%matplotlib inline
import datadive.diveindata.diveindata as dv
terror = dv.DataInfo('./globalterrorismdb_0616dist.csv', params={'encoding': 'latin1'})
/home/walrus/.virtualenvs/py3/lib/python3.5/site-packages/IPython/core/interactiveshell.py:2821: DtypeWarning: Columns (4,61,62,66,116,117,123) have mixed types. Specify dtype option on import or set low_memory=False. if self.run_code(code, result):
terror.columns
{'INT_ANY': {'idxmin': -9, 'max': 1, 'mean': -4.2211236700431201, 'min': -9, 'std': 4.6861425686833682, 'sum': -661754, 'type': 'INT', 'uniques': 3}, 'INT_IDEO': {'idxmin': -9, 'max': 1, 'mean': -4.7891141275227715, 'min': -9, 'std': 4.5897788910995079, 'sum': -750799, 'type': 'INT', 'uniques': 3}, 'INT_LOG': {'idxmin': -9, 'max': 1, 'mean': -4.834645217258184, 'min': -9, 'std': 4.5288624534878359, 'sum': -757937, 'type': 'INT', 'uniques': 3}, 'INT_MISC': {'idxmin': -9, 'max': 1, 'mean': 0.093894317862883672, 'min': -9, 'std': 0.60244188893120521, 'sum': 14720, 'type': 'INT', 'uniques': 3}, 'addnotes': {'type': 'CATEGORY', 'uniques': 12762}, 'alternative': {'equivalents': ['alternative_txt'], 'has_equivalent': True, 'idxmin': 1.0, 'max': 5.0, 'mean': 1.2989354678989933, 'min': 1.0, 'std': 0.68227016215906133, 'sum': 31481.0, 'type': 'FLOAT', 'uniques': 6}, 'alternative_txt': {'equivalents': ['alternative'], 'has_equivalent': True, 'type': 'CATEGORY', 'uniques': 6}, 'approxdate': {'type': 'CATEGORY', 'uniques': 1427}, 'attacktype1': {'equivalents': ['attacktype1_txt'], 'has_equivalent': True, 'idxmin': 1, 'max': 9, 'mean': 3.1870806011277524, 'min': 1, 'std': 1.8700641326881142, 'sum': 499645, 'type': 'INT', 'uniques': 9}, 'attacktype1_txt': {'equivalents': ['attacktype1'], 'has_equivalent': True, 'type': 'CATEGORY', 'uniques': 9}, 'attacktype2': {'equivalents': ['attacktype2_txt'], 'has_equivalent': True, 'idxmin': 1.0, 'max': 9.0, 'mean': 3.6159887233185661, 'min': 1.0, 'std': 2.2146946075035352, 'sum': 17957.0, 'type': 'FLOAT', 'uniques': 10}, 'attacktype2_txt': {'equivalents': ['attacktype2'], 'has_equivalent': True, 'type': 'CATEGORY', 'uniques': 10}, 'attacktype3': {'equivalents': ['attacktype3_txt'], 'has_equivalent': True, 'idxmin': 1.0, 'max': 8.0, 'mean': 4.884615384615385, 'min': 1.0, 'std': 2.3102220448717539, 'sum': 1524.0, 'type': 'FLOAT', 'uniques': 9}, 'attacktype3_txt': {'equivalents': ['attacktype3'], 'has_equivalent': True, 'type': 'CATEGORY', 'uniques': 9}, 'city': {'type': 'CATEGORY', 'uniques': 31325}, 'claim2': {'idxmin': -9.0, 'max': 1.0, 'mean': 0.23470319634703196, 'min': -9.0, 'std': 1.2231321911316297, 'sum': 257.0, 'type': 'FLOAT', 'uniques': 4}, 'claim3': {'idxmin': 0.0, 'max': 1.0, 'mean': 0.46835443037974683, 'min': 0.0, 'std': 0.500584194715889, 