country in South America differs in a significant way from another area, you may make your prior assume that some country is a country in South America with μ average attacks and σ variation across South American countries. You would then update that prior with the information of a single country in South America as well as a separate country in South America. How significantly do the resulting posteriors differ? (An important assumption made here is that the time periods are being held constant, perhaps a single year.) You should structure your own test of populations rather than using the above example. If you're unable to setup a different test, brainstorm with your squad in the Slack chat. You must justify the prior you selected and interpret your results (use credible intervals.) Remember you can attempt to use different priors (but don't "prior hack" to affect your output!)
In [34]:
# I would go with Bombings/Explosions in Russia
dfba = df_[(df_.attacktype1 == 3)&(df_.country == 167)]
In [35]:
dfba.year.value_counts().sort_index().plot(figsize=(12,8),
kind = 'bar',
title = "Number of Bomb Explosions in Russia",
fontsize = 14
)
# Which is in line with the global trends and fead by price in oil that
# They used to steal from pipelines
Out[35]:
<matplotlib.axes._subplots.AxesSubplot at 0x1191f7890>
In [ ]:
import pymc3 as pm
import theano as thno
import theano.tensor as T
In [ ]:
# Let me see if terrorism in Dagestan and Chechnya before Vladimir Putin
# became the president of Russia was of different nature?
dfba_prior = dfba[dfba.year < 2000]
In [26]:
# And after Putin has come to power
dfba_post = dfba[dfba.year >= 2000]
In [27]:
# Average number of bomb attacks in Russia before 2010:
prior_mean = dfba_prior.year.value_counts().mean()
prior_std = dfba_prior.year.value_counts().std()
print prior_mean
print prior_std
19.7142857143 9.1417410033
In [61]:
Dagestan = dfba_post[(dfba_post.provstate.str.contains('Dages'))|(dfba_post.city.str.contains('Dages'))].year.value_counts().values
Chechnya = dfba_post[(dfba_post.provstate.str.contains('Chech'))|(dfba_post.city.str.contains('Chech'))].year.value_counts().values
Ingushet = dfba_post[(dfba_post.provstate.str.contains('Chech'))|(dfba_post.city.str.contains('Chech'))].year.value_counts().values
In [63]:
plt.figure(figsize=(16,8))
D = df_[(df_.provstate.str.contains('Dages'))|(df_.city.str.contains('Dages'))].year.value_counts().sort_index().plot()
Ch = df_[(df_.provstate.str.contains('Chech'))|(df_.city.str.contains('Chech'))].year.value_counts().sort_index().plot()
In = df_[(df_.provstate.str.contains('Ingush'))|(df_.city.str.contains('Ingush'))].year.value_counts().sort_index().plot()
plt.legend(['Dagestan', 'Chechnya', 'Ingushetia'], fontsize = 14)
Out[63]:
<matplotlib.legend.Legend at 0x132c243d0>
In [35]:
# Instatiating the model
with pm.Model() as model:
D_mean = pm.Normal('bombings_Dagestan_mean', prior_mean, sd = prior_std)
Ch_mean = pm.Normal('bombings_Chech_mean', prior_mean, sd = prior_std)
In [314]:
std_prior_lower = 0.01
std_prior_upper = 100.0
with model:
D_std = pm.Uniform('bombings_Dagestan_st', lower = std_prior_lower, upper = std_prior_upper)
Ch_std = pm.Uniform('bombings_Chechnya_st', lower = std_prior_lower, upper = std_prior_upper)
In [315]:
with model:
grpD = pm.Normal('group_Dagestan', mu=D_mean,sd = D_std, observed=Dagestan)
grpCh = pm.Normal('group_Chechnya', mu=Ch_mean,sd = Ch_std, observed=Chechnya)
In [316]:
with model:
diff_of_means = pm.Deterministic('difference of means', D_mean - Ch_mean)
diff_of_stds = pm.Deterministic('difference of stds', D_std - Ch_std)
effect_size = pm.Deterministic(
'effect size',
diff_of_means/np.sqrt((D_std**2+Ch_std**2)))
In [317]:
with model:
trace = pm.sample(20000, njobs = 4)
