這裏是採用新浪疫情實時數據
最新數據是運行前一天(這裏是2月7號)
所有資料github地址：
以下是所有代碼：
from datetime import datetime
import numpy as np
import json, re
import requests
import matplotlib
import time
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
from matplotlib.font_manager import FontProperties
from matplotlib.patches import Polygon
from mpl_toolkits.basemap import Basemap
from matplotlib.backends.backend_agg import FigureCanvasAgg
plt.rcParams['font.sans-serif'] = ['FangSong'] # 設置默認字體
plt.rcParams['axes.unicode_minus'] = False # 解決保存圖像時'-'顯示爲方塊的問題
def get_daily_cn():
"""獲取全國每日數據"""
time_stamp = int(time.time()) * 1000
url = f'https://interface.sina.cn/news/wap/fymap2020_data.d.json?_={time_stamp}&callback='
resp = requests.get(url=url, )
resp_data = resp.content.decode("unicode_escape")
raw_data = json.loads(re.search("\(+([^)]*)\)+", resp_data).group(1)).get('data')['historylist']
# 處理數據
cn_conNum_list = list() # 確診
cn_deathNum_list = list() # 死亡
cn_cureNum_list = list() # 治癒
cn_susNum_list = list() # 疑似
date_list = list()
for item in raw_data:
month, day = item['date'].split('.')
date_list.append(datetime.strptime('2020-%s-%s' % (month, day), '%Y-%m-%d'))
cn_conNum_list.append(int(item.get('cn_conNum', 0)))
cn_deathNum_list.append(int(item.get('cn_deathNum', 0)))
cn_cureNum_list.append(int(item.get('cn_cureNum', 0)))
cn_susNum_list.append(item.get('cn_susNum', 0))
# 因爲新浪網數據有null值，這裏操作有點多
cn_susNum_list = [x for x in cn_susNum_list if x is not None]
for i in range(len(cn_conNum_list) - len(cn_susNum_list)):
cn_susNum_list.append(1)
cn_susNum_list = [int(x) for x in cn_susNum_list]
return cn_conNum_list, cn_deathNum_list, cn_susNum_list, cn_cureNum_list, date_list
def plot_date():
"""繪製全國每日疫情數據折線圖"""
cn_conNum_list, cn_deathNum_list, cn_susNum_list, cn_cureNum_list, date_list = get_daily_cn()
plt.figure('2019-nCoV疫情統計圖表', facecolor='#f4f4f4', figsize=(10, 8))
plt.title('2019-nCoV疫情折線圖', fontsize=20)
plt.plot(date_list, cn_conNum_list, label='確診')
plt.plot(date_list, cn_susNum_list, label='疑似')
plt.plot(date_list, cn_deathNum_list, label='死亡')
plt.plot(date_list, cn_cureNum_list, label='治癒')
ax = plt.gca().xaxis
ax.set_major_formatter(mdates.DateFormatter('%Y/%m/%d')) # 格式化時間軸標註
ax.set_major_locator(matplotlib.dates.DayLocator(bymonthday=None, interval=1, tz=None))
plt.gcf().autofmt_xdate() # 優化標註（自動傾斜）
plt.grid(linestyle=':') # 顯示網格
plt.xlabel('日期', fontsize=16)
plt.ylabel('人數', fontsize=16)
plt.legend(loc='best')
plt.savefig('2019-nCoV.png')
plt.show()
def china_value():
"""繪製全國每日疫情數據全國地圖"""
time_stamp = int(time.time()) * 1000
url = f'https://interface.sina.cn/news/wap/fymap2020_data.d.json?_={time_stamp}&callback='
resp = requests.get(url=url, )
resp_data = resp.content.decode("unicode_escape")
raw_data = json.loads(re.search("\(+([^)]*)\)+", resp_data).group(1)).get('data')['list']
# 處理數據，獲取每個省份確診數據
china_all = list()
city_value = {}
for item in raw_data:
city = item.get('name')
value = item.get('value')