'sum': 74.0, 'type': 'FLOAT', 'uniques': 3}, 'claimed': {'idxmin': -9.0, 'max': 2.0, 'mean': -0.0010371727113239399, 'min': -9.0, 'std': 1.2102576705415948, 'sum': -94.0, 'type': 'FLOAT', 'uniques': 5}, 'claimmode': {'equivalents': ['claimmode_txt'], 'has_equivalent': True, 'idxmin': 0.0, 'max': 10.0, 'mean': 7.0194335643266044, 'min': 0.0, 'std': 2.706718795807654, 'sum': 93190.0, 'type': 'FLOAT', 'uniques': 12}, 'claimmode2': {'equivalents': ['claimmode2_txt'], 'has_equivalent': True, 'idxmin': 1.0, 'max': 10.0, 'mean': 7.3876543209876546, 'min': 1.0, 'std': 2.9901398488789459, 'sum': 2992.0, 'type': 'FLOAT', 'uniques': 10}, 'claimmode2_txt': {'equivalents': ['claimmode2'], 'has_equivalent': True, 'type': 'CATEGORY', 'uniques': 10}, 'claimmode3': {'equivalents': ['claimmode3_txt'], 'has_equivalent': True, 'idxmin': 1.0, 'max': 10.0, 'mean': 7.5526315789473681, 'min': 1.0, 'std': 3.0524077352896581, 'sum': 574.0, 'type': 'FLOAT', 'uniques': 9}, 'claimmode3_txt': {'equivalents': ['claimmode3'], 'has_equivalent': True, 'type': 'CATEGORY', 'uniques': 9}, 'claimmode_txt': {'equivalents': ['claimmode'], 'has_equivalent': True, 'type': 'CATEGORY', 'uniques': 12}, 'compclaim': {'idxmin': -9.0, 'max': 1.0, 'mean': -6.6511173790410067, 'min': -9.0, 'std': 4.0237197310801118, 'sum': -30655.0, 'type': 'FLOAT', 'uniques': 4}, 'corp1': {'type': 'CATEGORY', 'uniques': 29296}, 'corp2': {'type': 'CATEGORY', 'uniques': 2345}, 'corp3': {'type': 'CATEGORY', 'uniques': 352}, 'country': {'equivalents': ['country_txt'], 'has_equivalent': True, 'idxmin': 4, 'max': 1004, 'mean': 133.08740081136938, 'min': 4, 'std': 113.94628974921478, 'sum': 20864378, 'type': 'INT', 'uniques': 206}, 'country_txt': {'equivalents': ['country'], 'has_equivalent': True, 'type': 'CATEGORY', 'uniques': 206}, 'crit1': {'idxmin': 0, 'max': 1, 'mean': 0.98832699716786165, 'min': 0, 'std': 0.10740957790998934, 'sum': 154942, 'type': 'INT', 'uniques': 2}, 'crit2': {'idxmin': 0, 'max': 1, 'mean': 0.99269002117725103, 'min': 0, 'std': 0.085185616860442917, 'sum': 155626, 'type': 'INT', 'uniques': 2}, 'crit3': {'idxmin': 0, 'max': 1, 'mean': 0.88291914372464475, 'min': 0, 'std': 0.32151763366457714, 'sum': 138417, 'type': 'INT', 'uniques': 2}, 'dbsource': {'type': 'CATEGORY', 'uniques': 26}, 'divert': {'type': 'CATEGORY', 'uniques': 143}, 'doubtterr': {'idxmin': -9.0, 'max': 1.0, 'mean': -0.63689713020903105, 'min': -9.0, 'std': 2.6214223529200651, 'sum': -99847.0, 'type': 'FLOAT', 'uniques': 4}, 'eventid': {'type': 'UNIQUE', 'uniques': 156772}, 'extended': {'idxmin': 0, 'max': 1, 'mean': 0.041346669048044293, 'min': 0, 'std': 0.19909137309588576, 'sum': 6482, 'type': 'INT', 'uniques': 2}, 'gname': {'equivalents': ['ingroup'], 