python可视化进阶---seaborn1.5 分类数据可视化 - 分类散点图 stripplot() / swarmplot()

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
#设置风格、尺度
sns.set_style('whitegrid')
sns.set_context('paper')
#不发出警告
import warnings
warnings.filterwarnings('ignore')

tips = sns.load_dataset('tips')
print(tips.head())
sns.stripplot(x = 'day',       #x ---> 设置分组统计字段
              y = 'total_bill',#y ---> 数据分布统计字段
              #这里xy数据对调，会使得散点图横向分布
              data = tips,    #data ---> 对应数据
              jitter = True, #jitter ---> 当数据重合较多时，用该参数做一些调整，也可以设置间距如，jitter = 0.1    
              size = 5, edgecolor = 'w', linewidth = 1, marker = 'o'
              )
#通过hue参数再分类
sns.stripplot(x = 'sex', y = 'total_bill', hue = 'day', data=tips, jitter = True)

#设置调色盘
sns.stripplot(x = 'sex' , y = 'total_bill', hue = 'day',
              data = tips, jitter = True,
              palette = 'Set2',#设置调色盘
              dodge = True,
              )

#筛选分类类别
#查看day字段的唯一值
print(tips['day'].value_counts())
#order  ---> 筛选类别
sns.stripplot(x = 'day', y = 'total_bill', data = tips, jitter = True,
              order = ['Sat','Sun'])

#用法和stripplot类似
sns.swarmplot(y = 'total_bill', x = 'day', data= tips,
              size = 5, edgecolor = 'w', linewidth = 1, marker = 'o',
              palette = 'Reds')