Auto-assigning NUTS sampler... Initializing NUTS using ADVI... Average Loss = 156.93: 5%|▍ | 9088/200000 [00:00<00:14, 13039.87it/s] Convergence archived at 9900 Interrupted at 9,900 [4%]: Average Loss = 161.14 100%|██████████| 20500/20500 [00:59<00:00, 342.14it/s]
In [319]:
pm.plot_posterior(trace[2000:],
varnames = ['bombings_Dagestan_mean', 'bombings_Chech_mean',
'bombings_Dagestan_st', 'bombings_Chechnya_st'],
color = '#87ceeb')
Out[319]:
array([<matplotlib.axes._subplots.AxesSubplot object at 0x14bcfd9d0>,
<matplotlib.axes._subplots.AxesSubplot object at 0x14bfd8f10>,
<matplotlib.axes._subplots.AxesSubplot object at 0x14bfa9210>,
<matplotlib.axes._subplots.AxesSubplot object at 0x14cbc8a10>], dtype=object)
In [320]:
pm.plot_posterior(trace[2000:],
varnames=['difference of means', 'difference of stds', 'effect size'],
ref_val=0,
color='#87ceeb')
Out[320]:
array([<matplotlib.axes._subplots.AxesSubplot object at 0x14e8cca90>,
<matplotlib.axes._subplots.AxesSubplot object at 0x14c57dd90>,
<matplotlib.axes._subplots.AxesSubplot object at 0x13fc91350>], dtype=object)
In [321]:
pm.summary(trace[2000:], varnames = ['difference of means', 'difference of stds', 'effect size'])
difference of means: Mean SD MC Error 95% HPD interval ------------------------------------------------------------------- 1.665 6.430 0.032 [-10.943, 14.293] Posterior quantiles: 2.5 25 50 75 97.5 |--------------|==============|==============|--------------| -10.992 -2.635 1.685 5.971 14.256 difference of stds: Mean SD MC Error 95% HPD interval ------------------------------------------------------------------- -1.997 5.947 0.022 [-14.170, 9.762] Posterior quantiles: 2.5 25 50 75 97.5 |--------------|==============|==============|--------------| -14.160 -5.608 -1.918 1.721 9.784 effect size: Mean SD MC Error 95% HPD interval ------------------------------------------------------------------- 0.056 0.210 0.001 [-0.351, 0.473] Posterior quantiles: 2.5 25 50 75 97.5 |--------------|==============|==============|--------------| -0.354 -0.086 0.056 0.197 0.470
In [322]:
from pymc3 import traceplot
traceplot(trace)
Out[322]:
array([[<matplotlib.axes._subplots.AxesSubplot object at 0x14ccb8390>,
<matplotlib.axes._subplots.AxesSubplot object at 0x14c096c10>],
[<matplotlib.axes._subplots.AxesSubplot object at 0x14f829bd0>,
<matplotlib.axes._subplots.AxesSubplot object at 0x13fab0b90>],
[<matplotlib.axes._subplots.AxesSubplot object at 0x14a39b350>,
<matplotlib.axes._subplots.AxesSubplot object at 0x1498e1b90>],
[<matplotlib.axes._subplots.AxesSubplot object at 0x14ccf5610>,
<matplotlib.axes._subplots.AxesSubplot object at 0x1494da5d0>],
[<matplotlib.axes._subplots.AxesSubplot object at 0x144729290>,
<matplotlib.axes._subplots.AxesSubplot object at 0x148d84750>],
[<matplotlib.axes._subplots.AxesSubplot object at 0x14f7c4a90>,
<matplotlib.axes._subplots.AxesSubplot object at 0x14f78db50>],
[<matplotlib.axes._subplots.AxesSubplot object at 0x14f679c50>,
<matplotlib.axes._subplots.AxesSubplot object at 0x14a6a7d10>]], dtype=object)
Part Three: 1993¶Â¶
The year 1993 is missing from our dataset! Given there is a wealth of information across different types of attacks, we will focus analysis on attacktype1 bombings (category 3, as per the codebook) For this section, you should determine a methodology that allows you to best fill in the missing values. Perhaps you want to consider hemispheres to be separate models, for example. (That's the only hint you'll receive - and even that hint is not an optimal option.) Once you've created your methodology and imputed the number of bombings in 1993, you should feel free to apply your methodology to OTHER attack categories. (Bonus opportunity: turn your method into a pipeline. Use that pipeline to fill in other missing attack values.)