'has_equivalent': True, 'type': 'CATEGORY', 'uniques': 3290}, 'gname2': {'equivalents': ['ingroup2'], 'has_equivalent': True, 'type': 'CATEGORY', 'uniques': 335}, 'gname3': {'equivalents': ['ingroup3'], 'has_equivalent': True, 'type': 'CATEGORY', 'uniques': 78}, 'gsubname': {'type': 'CATEGORY', 'uniques': 993}, 'gsubname2': {'type': 'CATEGORY', 'uniques': 44}, 'gsubname3': {'type': 'CATEGORY', 'uniques': 7}, 'guncertain1': {'idxmin': 0.0, 'max': 1.0, 'mean': 0.089453559599473126, 'min': 0.0, 'std': 0.28539821493516332, 'sum': 13990.0, 'type': 'FLOAT', 'uniques': 3}, 'guncertain2': {'idxmin': 0.0, 'max': 1.0, 'mean': 0.28657487091222034, 'min': 0.0, 'std': 0.45235584689376523, 'sum': 333.0, 'type': 'FLOAT', 'uniques': 3}, 'guncertain3': {'idxmin': 0.0, 'max': 1.0, 'mean': 0.26250000000000001, 'min': 0.0, 'std': 0.44137435443704359, 'sum': 42.0, 'type': 'FLOAT', 'uniques': 3}, 'hostkidoutcome': {'equivalents': ['hostkidoutcome_txt'], 'has_equivalent': True, 'idxmin': 1.0, 'max': 7.0, 'mean': 4.5921704087507198, 'min': 1.0, 'std': 2.0491841403728412, 'sum': 39883.0, 'type': 'FLOAT', 'uniques': 8}, 'hostkidoutcome_txt': {'equivalents': ['hostkidoutcome'], 'has_equivalent': True, 'type': 'CATEGORY', 'uniques': 8}, 'iday': {'idxmin': 0, 'max': 31, 'mean': 15.455215217003037, 'min': 0, 'std': 8.8155331157224879, 'sum': 2422945, 'type': 'INT', 'uniques': 32}, 'imonth': {'idxmin': 0, 'max': 12, 'mean': 6.4846656290664146, 'min': 0, 'std': 3.3922253591909777, 'sum': 1016614, 'type': 'INT', 'uniques': 13}, 'ingroup': {'equivalents': ['gname'], 'has_equivalent': True, 'idxmin': -9, 'max': 100047, 'mean': 4475.8470709055191, 'min': -9, 'std': 10484.350059970258, 'sum': 701687497, 'type': 'INT', 'uniques': 3290}, 'ingroup2': {'equivalents': ['gname2'], 'has_equivalent': True, 'idxmin': -9.0, 'max': 50011.0, 'mean': 19255.760459392946, 'min': -9.0, 'std': 15913.313955697273, 'sum': 23472772.0, 'type': 'FLOAT', 'uniques': 335}, 'ingroup3': {'equivalents': ['gname3'], 'has_equivalent': True, 'idxmin': -9.0, 'max': 40486.0, 'mean': 19952.298780487807, 'min': -9.0, 'std': 14335.366421683293, 'sum': 3272177.0, 'type': 'FLOAT', 'uniques': 78}, 'ishostkid': {'idxmin': -9.0, 'max': 1.0, 'mean': 0.060059772405072993, 'min': -9.0, 'std': 0.41883623514624141, 'sum': 9405.0, 'type': 'FLOAT', 'uniques': 4}, 'iyear': {'idxmin': 1970, 'max': 2015, 'mean': 2000.4740833822366, 'min': 1970, 'std': 12.982397186850177, 'sum': 313618323, 'type': 'INT', 'uniques': 45}, 'kidhijcountry': {'type': 'CATEGORY', 'uniques': 218}, 'latitude': {'idxmin': -53.154612999999998, 'max': 74.633553000000006, 'mean': 23.190988243423597, 'min': -53.154612999999998, 'std': 19.22072269941189, 'sum': 3530897.533025973, 'type': 