Python可视化颜色图例（Python可视化颜色图例）

#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()) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32

3.1显示正负号

import matplotlib.pyplot as plt 1 #用来正常显示负号 plt.rcParams['axes.unicode_minus']=False 1 2

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 1 2 3 4 5 6 7 8 9 10 11 12

3.3找出不合法数据

import pandas as pd 1 df[(df.age == '41"')].index.tolist() 1

3.4删除那一行

df = df.drop([1305]) 1

3.5显示图例

plt.legend(loc='upper right') 1

3.6保存为图片

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