数据分析练习Ⅱ———图形化显示海地地震危机数据

          Ushahidi是一家非盈利软件公司,人们可以通过短信向其提供有关自然灾害和地缘政治事件的信息。这些数据会被发布在他们的网站上以提供分析和图形化。本节,利用2010年海底地震及其余震期间搜集的数据。

数据下载在       https://download.csdn.net/download/qq_21467113/10828284

 该练习为Python2代码，主要是Python3不支持Basemap。

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.basemap import Basemap

data = pd.read_csv('D:\programme\sqldata\Haiti.csv')
data = data[(data.LATITUDE>18)&(data.LATITUDE<20)&(data.LONGITUDE>-75)&(data.LONGITUDE<-70)&data.CATEGORY.notnull()]
def to_cat_list(catstr):
    stripped = (x.strip() for x in catstr.split(','))
    return [x for x in stripped if x]

def get_all_categories(cat_series):
    cat_sets = (set(to_cat_list(x)) for x in cat_series)
    return sorted(set.union(*cat_sets))

def get_english(cat):
    code,names = cat.split('.')
    if '|' in names:
        names = names.split('|')[1]
    return code,names.strip()

all_cats = get_all_categories(data.CATEGORY)
english_mapping = dict(get_english(x) for x in all_cats)

def get_code(seq):
    return [x.split('.')[0] for x in seq if x]

all_codes = get_code(all_cats)
code_index = pd.Index(np.unique(all_codes))
dummy_frame = pd.DataFrame(np.zeros((len(data), len(code_index))), index = data.index, columns = code_index)

for row,cat in zip(data.index,data.CATEGORY):
    codes = get_code(to_cat_list(cat))
    dummy_frame.ix[row,codes] = 1

data = data.join(dummy_frame.add_prefix('category_'))

def basic_haiti_map(ax=None,lllat=17.25,urlat=20.25,lllon=-75,urlon=-71):
    m = Basemap(ax=ax,projection='stere',lon_0=(urlon + lllon)/2,
                lat_0=(urlat + lllat)/2, llcrnrlat=lllat,
                urcrnrlat=urlat,llcrnrlon=lllon,urcrnrlon=urlon,
                resolution='f')
    m.drawcoastlines()
    m.drawstates()
    m.drawcountries()
    return m

fig,axes = plt.subplots(nrows=2,ncols=2,figsize=(12,10))
fig.subplots_adjust(hspace=0.05,wspace=0.05)

to_plot = ['2a','1','3c','7a']

lllat=17.25; urlat=20.25; lllon=-75; urlon=-71

for code,ax in zip(to_plot,axes.flat):
    m = basic_haiti_map(ax, lllat=lllat,urlat=urlat,
                        lllon=lllon, urlon=urlon)
    cat_data = data[data['category_%s' %code]==1]

    x,y = m(cat_data.LONGITUDE.values,cat_data.LATITUDE.values)

    m.plot(x,y, 'k.', alpha=0.5)
    ax.set_title('%s: %s' %(code,english_mapping[code]))

print("over!!")
plt.show()

处理结果为：