'FLOAT', 'uniques': 52022}, 'location': {'type': 'CATEGORY', 'uniques': 35798}, 'longitude': {'idxmin': -176.176447, 'max': 179.36666700000001, 'mean': 24.210466985236085, 'min': -176.176447, 'std': 59.900830798232235, 'sum': 3686116.2299031499, 'type': 'FLOAT', 'uniques': 51633}, 'motive': {'type': 'CATEGORY', 'uniques': 11683}, 'multiple': {'idxmin': 0, 'max': 1, 'mean': 0.13037404638583419, 'min': 0, 'std': 0.33671557376214656, 'sum': 20439, 'type': 'INT', 'uniques': 2}, 'natlty1': {'equivalents': ['natlty1_txt'], 'has_equivalent': True, 'idxmin': 4.0, 'max': 1004.0, 'mean': 127.63543434655146, 'min': 4.0, 'std': 87.60599966458399, 'sum': 19852926.0, 'type': 'FLOAT', 'uniques': 213}, 'natlty1_txt': {'equivalents': ['natlty1'], 'has_equivalent': True, 'type': 'CATEGORY', 'uniques': 213}, 'natlty2': {'equivalents': ['natlty2_txt'], 'has_equivalent': True, 'idxmin': 4.0, 'max': 1004.0, 'mean': 130.11593023255813, 'min': 4.0, 'std': 122.71411480931565, 'sum': 1118997.0, 'type': 'FLOAT', 'uniques': 155}, 'natlty2_txt': {'equivalents': ['natlty2'], 'has_equivalent': True, 'type': 'CATEGORY', 'uniques': 155}, 'natlty3': {'equivalents': ['natlty3_txt'], 'has_equivalent': True, 'idxmin': 4.0, 'max': 1004.0, 'mean': 139.28761061946904, 'min': 4.0, 'std': 152.47392610183195, 'sum': 125916.0, 'type': 'FLOAT', 'uniques': 102}, 'natlty3_txt': {'equivalents': ['natlty3'], 'has_equivalent': True, 'type': 'CATEGORY', 'uniques': 102}, 'ndays': {'idxmin': -99.0, 'max': 1941.0, 'mean': -30.865846247341235, 'min': -99.0, 'std': 113.10890931887432, 'sum': -203159.0, 'type': 'FLOAT', 'uniques': 290}, 'nhostkid': {'idxmin': -99.0, 'max': 17000.0, 'mean': 3.9625488107916222, 'min': -99.0, 'std': 211.67170244884184, 'sum': 44650.0, 'type': 'FLOAT', 'uniques': 222}, 'nhostkidus': {'idxmin': -99.0, 'max': 86.0, 'mean': -0.39240167662534559, 'min': -99.0, 'std': 7.1895333145748355, 'sum': -4400.0, 'type': 'FLOAT', 'uniques': 29}, 'nhours': {'idxmin': -99.0, 'max': 999.0, 'mean': -37.322228952150212, 'min': -99.0, 'std': 87.837036484094014, 'sum': -123238.0, 'type': 'FLOAT', 'uniques': 35}, 'nkill': {'idxmin': 0.0, 'max': 1500.0, 'mean': 2.3592374870502684, 'min': 0.0, 'std': 11.42127034765741, 'sum': 348758.99999818002, 'type': 'FLOAT', 'uniques': 339}, 'nkillter': {'idxmin': 0.0, 'max': 500.0, 'mean': 0.41996371039123082, 'min': 0.0, 'std': 3.9668992833381096, 'sum': 37958.000000001004, 'type': 'FLOAT', 'uniques': 134}, 'nkillus': {'idxmin': 0.0, 'max': 1357.5, 'mean': 0.056274711585332829, 'min': 0.0, 'std': 6.3917231276824413, 'sum': 5195.0, 'type': 'FLOAT', 'uniques': 31}, 'nperpcap': {'idxmin': -99.0, 'max': 406.0, 'mean': -1.5723453507827003, 'min': -99.0, 'std': 13.099647483344807, 'sum': -137206.0, 