数据可视化训练第7天（json文件读取国家人口数据，找出前10和后10）

数据

https://restcountries.com/v3.1/all；建议下载下来，并不是很大

import numpy as np
import matplotlib.pyplot as plt
import requests
import json
#由于访问url过于慢；将数据下载到本地是json数据
#url='https://restcountries.com/v3.1/all'#r=requests.get(url)
#r.json()获得文件数据
#statuscode判断是否成功访问filename='/Users/oommnn/Desktop/学习笔记/数据可视化30天项目/all.json'try:with open(filename) as f:data=json.load(f)except FileNotFoundError:print(f"{filename}找不到")#这是姓名的数组print(data[0]['name'])
#这是人口的消息print(data[0]['population'])results=[]
#250个国家print(len(data))
for i in range(len(data)):result={'name':data[i]['name']['common'],'population':int(data[i]['population'])}results.append(result)
print(results[:2])arr_results=np.array(results)
#列表的排序
results=sorted(results,key=lambda x: x['population'],reverse=True)
#np数组的排序;没有直接的方法#可视化过程；使用matplotlib
x_values=[result['name'] for result in results]
y_values=[result['population'] for result in results]fig,axs=plt.subplot_mosaic([['left_top','left_top'],['left_bottom','left_bottom']],figsize=(20,15),facecolor='gray')axs['left_top'].bar(x_values[:10],y_values[:10])
axs['left_top'].set_title("Max Population about country")
axs['left_top'].set_xlabel('Country')
axs['left_top'].set_ylabel('Number/a hundred million')
axs['left_top'].set_xticks(x_values[:10],x_values[:10],rotation=45,fontsize=13)axs['left_bottom'].bar(x_values[-10:],y_values[-10:])
axs['left_bottom'].set_title("Min Population about country")
axs['left_bottom'].set_xlabel('Country')
axs['left_bottom'].set_ylabel('Number/people')
axs['left_bottom'].set_xticks(x_values[-10:],x_values[-10:],rotation=45,fontsize=13)plt.show()