一、颜色

二、实例

#读者分布
import pandas as pd
import matplotlib.pyplot as plt
def age_pie():
 plt.rcParams['font.family'] = 'SimHei'
 df = pd.read_csv("user.csv", sep=";", header=None, names=["user_id", "location", "age"],
 encoding='gbk')
 # print(df.head())
 df[(df.age == '41"')].index.tolist() # 找出不合法数值所在行
 df = df.drop([1305]) # 删除那一行
 df[['age']] = df[['age']].astype(float)
 labels = ['10-20', '20-30', '30-40', '40-50', '50-60']
 sizes = [len(df[(df.age >= 10) & (df.age < 20)]), \
 len(df[(df.age >= 20) & (df.age < 30)]), \
 len(df[(df.age >= 30) & (df.age < 40)]), \
 len(df[(df.age >= 40) & (df.age < 50)]), \
 len(df[(df.age >= 50) & (df.age < 60)])]
 # print(sizes)
 explode = (0, 0.05, 0, 0, 0) # 0.1为第二个元素凸出距离
 colors = ['tomato', 'lightskyblue', 'goldenrod', 'green', 'y']
 # 饼图绘制函数
 plt.figure(figsize=(8, 6))
 plt.pie(sizes, explode=explode, labels=labels, colors=colors, \
 autopct='%1.1f%%', shadow=False, pctdistance=0.8, \
 startangle=90, textprops={'fontsize': 16, 'color': 'w'})
 plt.title('读者年龄分布图')
 plt.axis('equal')
 plt.legend(loc='upper right')
 plt.savefig('age.png', dpi=600)
 plt.show()
print(age_pie())
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三、代码解析

3.1显示正负号

import matplotlib.pyplot as plt
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#用来正常显示负号 
plt.rcParams['axes.unicode_minus']=False 
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3.2显示中文

plt.rcParams['font.family'] = 'SimHei'
黑体 SimHei 
微软雅黑 Microsoft YaHei 
微软正黑体 Microsoft JhengHei 
新宋体 NSimSun 
新细明体 PMingLiU 
细明体 MingLiU 
标楷体 DFKai-SB 
仿宋 FangSong 
楷体 KaiTi 
仿宋_GB2312 FangSong_GB2312 
楷体_GB2312 KaiTi_GB2312 
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3.3找出不合法数据

import pandas as pd
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df[(df.age == '41"')].index.tolist() 
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3.4删除那一行

df = df.drop([1305]) 
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3.5显示图例

plt.legend(loc='upper right')
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3.6保存为图片

 plt.savefig('age.png', dpi=600)