In [546]:
# First let's select the how far we would to go to predict 1993
# You will see below on this notebook that I observed a correlation
# with the oil price. And the observed correlation remains from two
# to six years after. This means 6 effective years (2, 3, 4, 5, 6, 7)
# Meaning that I will look into 1970 until 1999
In [547]:
dfb_1993 = df_[(df_.attacktype1 ==3)&(df_.year >= 1970)&(df_.year < 2000)].year.value_counts().sort_index()
In [548]:
%matplotlib inline
dfb_1993.plot(figsize=(12,8),
kind = 'line',
title = "Number of Bomb Explosions Globally \n Years 1970 - 1999",
fontsize = 14,
color = 'red'
)
Out[548]:
<matplotlib.axes._subplots.AxesSubplot at 0x1539ebe90>
In [549]:
dfb_1993.head()
Out[549]:
1970 333 1971 238 1972 187 1973 149 1974 282 Name: year, dtype: int64
In [557]:
from statsmodels.tsa.stattools import adfuller
In [589]:
def test_stationarity(i, data):
#Determing rolling statistics
#Tried pd.rolling - it spits out a deprecation notification
rolmean = data.rolling(window=i,center=False).mean()
rolstd = data.rolling(window=i,center=False).std()
#Plot rolling statistics:
fig = plt.figure(figsize=(12, 8))
orig = plt.plot(data, color='blue',label='Original')
mean = plt.plot(rolmean, color='red', label='Rolling Mean')
std = plt.plot(rolstd, color='black', label = 'Rolling Std')
plt.legend(loc='best')
plt.title('Rolling Mean & Standard Deviation')
plt.show()
#Perform Dickey-Fuller test:
print 'Results of Dickey-Fuller Test:'
dftest = adfuller(data)#, autolag='AIC')
dfoutput = pd.Series(dftest[0:4], index=['Test Statistic','p-value','#Lags Used','Number of Observations Used'])
for key,value in dftest[4].items():
dfoutput['Critical Value (%s)'%key] = value
print dfoutput
In [618]:
for i in range(1,10):
test_stationarity(i, dfb_1993)
print 'Lag - ', i
Results of Dickey-Fuller Test: Test Statistic -2.444203 p-value 0.129647 #Lags Used 7.000000 Number of Observations Used 21.000000 Critical Value (5%) -3.013098 Critical Value (1%) -3.788386 Critical Value (10%) -2.646397 dtype: float64 Lag - 1
Results of Dickey-Fuller Test: Test Statistic -2.444203 p-value 0.129647 #Lags Used 7.000000 Number of Observations Used 21.000000 Critical Value (5%) -3.013098 Critical Value (1%) -3.788386 Critical Value (10%) -2.646397 dtype: float64 Lag - 2
Results of Dickey-Fuller Test: Test Statistic -2.444203 p-value 0.129647 #Lags Used 7.000000 Number of Observations Used 21.000000 Critical Value (5%) -3.013098 Critical Value (1%) -3.788386 Critical Value (10%) -2.646397 dtype: float64 Lag - 3
Results of Dickey-Fuller Test: Test Statistic -2.444203 p-value 0.129647 #Lags Used 7.000000 Number of Observations Used 21.000000 Critical Value (5%) -3.013098 Critical Value (1%) -3.788386 Critical Value (10%) -2.646397 dtype: float64 Lag - 4
Results of Dickey-Fuller Test: Test Statistic -2.444203 p-value 0.129647 #Lags Used 7.000000 Number of Observations Used 21.000000 Critical Value (5%) -3.013098 Critical Value (1%) -3.788386 Critical Value (10%) -2.646397 dtype: float64 Lag - 5
Results of Dickey-Fuller Test: Test Statistic -2.444203 p-value 0.129647 #Lags Used 7.000000 Number of Observations Used 21.000000 Critical Value (5%) -3.013098 Critical Value (1%) -3.788386 Critical Value (10%) -2.646397 dtype: float64 Lag - 6
Results of Dickey-Fuller Test: Test Statistic -2.444203 p-value 0.129647 #Lags Used 7.000000 Number of Observations Used 21.000000 Critical Value (5%) -3.013098 Critical Value (1%) -3.788386 Critical Value (10%) -2.646397 dtype: float64 Lag - 7
Results of Dickey-Fuller Test: Test Statistic -2.444203 p-value 0.129647 #Lags Used 7.000000 Number of Observations Used 21.000000 Critical Value (5%) -3.013098 Critical Value (1%) -3.788386 Critical Value (10%) -2.646397 dtype: float64 Lag - 8
Results of Dickey-Fuller Test: Test Statistic -2.444203 p-value 0.129647 #Lags Used 7.000000 Number of Observations Used 21.000000 Critical Value (5%) -3.013098 Critical Value (1%) -3.788386 Critical Value (10%) -2.646397 dtype: float64 Lag - 9
