import matplotlib.pyplot as plt import matplotlib.dates as mdates from matplotlib.font_manager import FontProperties from mpl_toolkits.basemap import Basemap from matplotlib.patches import Polygon import numpy as np import jsonpath plt.rcParams[ ' font.sans-serif ' ] = [ ' SimHei ' ] # 用来正常显示中文标签 plt.rcParams[ ' axes.unicode_minus ' ] = False # 用来正常显示负号 # 全国疫情地区分布(省级确诊病例) def catch_cn_disease_dis(): timestamp = ' %d ' %int(time.time()*1000 ) url_area = ( ' https://view.inews.qq.com/g2/getOnsInfo?name=disease_h5 ' ' &callback=&_= ' ) + timestamp world_data = json.loads(requests.get(url=url_area).json()[ ' data ' ]) china_data = jsonpath.jsonpath(world_data, expr = ' $.areaTree[0].children[*] ' ) list_province = jsonpath.jsonpath(china_data, expr= ' $[*].name ' ) list_province_confirm = jsonpath.jsonpath(china_data, expr= ' $[*].total.confirm ' ) dic_province_confirm = dict(zip(list_province, list_province_confirm)) return dic_province_confirm area_data = catch_cn_disease_dis() print (area_data) # 抓取全国疫情按日期分布 "chinaDayList": [{ "date": "01.13", "confirm": "41", "suspect": "0", "dead": "1", "heal": "0" "date": "01.14", "confirm": "41", "suspect": "0", "dead": "1", "heal": "0" def catch_cn_daily_dis(): timestamp = ' %d ' %int(time.time()*1000 ) url_area = ( ' https://view.inews.qq.com/g2/getOnsInfo?name=disease_h5 ' ' &callback=&_= ' ) + timestamp world_data = json.loads(requests.get(url=url_area).json()[ ' data ' ]) china_daily_data = jsonpath.jsonpath(world_data, expr = ' $.chinaDayList[*] ' ) # 其实没必要单独用list存储，json可读性已经很好了；这里这样写仅是为了少该点老版本的代码 list_dates = list() # 日期 list_confirms = list() # 确诊 list_suspects = list() # 疑似 list_deads = list() # 死亡 list_heals = list() # 治愈 for item in china_daily_data: month, day = item[ ' date ' ].split( ' . ' ) list_dates.append(datetime.strptime( ' 2020-%s-%s ' %(month, day), ' %Y-%m-%d ' )) list_confirms.append(int(item[ ' confirm ' ])) list_suspects.append(int(item[ ' suspect ' ])) list_deads.append(int(item[ ' dead ' ])) list_heals.append(int(item[ ' heal ' ])) return list_dates, list_confirms, list_suspects, list_deads, list_heals list_date, list_confirm, list_suspect, list_dead, list_heal = catch_cn_daily_dis() print (list_date) # 绘制每日确诊和死亡数据 def plot_cn_daily(): # list_date, list_confirm, list_suspect, list_dead, list_heal = catch_cn_daily_dis() plt.figure( ' novel coronavirus ' , facecolor= ' #f4f4f4 ' , figsize=(10, 8 )) plt.title( ' 全国新型冠状病毒疫情曲线 ' , fontsize=20 ) print ( ' 日期元素数： ' , len(list_date), " \n确诊元素数： " , len(list_confirm)) plt.plot(list_date, list_confirm, label = ' 确诊 ' ) plt.plot(list_date, list_suspect, label = ' 疑似 ' ) plt.plot(list_date, list_dead, label = ' 死亡 ' ) plt.plot(list_date, list_heal, label = ' 治愈 ' ) xaxis = plt.gca().xaxis # x轴刻度为1天 xaxis.set_major_locator(matplotlib.dates.DayLocator(bymonthday=None, interval=1, tz= None)) xaxis.set_major_formatter(mdates.DateFormatter( ' %m月%d日 ' )) plt.gcf().autofmt_xdate() # 优化标注（自动倾斜） plt.grid(linestyle= ' : ' ) # 显示网格 plt.xlabel( ' 日期 ' ,fontsize=16 ) plt.ylabel( ' 人数 ' ,fontsize=16 ) plt.legend(loc = ' best ' ) plot_cn_daily() # 绘制全国省级行政区域确诊分布图 count_iter = 0 def plot_cn_disease_dis(): # area_data = catch_area_distribution() font = FontProperties(fname= ' res/coure.fon ' , size=14 ) # 经纬度范围 lat_min = 10 # 纬度 lat_max = 60 lon_min = 70 # 经度 lon_max = 140 # 标签颜色和文本 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 )) # 新建区域 axes = fig.add_axes((0.1, 0.1, 0.8, 0.8)) # left, bottom, width, height, figure的百分比,从figure 10%的位置开始绘制, 宽高是figure的80% axes.set_title( ' 全国新型冠状病毒疫情地图（确诊） ' , fontsize=20) # fontproperties=font 设置失败 # bbox_to_anchor(num1, num2), num1用于控制legend的左右移动，值越大越向右边移动，num2用于控制legend的上下移动，值越大，越向上移动。 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] 分别代表 [left,right,top,bottom] china_map.drawparallels(np.arange(lat_min,lat_max,10), labels=[1,0,0,0]) # 画经度线 china_map.drawmeridians(np.arange(lon_min,lon_max,10), labels=[0,0,0,1]) # 画纬度线 china_map.drawcoastlines(color= ' black ' ) # 洲际线 china_map.drawcountries(color= ' red ' ) # 国界线 china_map.drawmapboundary(fill_color = ' aqua ' ) # 画中国国内省界和九段线 china_map.readshapefile( ' res/china-shapefiles-master/china ' , ' province ' , drawbounds= True) china_map.readshapefile( ' res/china-shapefiles-master/china_nine_dotted_line ' , ' section ' , drawbounds= True) global count_iter count_iter = 0 # 内外循环不能对调，地图中每个省的数据有多条(绘制每一个shape，可以去查一下第一条“台湾省”的数据) 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: # 不绘制海岛 continue is_reported = False # 西藏没有疫情，数据源就不取不到其数据 for prov_name in area_data.keys(): count_iter += 1 if prov_name in pname: is_reported = True if area_data[prov_name] == 0: color = ' #f0f0f0 ' elif area_data[prov_name] <= 10 : color = ' #ffaa85 ' elif area_data[prov_name] <= 100 : color = ' #ff7b69 ' elif area_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) plot_cn_disease_dis() print ( ' 迭代次数 ' , count_iter) example

