matplotlib

6.1离散型变量的可视化

6.1.1饼图

import matplotlib.pyplot as plt

plt.rcParams['font.sans-serif']=['Microsoft Yahei']
plt.rcParams['axes.unicode_minus']=False

edu=[0.2515,0.3724,0.3336,0.2368,0.2075]
labels=['中专','大专','本科','硕士','其他']

plt.pie(x=edu,labels=labels,autopct='%.1f%%')
plt.title('失信用户的教育水平分布')
plt.show()

6.1.2条形图

import matplotlib.pyplot as plt
import pandas as pd

GDP=pd.read_excel("dataFile/ProvinceGDp2017.xlsx",engine="openpyxl")

plt.rcParams['font.sans-serif']=['Microsoft Yahei']
plt.rcParams['axes.unicode_minus']=False

plt.bar(x=range(GDP.shape[0]),tick_label=GDP.Province,height=GDP.GDP,color='steelblue')

plt.ylabel('GDP(万亿)')
plt.title('2017年度6个省份GDP分布')

for x,y in enumerate(GDP.GDP):
    plt.text(x,y+0.1,'%s'%round(y,1),ha='center')

plt.show()

6.2数值型变量的可视化

6.2.1直方图与核密度曲线

import matplotlib.pyplot as plt
import pandas as pd

plt.rcParams['font.sans-serif']=['Microsoft Yahei']
plt.rcParams['axes.unicode_minus']=False

Titanic=pd.read_csv("datafile/titanic_train.csv")
Titanic.dropna(subset=['Age'],inplace=True)

plt.hist(x=Titanic.Age,bins=20,color='steelBlue',edgecolor='black')

plt.xlabel('年龄')
plt.ylabel('频数')
plt.title('乘客年龄分布')
plt.show()

6.2.2箱线图

6.2.3小提琴图

6.2.4折线图

 

 

 

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