city_value[city] = int(value)
china_all.append(city_value)
return city_value
def plot_distribution():
"""繪製行政區域確診分佈數據"""
china_data = china_value()
print(china_data)
# 經緯度範圍
lat_min = 10 # 緯度
lat_max = 60
lon_min = 70 # 經度
lon_max = 140
font = FontProperties(fname='simsun/simsun.ttf', size=14)
# 標籤顏色和文本
legend_handles = [
matplotlib.patches.Patch(color='#7FFFAA', alpha=1, linewidth=0),
matplotlib.patches.Patch(color='#ffaa85', alpha=1, linewidth=0),
matplotlib.patches.Patch(color='#ff7b69', alpha=1, linewidth=0),
matplotlib.patches.Patch(color='#bf2121', alpha=1, linewidth=0),
matplotlib.patches.Patch(color='#7f1818', alpha=1, linewidth=0),
]
legend_labels = ['0人', '1-10人', '11-100人', '101-1000人', '>1000人']
fig = plt.figure(facecolor='#f4f4f4', figsize=(10, 8))
# 新建區域
axes = fig.add_axes(
(0.1, 0.1, 0.8, 0.8)) # left, bottom, width, height, figure的百分比,從figure 10%的位置開始繪製, 寬高是figure的80%
axes.set_title('全國新型冠狀病毒疫情地圖（確診）', fontsize=20) # fontproperties=font 設置失敗
# bbox_to_anchor(num1, num2), num1用於控制legend的左右移動，值越大越向右邊移動，num2用於控制legend的上下移動，值越大，越向上移動。
axes.legend(legend_handles, legend_labels, bbox_to_anchor=(0.5, -0.11), loc='lower center', ncol=5) # prop=font
china_map = Basemap(llcrnrlon=lon_min, urcrnrlon=lon_max, llcrnrlat=lat_min, urcrnrlat=lat_max, resolution='l',
ax=axes)
# labels=[True,False,False,False] 分別代表 [left,right,top,bottom]
china_map.drawparallels(np.arange(lat_min, lat_max, 10), labels=[1, 0, 0, 0]) # 畫經度線
china_map.drawmeridians(np.arange(lon_min, lon_max, 10), labels=[0, 0, 0, 1]) # 畫緯度線
china_map.drawcoastlines(color='black') # 洲際線
china_map.drawcountries(color='red') # 國界線
china_map.drawmapboundary(fill_color='aqua')
# 畫中國國內省界和九段線
china_map.readshapefile('china-shapefiles-master/china', 'province', drawbounds=True)
china_map.readshapefile('china-shapefiles-master/china_nine_dotted_line', 'section', drawbounds=True)
global count_iter
count_iter = 0
# 內外循環不能對調，地圖中每個省的數據有多條(繪製每一個shape，可以去查一下第一條“臺灣省”的數據)
for info, shape in zip(china_map.province_info, china_map.province):
pname = info['OWNER'].strip('\x00')
fcname = info['FCNAME'].strip('\x00')
if pname != fcname: # 不繪製海島
continue
is_reported = False # 西藏沒有疫情，數據源就不取不到其數據
for prov_name in china_data.keys():
count_iter += 1
if prov_name in pname:
is_reported = True
if china_data[prov_name] == 0:
color = '#f0f0f0'
elif china_data[prov_name] <= 10:
color = '#ffaa85'
elif china_data[prov_name] <= 100:
color = '#ff7b69'
elif china_data[prov_name] <= 1000:
color = '#bf2121'
else:
color = '#7f1818'
break
if not is_reported:
color = '#7FFFAA'
poly = Polygon(shape, facecolor=color, edgecolor=color)
axes.add_patch(poly)
axes.legend(legend_handles, legend_labels, bbox_to_anchor=(0.5, -0.11), loc='lower center', ncol=4, prop=font)
axes.set_title("2019-nCoV疫情地圖", fontproperties=font)
FigureCanvasAgg(fig)
fig.savefig('2019-nCoV疫情地圖.png')
if __name__ == '__main__':
plot_date()
plot_distribution()
參考文章：
蒜泥的冬天和天元浪子兩位大神，多謝
讀到這兒了，有興趣的可以添加下我的微信公衆號