在这份代码中，先就是import各种库，在mpl_toolkits.basemap上费了不少功夫，解决方案就是basemap的安装参考这位博主的操作（https://blog.csdn.net/moxigandashu/article/details/68945845）。即在 http://www.lfd.uci.edu/%7Egohlke/pythonlibs/ 下载basemap和pyproj两个库（注意在下载的时候要看whl的cp版本，我是python3.7，就只能安装cp37以下的版本）安装完成之后可能会遇见奇奇怪怪的版本问题，我遇见了

ModuleNotFoundError: No module named 'numpy.core._multiarray_umath'
Traceback (most recent call last):

File "<ipython-input-1-4fc84cbcc854>", line 2, in <module>
from mpl_toolkits.basemap import Basemap

File "D:\anaconda3\lib\site-packages\mpl_toolkits\basemap\__init__.py", line 45, in <module>
import _geoslib

SystemError: execution of module _geoslib raised unreported exception

我用pip install --user --upgrade numpy解决了

但是又遇见了：

ModuleNotFoundError: No module named 'mpl_toolkits.basemap'
conda install basemap//等一会输入y,解决上述问题

KeyError:'PROJ_LIB'

1）找到“epsg”的相应位置，复制文件所在路径（例如我的电脑中“epsg”的位置为C:\ProgramData\Anaconda3\Library\share）
2）设置系统环境变量PROJ_LIB

ModuleNotFoundError: No module named 'jsonpath'

pip install jsonpath

'bool' object is not iterable