'type': 'FLOAT', 'uniques': 51}, 'nperps': {'idxmin': -99.0, 'max': 25000.0, 'mean': -61.504437178888367, 'min': -99.0, 'std': 243.82422130303308, 'sum': -5267240.0, 'type': 'FLOAT', 'uniques': 114}, 'nreleased': {'idxmin': -99.0, 'max': 1201.0, 'mean': -27.788634959851759, 'min': -99.0, 'std': 58.524975920758529, 'sum': -224949.0, 'type': 'FLOAT', 'uniques': 156}, 'nwound': {'idxmin': 0.0, 'max': 5500.0, 'mean': 3.0899264932806019, 'min': 0.0, 'std': 22.722313053878182, 'sum': 440537.00000000198, 'type': 'FLOAT', 'uniques': 377}, 'nwoundte': {'idxmin': 0.0, 'max': 200.0, 'mean': 0.0815830526101603, 'min': 0.0, 'std': 1.3577059214074707, 'sum': 7217.0, 'type': 'FLOAT', 'uniques': 65}, 'nwoundus': {'idxmin': 0.0, 'max': 751.0, 'mean': 0.045586861599287466, 'min': 0.0, 'std': 3.4407299631033381, 'sum': 4197.0, 'type': 'FLOAT', 'uniques': 44}, 'propcomment': {'type': 'CATEGORY', 'uniques': 17459}, 'property': {'idxmin': -9, 'max': 1, 'mean': -0.43405072334345418, 'min': -9, 'std': 3.0319448640017441, 'sum': -68047, 'type': 'INT', 'uniques': 3}, 'propextent': {'equivalents': ['propextent_txt'], 'has_equivalent': True, 'idxmin': 1.0, 'max': 4.0, 'mean': 3.3021898069278817, 'min': 1.0, 'std': 0.49305319129649716, 'sum': 186085.0, 'type': 'FLOAT', 'uniques': 5}, 'propextent_txt': {'equivalents': ['propextent'], 'has_equivalent': True, 'type': 'CATEGORY', 'uniques': 5}, 'propvalue': {'idxmin': -99.0, 'max': 2700000000.0, 'mean': 249620.80636592614, 'min': -99.0, 'std': 17300755.721233137, 'sum': 7816126688.9298792, 'type': 'FLOAT', 'uniques': 605}, 'provstate': {'type': 'CATEGORY', 'uniques': 2510}, 'ransom': {'idxmin': -9.0, 'max': 1.0, 'mean': -0.14366377243914133, 'min': -9.0, 'std': 1.1937195833558845, 'sum': -10788.0, 'type': 'FLOAT', 'uniques': 4}, 'ransomamt': {'idxmin': -99.0, 'max': 1000000000.0, 'mean': 3320127.170334728, 'min': -99.0, 'std': 31876939.232123595, 'sum': 3967551968.5500002, 'type': 'FLOAT', 'uniques': 351}, 'ransomamtus': {'idxmin': -99.0, 'max': 132000000.0, 'mean': 545445.05267639901, 'min': -99.0, 'std': 6665966.884489282, 'sum': 224177916.65000001, 'type': 'FLOAT', 'uniques': 22}, 'ransomnote': {'type': 'CATEGORY', 'uniques': 297}, 'ransompaid': {'idxmin': -99.0, 'max': 41000000.0, 'mean': 431972.09743178176, 'min': -99.0, 'std': 2589892.7713035513, 'sum': 269118616.70000005, 'type': 'FLOAT', 'uniques': 123}, 'ransompaidus': {'idxmin': -99.0, 'max': 48000.0, 'mean': 305.19651741293535, 'min': -99.0, 'std': 3409.0276853216646, 'sum': 122689.0, 'type': 'FLOAT', 'uniques': 9}, 'region': {'equivalents': ['region_txt'], 'has_equivalent': True, 'idxmin': 1, 'max': 12, 'mean': 6.9700967009414949, 'min': 1, 'std': 2.9678026050631856, 'sum': 1092716, 'type': 