python实现deep learning

seaborn可视化之FacetGrid()

2019-05-16  本文已影响0人  juriau

准备数据

import seaborn as sns
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

tips = sns.load_dataset("tips")

1、操作流程

直方图

g = sns.FacetGrid(tips, col='time')
g.map(plt.hist, "tip")

散点图

g = sns.FacetGrid(tips,col='sex',hue='smoker') # 设置参数hue,分类显示
g.map(plt.scatter,"total_bill","tip", alpha=0.7) # 参数alpha,设置点的大小
g.add_legend()  # 加注释

条形图

g = sns.FacetGrid(tips,col='day',size=4,aspect=0.5)
g.map(sns.barplot,"sex","total_bill")

箱状图

from pandas import Categorical
ordered_days = tips.day.value_counts().index
print(ordered_days)
ordered_days = Categorical(['Thur',"Fri","Sat","Sun"])
# FacetGrid传数据需要是pandas格式
g = sns.FacetGrid(tips,row='day',row_order=ordered_days,size=1.7,aspect=4)
g.map(sns.boxplot,"total_bill")
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