matplotlib 报错，求大佬解决办法

[菲其弥章]

报错信息：
MatplotlibDeprecationWarning:
The dedent function was deprecated in Matplotlib 3.1 and will be removed in 3.3. Use inspect.cleandoc instead.
m = Basemap(llcrnrlon=lon_min, urcrnrlon=lon_max, llcrnrlat=lat_min, urcrnrlat=lat_max, resolution='l', ax=axes)
Traceback (most recent call last):
File "wuhan.py", line 135, in <module>
plot_distribution()
File "wuhan.py", line 98, in plot_distribution
m.readshapefile('res/china-shapefiles-master/china', 'province', drawbounds=True)
File "/usr/local/lib/python3.6/dist-packages/mpl_toolkits/basemap/__init__.py", line 2124, in readshapefile
raise IOError('cannot locate %s.shp'%shapefile)
OSError: cannot locate res/china-shapefiles-master/china.shp
/home/james/.local/lib/python3.6/site-packages/matplotlib/backends/backend_gtk3.py:197: Warning: Source ID 8 was not found when attempting to remove it
GLib.source_remove(self._idle_draw_id)

[冰风漫天]

res/china-shapefiles-master/china.shp 这个文件有吗？

[菲其弥章]

没有啊，还有后面的报错Warning: Source ID 8 was not found when attempting to remove it
GLib.source_remove(self._idle_draw_id)也没弄明白

[冰风漫天]

可以发完整的代码吗？

[菲其弥章]

import time
import json
import requests
from datetime import datetime
import numpy as np
import matplotlib
import matplotlib.figure
from matplotlib.font_manager import FontProperties
from matplotlib.backends.backend_agg import FigureCanvasAgg
from matplotlib.patches import Polygon
from matplotlib.collections import PatchCollection
from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt
import matplotlib.dates as mdates

plt.rcParams['font.sans-serif'] = ['FangSong'] # 设置默认字体
plt.rcParams['axes.unicode_minus'] = False # 解决保存图像时'-'显示为方块的问题

def catch_daily():
"""抓取每日确诊和死亡数据"""

url = 'https://view.inews.qq.com/g2/getOnsInfo?name=wuwei_ww_cn_day_counts&callback=&_=%d'%int(time.time()*1000)
data = json.loads(requests.get(url=url).json()['data'])
data.sort(key=lambda x:x['date'])

date_list = list() # 日期
confirm_list = list() # 确诊
suspect_list = list() # 疑似
dead_list = list() # 死亡
heal_list = list() # 治愈
for item in data:
month, day = item['date'].split('.')
date_list.append(datetime.strptime('2020-%s-%s'%(month, day), '%Y-%m-%d'))
confirm_list.append(int(item['confirm']))
suspect_list.append(int(item['suspect']))
dead_list.append(int(item['dead']))
heal_list.append(int(item['heal']))

return date_list, confirm_list, suspect_list, dead_list, heal_list

def catch_distribution():
"""抓取行政区域确诊分布数据"""

data = {'西藏':0}
url = 'https://view.inews.qq.com/g2/getOnsInfo?name=wuwei_ww_area_counts&callback=&_=%d'%int(time.time()*1000)
for item in json.loads(requests.get(url=url).json()['data']):
if item['area'] not in data:
data.update({item['area']:0})
data[item['area']] += int(item['confirm'])

return data

def plot_daily():
"""绘制每日确诊和死亡数据"""

date_list, confirm_list, suspect_list, dead_list, heal_list = catch_daily() # 获取数据

plt.figure('2019-nCoV疫情统计图表', facecolor='#f4f4f4', figsize=(10, 8))
plt.title('2019-nCoV疫情曲线', fontsize=20)

plt.plot(date_list, confirm_list, label='确诊')
plt.plot(date_list, suspect_list, label='疑似')
plt.plot(date_list, dead_list, label='死亡')
plt.plot(date_list, heal_list, label='治愈')

plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%m-%d')) # 格式化时间轴标注
plt.gcf().autofmt_xdate() # 优化标注（自动倾斜）
plt.grid(linestyle=':') # 显示网格
plt.legend(loc='best') # 显示图例
plt.savefig('2019-nCoV疫情曲线.png') # 保存为文件
#plt.show()