'INT', 'uniques': 12}, 'region_txt': {'equivalents': ['region'], 'has_equivalent': True, 'type': 'CATEGORY', 'uniques': 12}, 'related': {'type': 'CATEGORY', 'uniques': 20030}, 'resolution': {'type': 'CATEGORY', 'uniques': 2658}, 'scite1': {'type': 'CATEGORY', 'uniques': 66823}, 'scite2': {'type': 'CATEGORY', 'uniques': 50240}, 'scite3': {'type': 'CATEGORY', 'uniques': 28555}, 'specificity': {'idxmin': 1, 'max': 5, 'mean': 1.4526318475237925, 'min': 1, 'std': 1.0169709073052788, 'sum': 227732, 'type': 'INT', 'uniques': 5}, 'success': {'idxmin': 0, 'max': 1, 'mean': 0.90361161431888348, 'min': 0, 'std': 0.29512407621110542, 'sum': 141661, 'type': 'INT', 'uniques': 2}, 'suicide': {'idxmin': 0, 'max': 1, 'mean': 0.030432730334498507, 'min': 0, 'std': 0.1717753401202016, 'sum': 4771, 'type': 'INT', 'uniques': 2}, 'summary': {'type': 'CATEGORY', 'uniques': 88704}, 'target1': {'type': 'CATEGORY', 'uniques': 79948}, 'target2': {'type': 'CATEGORY', 'uniques': 4563}, 'target3': {'type': 'CATEGORY', 'uniques': 632}, 'targsubtype1': {'equivalents': ['targsubtype1_txt'], 'has_equivalent': True, 'idxmin': 1.0, 'max': 111.0, 'mean': 46.654884703634174, 'min': 1.0, 'std': 31.10804746151652, 'sum': 6933709.0, 'type': 'FLOAT', 'uniques': 111}, 'targsubtype1_txt': {'equivalents': ['targsubtype1'], 'has_equivalent': True, 'type': 'CATEGORY', 'uniques': 111}, 'targsubtype2': {'equivalents': ['targsubtype2_txt'], 'has_equivalent': True, 'idxmin': 1.0, 'max': 111.0, 'mean': 54.622623686385644, 'min': 1.0, 'std': 25.830595023453668, 'sum': 462599.0, 'type': 'FLOAT', 'uniques': 104}, 'targsubtype2_txt': {'equivalents': ['targsubtype2'], 'has_equivalent': True, 'type': 'CATEGORY', 'uniques': 104}, 'targsubtype3': {'equivalents': ['targsubtype3_txt'], 'has_equivalent': True, 'idxmin': 1.0, 'max': 109.0, 'mean': 54.86279069767442, 'min': 1.0, 'std': 26.779003496982764, 'sum': 47182.0, 'type': 'FLOAT', 'uniques': 86}, 'targsubtype3_txt': {'equivalents': ['targsubtype3'], 'has_equivalent': True, 'type': 'CATEGORY', 'uniques': 86}, 'targtype1': {'equivalents': ['targtype1_txt'], 'has_equivalent': True, 'idxmin': 1, 'max': 22, 'mean': 8.3051118822238656, 'min': 1, 'std': 6.64251830538063, 'sum': 1302009, 'type': 'INT', 'uniques': 22}, 'targtype1_txt': {'equivalents': ['targtype1'], 'has_equivalent': True, 'type': 'CATEGORY', 'uniques': 22}, 'targtype2': {'equivalents': ['targtype2_txt'], 'has_equivalent': True, 'idxmin': 1.0, 'max': 22.0, 'mean': 10.117858345493321, 'min': 1.0, 'std': 5.7649110534432575, 'sum': 90140.0, 'type': 'FLOAT', 'uniques': 23}, 'targtype2_txt': {'equivalents': ['targtype2'], 'has_equivalent': True, 'type': 'CATEGORY', 'uniques': 23}, 'targtype3': {'equivalents': ['targtype3_txt'], 