一、顏色

二、實例

#讀者分佈
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() # 找出不合法數值所在行
 df = df.drop([1305]) # 刪除那一行
 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為第二個元素凸出距離
 colors = ['tomato', 'lightskyblue', 'goldenrod', 'green', 'y']
 # 餅圖繪製函數
 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('讀者年齡分佈圖')
 plt.axis('equal')
 plt.legend(loc='upper right')
 plt.savefig('age.png', dpi=600)
 plt.show()
print(age_pie())
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三、代碼解析

3.1顯示正負號

import matplotlib.pyplot as plt
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#用來正常顯示負號 
plt.rcParams['axes.unicode_minus']=False 
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3.2顯示中文

plt.rcParams['font.family'] = 'SimHei'
黑體 SimHei 
微軟雅黑 Microsoft YaHei 
微軟正黑體 Microsoft JhengHei 
新宋體 NSimSun 
新細明體 PMingLiU 
細明體 MingLiU 
標楷體 DFKai-SB 
仿宋 FangSong 
楷體 KaiTi 
仿宋_GB2312 FangSong_GB2312 
楷體_GB2312 KaiTi_GB2312 
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3.3找出不合法數據

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

df = df.drop([1305]) 
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3.5顯示圖例

plt.legend(loc='upper right')
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3.6保存為圖片

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