def plot_distribution():
"""绘制行政区域确诊分布数据"""

data = catch_distribution()

font = FontProperties(fname='res/simsun.ttf', size=14)
lat_min = 0
lat_max = 60
lon_min = 70
lon_max = 140

handles = [
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),
]
labels = [ '1-9人', '10-99人', '100-999人', '>1000人']

fig = matplotlib.figure.Figure()
fig.set_size_inches(10, 8) # 设置绘图板尺寸
axes = fig.add_axes((0.1, 0.12, 0.8, 0.8)) # rect = l,b,w,h
m = Basemap(llcrnrlon=lon_min, urcrnrlon=lon_max, llcrnrlat=lat_min, urcrnrlat=lat_max, resolution='l', ax=axes)
m.readshapefile('res/china-shapefiles-master/china', 'province', drawbounds=True)
m.readshapefile('res/china-shapefiles-master/china_nine_dotted_line', 'section', drawbounds=True)
m.drawcoastlines(color='black') # 洲际线
m.drawcountries(color='black') # 国界线
m.drawparallels(np.arange(lat_min,lat_max,10), labels=[1,0,0,0]) #画经度线
m.drawmeridians(np.arange(lon_min,lon_max,10), labels=[0,0,0,1]) #画纬度线

for info, shape in zip(m.province_info, m.province):
pname = info['OWNER'].strip('\x00')
fcname = info['FCNAME'].strip('\x00')
if pname != fcname: # 不绘制海岛
continue

for key in data.keys():
if key in pname:
if data[key] == 0:
color = '#f0f0f0'
elif data[key] < 10:
color = '#ffaa85'
elif data[key] <100:
color = '#ff7b69'
elif data[key] < 1000:
color = '#bf2121'
else:
color = '#7f1818'
break

poly = Polygon(shape, facecolor=color, edgecolor=color)
axes.add_patch(poly)

axes.legend(handles, labels, bbox_to_anchor=(0.5, -0.11), loc='lower center', ncol=4, prop=font)
axes.set_title("2019-nCoV疫情地图", fontproperties=font)
FigureCanvasAgg(fig)
fig.savefig('2019-nCoV疫情地图.png')

if __name__ == '__main__':
plot_daily()
plot_distribution()

[菲其弥章]

res/china-shapefiles-master/china.shp 文件可以从https://gitee.com/masterkeze/china-shapefiles下载

[菲其弥章]

https://github.com/dongli/china-shapefiles　我从这个网下载的

[冰风漫天]

我下了你前面给我的那个，基本上可以跑通的

import time
import json
import requests
from datetime import datetime
import numpy as np
import matplotlib
import matplotlib.figure
from matplotlib.font_manager import FontProperties
from matplotlib.backends.backend_agg import FigureCanvasAgg
from matplotlib.patches import Polygon
from matplotlib.collections import PatchCollection
from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt
import matplotlib.dates as mdates

plt.rcParams['font.sans-serif'] = ['FangSong']  # 设置默认字体
plt.rcParams['axes.unicode_minus'] = False  # 解决保存图像时'-'显示为方块的问题


def catch_daily():
    """抓取每日确诊和死亡数据"""

    url = 'https://view.inews.qq.com/g2/getOnsInfo?name=wuwei_ww_cn_day_counts&callback=&_=%d' % int(time.time() * 1000)
    data = json.loads(requests.get(url=url).json()['data'])
    data.sort(key=lambda x: x['date'])

    date_list = list()  # 日期
    confirm_list = list()  # 确诊
    suspect_list = list()  # 疑似
    dead_list = list()  # 死亡
    heal_list = list()  # 治愈
    for item in data:
        month, day = item['date'].split('.')
        date_list.append(datetime.strptime('2020-%s-%s' % (month, day), '%Y-%m-%d'))
        confirm_list.append(int(item['confirm']))
        suspect_list.append(int(item['suspect']))
        dead_list.append(int(item['dead']))
        heal_list.append(int(item['heal']))

    return date_list, confirm_list, suspect_list, dead_list, heal_list


def catch_distribution():
    """抓取行政区域确诊分布数据"""

