import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
import seaborn as sns
import numpy as np
plt.style.use('fivethirtyeight')
import plotly.offline as py
py.init_notebook_mode(connected=True)
import plotly.graph_objs as go
import plotly.tools as tls
from mpl_toolkits.basemap import Basemap
#https://www.lfd.uci.edu/~gohlke/pythonlibs/#basemap
import folium
import folium.plugins
from matplotlib import animation,rc
import io
import base64
from IPython.display import HTML, display
import warnings
warnings.filterwarnings('ignore')
from scipy.misc import imread
import codecs
terror=pd.read_csv('globalterrorismdb_0617dist.csv',encoding='ISO-8859-1')
terror.rename(columns={'iyear':'Year','imonth':'Month','iday':'Day','country_txt':'Country','region_txt':'Region','attacktype1_txt':'AttackType','target1':'Target','nkill':'Killed','nwound':'Wounded','summary':'Summary','gname':'Group','targtype1_txt':'Target_type','weaptype1_txt':'Weapon_type','motive':'Motive'},inplace=True)
terror=terror[['Year','Month','Day','Country','Region','city','latitude','longitude','AttackType','Killed','Wounded','Target','Summary','Group','Target_type','Weapon_type','Motive']]
terror['casualities']=terror['Killed']+terror['Wounded']
terror.head(3)
terror.describe()
print('Country with Highest Terrorist Attacks:',terror['Country'].value_counts().index[0])
print('Regions with Highest Terrorist Attacks:',terror['Region'].value_counts().index[0])
print('Maximum people killed in an attack are:',terror['Killed'].max(),'that took place in',terror.loc[terror['Killed'].idxmax()].Country)
plt.subplots(figsize=(15,6))
sns.countplot('Year',data=terror,palette='RdYlGn_r',edgecolor=sns.color_palette('dark',7))
plt.xticks(rotation=90)
plt.title('Number Of Terrorist Activities Each Year')
plt.show()
plt.subplots(figsize=(15,6))
sns.countplot('AttackType',data=terror,palette='inferno',order=terror['AttackType'].value_counts().index)
plt.xticks(rotation=90)
plt.title('Attacking Methods by Terrorists')
plt.show()
#炸弹 武装袭击 暗杀 人质 基础设施袭击
plt.subplots(figsize=(15,6))
sns.countplot(terror['Target_type'],palette='inferno',order=terror['Target_type'].value_counts().index)
plt.xticks(rotation=90)
plt.title('Favorite Targets')
plt.show()
m3 = Basemap(projection='mill',llcrnrlat=-80,urcrnrlat=80, llcrnrlon=-180,urcrnrlon=180,lat_ts=20,resolution='c',lat_0=True,lat_1=True)
lat_100=list(terror[terror['casualities']>=75].latitude)
long_100=list(terror[terror['casualities']>=75].longitude)
x_100,y_100=m3(long_100,lat_100)
m3.plot(x_100, y_100,'go',markersize=5,color = 'r')
lat_=list(terror[terror['casualities']<75].latitude)
long_=list(terror[terror['casualities']<75].longitude)
x_,y_=m3(long_,lat_)
m3.plot(x_, y_,'go',markersize=2,color = 'b',alpha=0.4)
m3.drawcoastlines()
m3.drawcountries()
m3.fillcontinents(lake_color='aqua')
m3.drawmapboundary(fill_color='aqua')
fig=plt.gcf()
fig.set_size_inches(10,6)
plt.title('Global Terrorist Attacks')
plt.legend(loc='lower left',handles=[mpatches.Patch(color='b', label = "< 75 casualities"),
mpatches.Patch(color='red',label='> 75 casualities')])
plt.show()
terror_region=pd.crosstab(terror.Year,terror.Region)
terror_region.plot(color=sns.color_palette('Set2',12))
fig=plt.gcf()
fig.set_size_inches(18,6)
plt.show()
top_groups10=terror[terror['Group'].isin(terror['Group'].value_counts()[1:11].index)]
pd.crosstab(top_groups10.Year,top_groups10.Group).plot(color=sns.color_palette('Paired',10))
fig=plt.gcf()
fig.set_size_inches(18,6)
plt.show()
top_groups=terror[terror['Group'].isin(terror['Group'].value_counts()[:14].index)]
m4 = Basemap(projection='mill',llcrnrlat=-80,urcrnrlat=80, llcrnrlon=-180,urcrnrlon=180,lat_ts=20,resolution='c',lat_0=True,lat_1=True)
m4.drawcoastlines()
m4.drawcountries()
m4.fillcontinents(lake_color='aqua')
m4.drawmapboundary(fill_color='aqua')
fig=plt.gcf()
fig.set_size_inches(22,10)
colors=['r','g','b','y','#800000','#ff1100','#8202fa','#20fad9','#ff5733','#fa02c6',"#f99504",'#b3b6b7','#8e44ad','#1a2b3c']
group=list(top_groups['Group'].unique())
def group_point(group,color,label):
lat_group=list(top_groups[top_groups['Group']==group].latitude)
long_group=list(top_groups[top_groups['Group']==group].longitude)
x_group,y_group=m4(long_group,lat_group)
m4.plot(x_group,y_group,'go',markersize=3,color=j,label=i)
for i,j in zip(group,colors):
group_point(i,j,i)
legend=plt.legend(loc='lower left',frameon=True,prop={'size':10})
frame=legend.get_frame()
frame.set_facecolor('white')
plt.title('Regional Activities of Terrorist Groups')
plt.show()