'has_equivalent': True, 'idxmin': 1.0, 'max': 22.0, 'mean': 9.7982832618025757, 'min': 1.0, 'std': 5.835194274069373, 'sum': 9132.0, 'type': 'FLOAT', 'uniques': 21}, 'targtype3_txt': {'equivalents': ['targtype3'], 'has_equivalent': True, 'type': 'CATEGORY', 'uniques': 21}, 'vicinity': {'idxmin': -9, 'max': 1, 'mean': 0.067422754063225579, 'min': -9, 'std': 0.28904050760340855, 'sum': 10570, 'type': 'INT', 'uniques': 3}, 'weapdetail': {'type': 'CATEGORY', 'uniques': 16988}, 'weapsubtype1': {'equivalents': ['weapsubtype1_txt'], 'has_equivalent': True, 'idxmin': 1.0, 'max': 29.0, 'mean': 10.949519317322579, 'min': 1.0, 'std': 6.4389857794042182, 'sum': 1520505.0, 'type': 'FLOAT', 'uniques': 29}, 'weapsubtype1_txt': {'equivalents': ['weapsubtype1'], 'has_equivalent': True, 'type': 'CATEGORY', 'uniques': 29}, 'weapsubtype2': {'equivalents': ['weapsubtype2_txt'], 'has_equivalent': True, 'idxmin': 1.0, 'max': 28.0, 'mean': 10.591715976331361, 'min': 1.0, 'std': 7.4922207854013534, 'sum': 98450.0, 'type': 'FLOAT', 'uniques': 27}, 'weapsubtype2_txt': {'equivalents': ['weapsubtype2'], 'has_equivalent': True, 'type': 'CATEGORY', 'uniques': 27}, 'weapsubtype3': {'equivalents': ['weapsubtype3_txt'], 'has_equivalent': True, 'idxmin': 1.0, 'max': 28.0, 'mean': 11.426493108728943, 'min': 1.0, 'std': 8.2059432409625419, 'sum': 14923.0, 'type': 'FLOAT', 'uniques': 23}, 'weapsubtype3_txt': {'equivalents': ['weapsubtype3'], 'has_equivalent': True, 'type': 'CATEGORY', 'uniques': 23}, 'weapsubtype4': {'equivalents': ['weapsubtype4_txt'], 'has_equivalent': True, 'idxmin': 2.0, 'max': 28.0, 'mean': 10.788732394366198, 'min': 2.0, 'std': 8.1467179946593848, 'sum': 766.0, 'type': 'FLOAT', 'uniques': 17}, 'weapsubtype4_txt': {'equivalents': ['weapsubtype4'], 'has_equivalent': True, 'type': 'CATEGORY', 'uniques': 17}, 'weaptype1': {'equivalents': ['weaptype1_txt'], 'has_equivalent': True, 'idxmin': 1, 'max': 13, 'mean': 6.4085869925752048, 'min': 1, 'std': 2.1307853828571552, 'sum': 1004687, 'type': 'INT', 'uniques': 12}, 'weaptype1_txt': {'equivalents': ['weaptype1'], 'has_equivalent': True, 'type': 'CATEGORY', 'uniques': 12}, 'weaptype2': {'equivalents': ['weaptype2_txt'], 'has_equivalent': True, 'idxmin': 1.0, 'max': 13.0, 'mean': 6.6269086718524921, 'min': 1.0, 'std': 2.0854659636748027, 'sum': 69006.0, 'type': 'FLOAT', 'uniques': 12}, 'weaptype2_txt': {'equivalents': ['weaptype2'], 'has_equivalent': True, 'type': 'CATEGORY', 'uniques': 12}, 'weaptype3': {'equivalents': ['weaptype3_txt'], 'has_equivalent': True, 'idxmin': 2.0, 'max': 13.0, 'mean': 6.8044692737430168, 'min': 2.0, 'std': 2.0977595110524638, 'sum': 9744.0, 'type': 'FLOAT', 'uniques': 11}, 'weaptype3_txt': {'equivalents': ['weaptype3'], 'has_equivalent': True, 'type': 'CATEGORY', 'uniques': 11}, 'weaptype4': {'equivalents': ['weaptype4_txt'], 'has_equivalent': True, 'idxmin': 5.0, 'max': 12.0, 'mean': 6.243243243243243, 'min': 5.0, 'std': 1.4971279427652517, 'sum': 462.0, 'type': 'FLOAT', 'uniques': 6}, 'weaptype4_txt': {'equivalents': ['weaptype4'], 'has_equivalent': True, 'type': 'CATEGORY', 'uniques': 6}}