    data = {'西藏': 0}
    url = 'https://view.inews.qq.com/g2/getOnsInfo?name=wuwei_ww_area_counts&callback=&_=%d' % int(time.time() * 1000)
    for item in json.loads(requests.get(url=url).json()['data']):
        if item['area'] not in data:
            data.update({item['area']: 0})
        data[item['area']] += int(item['confirm'])

    return data


def plot_daily():
    """绘制每日确诊和死亡数据"""

    date_list, confirm_list, suspect_list, dead_list, heal_list = catch_daily()  # 获取数据

    plt.figure('2019-nCoV疫情统计图表', facecolor='#f4f4f4', figsize=(10, 8))
    plt.title('2019-nCoV疫情曲线', fontsize=20)

    plt.plot(date_list, confirm_list, label='确诊')
    plt.plot(date_list, suspect_list, label='疑似')
    plt.plot(date_list, dead_list, label='死亡')
    plt.plot(date_list, heal_list, label='治愈')

    plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%m-%d'))  # 格式化时间轴标注
    plt.gcf().autofmt_xdate()  # 优化标注（自动倾斜）
    plt.grid(linestyle=':')  # 显示网格
    plt.legend(loc='best')  # 显示图例
    plt.savefig('2019-nCoV疫情曲线.png')  # 保存为文件
    # plt.show()


def plot_distribution():
    """绘制行政区域确诊分布数据"""

    data = catch_distribution()

    # font = FontProperties(fname='res/simsun.ttf', size=14)
    lat_min = 0
    lat_max = 60
    lon_min = 70
    lon_max = 140

    handles = [
        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),
    ]
    labels = ['1-9人', '10-99人', '100-999人', '>1000人']

    fig = matplotlib.figure.Figure()
    fig.set_size_inches(10, 8)  # 设置绘图板尺寸
    axes = fig.add_axes((0.1, 0.12, 0.8, 0.8))  # rect = l,b,w,h
    m = Basemap(llcrnrlon=lon_min, urcrnrlon=lon_max, llcrnrlat=lat_min, urcrnrlat=lat_max, resolution='l', ax=axes)
    m.readshapefile('res/china-shapefiles/china_prov', 'province', drawbounds=True)
    # m.readshapefile('res/china-shapefiles/ne_10m_coastline', 'ne_10m_coastline', drawbounds=True)
    m.drawcoastlines(color='black')  # 洲际线
    m.drawcountries(color='black')  # 国界线
    m.drawparallels(np.arange(lat_min, lat_max, 10), labels=[1, 0, 0, 0])  # 画经度线
    m.drawmeridians(np.arange(lon_min, lon_max, 10), labels=[0, 0, 0, 1])  # 画纬度线

    for info, shape in zip(m.province_info, m.province):
        pname = info['name'].strip('\x00')
        # fcname = info['FCNAME'].strip('\x00')
        # if pname != fcname:  # 不绘制海岛
        #     continue

        for key in data.keys():
            if key in pname:
                if data[key] == 0:
                    color = '#f0f0f0'
                elif data[key] < 10:
                    color = '#ffaa85'
                elif data[key] < 100:
                    color = '#ff7b69'
                elif data[key] < 1000:
                    color = '#bf2121'
                else:
                    color = '#7f1818'
                break

        poly = Polygon(shape, facecolor=color, edgecolor=color)
        axes.add_patch(poly)

    axes.legend(handles, labels, bbox_to_anchor=(0.5, -0.11), loc='lower center', ncol=4)
    axes.set_title("2019-nCoV疫情地图")
    FigureCanvasAgg(fig)
    fig.savefig('2019-nCoV疫情地图.png')


if __name__ == '__main__':
    plot_daily()
    plot_distribution()

[菲其弥章]

还是你厉害，我搭建环境有问题，重装下ｍａｔｐｌｏｔｌｉｂ试试

[冰风漫天]

引用 6 楼 weixin_43689590 的回复:

https://github.com/dongli/china-shapefiles　我从这个网下载的

下了你说的这个地图，用这个地图，你的程序直接可以跑出结果，你看下是不是把python版本升到3.7.6

[冰风漫天]

我这边几个包的版本是这样的 matplotlib==3.1.2 pyproj==1.9.6 basemap==1.2.0