python3使用seaborn生成带有扰动点的分组箱型图

import json
import seaborn as sns
import matplotlib.pyplot as plt

fig = plt.figure(figsize=(20, 5))
sns.set(style="darkgrid")
xData = []
yData = []
zData = []
with open('./files/1.txt', encoding='utf-8-sig') as f:
    data = json.load(f)
    xData = data['x']['1']
    for val in data['data']['1']:
        yData.append(float(val))
        zData.append('a')
sns.boxplot(x=xData, y=yData, whis=[0, 100])
sns.stripplot(x=xData, y=yData, jitter=0.2, size=0.5)
plt.savefig('./files/no-group.jpg')

import json
import seaborn as sns
import matplotlib.pyplot as plt

fig = plt.figure(figsize=(20, 5))
sns.set(style="darkgrid")

# whis = [0, 100] 不显示异常点
# dodge=True 扰动点图分组
xData = []
yData = []
zData = []
with open('./files/1.txt', encoding='utf-8-sig') as f:
    data = json.load(f)
    xData = data['x']['1'] + data['x']['1']
    for val in data['data']['1']:
        yData.append(float(val))
        zData.append('a')
    for val in data['data']['1']:
        yData.append(float(val))
        zData.append('b')
sns.boxplot(x=xData, y=yData, hue=zData, whis=[0, 100])
sns.stripplot(x=xData, y=yData, hue=zData, dodge=True, jitter=0.2, size=0.5, legend=False)
plt.savefig('./files/group.jpg')