terror.columns['nkill']
{'idxmin': 0.0, 'max': 1500.0, 'mean': 2.3592374870502684, 'min': 0.0, 'std': 11.42127034765741, 'sum': 348758.99999818002, 'type': 'FLOAT', 'uniques': 339}
terror.columns['country_txt']
{'equivalents': ['country'], 'has_equivalent': True, 'type': 'CATEGORY', 'uniques': 206}
terror.bar_groups(['region_txt']).plot.barh()
<matplotlib.axes._subplots.AxesSubplot at 0x7f1892bb47f0>
terror.bar_groups([('region_txt', ['North America', 'Middle East & North Africa'])]).plot.barh()
<matplotlib.axes._subplots.AxesSubplot at 0x7f1892be3390>
# If 'level = 1' we use column 1 ('arracktype1_txt') for the groups
terror.bar_groups(['region_txt', 'attacktype1_txt']).unstack(level=1).plot.barh(figsize=(20,30))
<matplotlib.axes._subplots.AxesSubplot at 0x7f188a84cc50>
# If 'level = 0' we use column 0 ('region_txt') for the groups
terror.bar_groups(['region_txt', 'attacktype1_txt']).unstack(level=0).plot.barh(figsize=(20,20))
<matplotlib.axes._subplots.AxesSubplot at 0x7f188a239e10>
terror.bar_groups([('region_txt', ['North America', 'Middle East & North Africa']), 'attacktype1_txt']).unstack(level=0).plot.barh()
<matplotlib.axes._subplots.AxesSubplot at 0x7f188a639eb8>
terror.bar_groups([('region_txt', ['North America', 'Middle East & North Africa']), 'attacktype1_txt']).unstack(level=1).plot.barh()
<matplotlib.axes._subplots.AxesSubplot at 0x7f188b66f5c0>
terror.bar_groups([('country_txt', 'Iraq'), 'attacktype1_txt']).unstack(level=0).plot.barh()
<matplotlib.axes._subplots.AxesSubplot at 0x7f1888a0f208>
terror.bar_groups([('country_txt', ['Iraq', 'United States']), 'attacktype1_txt']).unstack(level=0).plot.barh()
<matplotlib.axes._subplots.AxesSubplot at 0x7f18888e4400>
By default the bar graph is going to display the count of entries in a given category. If you pass a column name, it is going to use it for the weight of the bar.
terror.bar_groups([('country_txt', ['Iraq', 'United States'])], 'nkill').plot.barh()
<matplotlib.axes._subplots.AxesSubplot at 0x7f1888565b38>
The default is to sum the values in this column, if you want other types of aggregation, you can pass a argument 'aggs' with possible values as ['sum', 'count', 'mean', 'std']:
terror.bar_groups([('country_txt', ['Iraq', 'United States'])], 'nkill', aggs=['count', 'sum']).plot.barh()
<matplotlib.axes._subplots.AxesSubplot at 0x7f188867f400>