一、顏色

二、例項

#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']
    # 餅圖繪製函式
    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())

三、程式碼解析

3.1顯示正負號

import matplotlib.pyplot as plt

#用來正常顯示負號  
plt.rcParams['axes.unicode_minus']=False 

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    

3.3找出不合法資料

import pandas as pd

df[(df.age == '41"')].index.tolist()  

3.4刪除那一行

df = df.drop([1305])  

3.5顯示圖例

plt.legend(loc='upper right')

3.6儲存為圖片

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