I tried Dickey-Fuller Test on various regression and without a regression. The minimum achievable p-value is above. This means that unit root is not a reliable measure of stochastic process. Thus I will go with a rolling mean.¶
In [596]:
rollingmean = dfb_1993.rolling(window = 6, center=False).mean()
rollingmean
Out[596]:
1970 NaN 1971 NaN 1972 NaN 1973 NaN 1974 NaN 1975 259.666667 1976 274.000000 1977 339.333333 1978 415.500000 1979 566.833333 1980 686.000000 1981 804.833333 1982 922.333333 1983 1025.000000 1984 1213.666667 1985 1284.500000 1986 1369.333333 1987 1435.166667 1988 1522.666667 1989 1614.500000 1990 1607.000000 1991 1691.333333 1992 1730.000000 1994 1676.000000 1995 1533.000000 1996 1436.333333 1997 1335.000000 1998 1087.666667 1999 906.666667 Name: year, dtype: float64
In [615]:
# Since, Dickey-Fuller p-value in none of iterations achieved <.05 threshold
# I will use the rolling mean with a window of 6 years behind
# and will calculate the average of the rolling mean for 1992 and 1994
print 'The estimated number of bombings in 1993 is - ', rollingmean[22:24].mean()
The estimated number of bombings in 1993 is - 1703.0
Found data on oil prices. Graphically, there is a visible correlation between the oil price and the spykes in the number of terror attacks. Wanted to see if it reflects on numbers.¶
In [518]:
# So I re-run the same code and shift the oil price
# from 0 to 9 years behind, to see if there is a delayed effect
In [516]:
Rcoef = []
for i in range(10):
oilprice = pd.read_csv('data/OilPrice.csv')
oilprice.set_index(['year'], inplace = True)
oilprice.OilPrice = oilprice.OilPrice.shift(i)
dt = pd.DataFrame(df_.year.value_counts().sort_index())
dt.rename(columns = {'year':'NAttacks'}, inplace = True)
result = dt.join(oilprice, how = 'inner')
result.dropna(inplace = True)
Rcoef.append([i, np.corrcoef(result.NAttacks, result.OilPrice)[0,1]])
In [517]:
Rcoef
Out[517]:
[[0, 0.30980912578825276], [1, 0.4795848590166959], [2, 0.59225100395794661], [3, 0.58892375992158874], [4, 0.57763461354041634], [5, 0.55058267312996534], [6, 0.55071667825621773], [7, 0.52625825483024113], [8, 0.50824527921362839], [9, 0.37333712263327307]]
So, there is a visible correlation between the oil prices and spykes in terrorist activity with a two year lag. It means that oil as well as other commodities, and drug trafficking shall be under a strict control as well as money laundering as they tend to enentually end up in arming various groups of interest.¶
Summary
EDA Our dataset had over 170 thousand observations with 135 features. I focused only on those that had were more consistent from observation to observation. Left 20 features and only those observations that had clear attachment to location. Dropped observations with 0 months, and fixed day 0’s to 1’s.
Added observations on urban population and oil price for the same number of years.
Bayesian inference I was reading about the first and second Russian war on Chechnya. Chechnya announced independence from Russia in 1994 and Russia introduced its troops almost the same year. The military campaign was held by Yeltsin and ended in 1996. There was another one in 1999 - 2000 before Putin was appointed as Russia’s interim leader. I checked on details of how Chechen rebels financed their activity and it turned out that they were stealing oil from the bypassing oil pipelines. It became clear that the terrorist activity spreads along the oil producing areas in the North Caucasus. So I decided to compare if terrorist activity is different or similar in the neighboring republic of Dagestan. Compared the means and standard distribution on both republics and they turned out to be very similar.
It is particularly interesting to observe because there is another Republic of Ingushetia, that is ethnically much closer to Chechnya but it has not been so much involved into terrorist activity.
Imputing 1993 It was a very simple task, since I connected the correlation between oil and terrorist activity I take terrorist activity as far as 6 years ago to impute 1993. The next step was just to calculate the average mean of 1994 and 1992.
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