[英]Plot mean in subplots - Seaborn
我的目標是 plot 是一組子圖的平均值。 使用下面,我將每個獨特的Item
分成一個單獨的子圖。 我希望 plot 與每個子圖的Num
相關平均值。
import pandas as pd
import seaborn as sns
df = pd.DataFrame({
'Num' : [1,2,1,2,3,2,1,3,2,2,1,2,3,3,1,3],
'Label' : ['A','B','C','B','B','C','C','B','B','A','C','A','B','A','C','A'],
'Item' : ['Up','Left','Up','Left','Down','Right','Up','Down','Right','Down','Right','Up','Up','Right','Down','Left'],
})
g = sns.displot(data = df,
x = 'Num',
row = 'Item',
row_order = ['Up','Down','Left','Right'],
discrete = True,
aspect = 4,
height = 2,
)
#for x in df['IMMEDIATE_CONGESTION_PLAYER_COUNT']:
plt.axvline(np.median(df['Num']),color='b', linestyle='--')
這是一個很好的答案。 對於初始圖 object,使用 map function 添加一條垂直線。
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
df = pd.DataFrame({
'Num' : [1,2,1,2,3,2,1,3,2,2,1,2,3,3,1,3],
'Label' : ['A','B','C','B','B','C','C','B','B','A','C','A','B','A','C','A'],
'Item' : ['Up','Left','Up','Left','Down','Right','Up','Down','Right','Down','Right','Up','Up','Right','Down','Left'],
})
g = sns.displot(data = df,
x = 'Num',
row = 'Item',
row_order = ['Up','Down','Left','Right'],
discrete = True,
aspect = 4,
height = 2,
)
cols = df['Item'].unique()
for c,ax in zip(cols, g.axes.flat):
ax.axvline(np.median(df[df['Item'] == c]['Num']), color='r', linestyle='--')
plt.show()
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