我有一个多索引数据框，我已将其融化为如下所示:
Color Frequency variable value
Red 2-3 times a month x 22
Red A few days a week x 45
Red At least once a day x 344
Red Never x 5
Red Once a month x 1
Red Once a week x 0
Red Once every few months x 4
Blue 2-3 times a month x 4
Blue A few days a week x 49
Blue At least once a day x 200
Blue Never x 7
Blue Once a month x 19
Blue Once a week x 10
Blue Once every few months x 5
Red 2-3 times a month y 3
Red A few days a week y 97
Red At least once a day y 144
Red Never y 4
Red Once a month y 0
Red Once a week y 0
Red Once every few months y 4
Blue 2-3 times a month y 44
Blue A few days a week y 62
Blue At least once a day y 300
Blue Never y 2
Blue Once a month y 4
Blue Once a week y 23
Blue Once every few months y 6
Red 2-3 times a month z 4
Red A few days a week z 12
Red At least once a day z 101
Red Never z 0
Red Once a month z 0
Red Once a week z 10
Red Once every few months z 0
Blue 2-3 times a month z 100
Blue A few days a week z 203
Blue At least once a day z 299
Blue Never z 0
Blue Once a month z 0
Blue Once a week z 204
Blue Once every few months z 100
我正在尝试制作一个seaborn图，其中x轴变量和频率有两个类别，色调基于Color。此外，我希望 y 轴是每个 Color 的 value 与该 variable 值之和的比例；例如变量“每月 x.2-3 次”的 y 值应为 22/(22+45+344+5+1+0+4) 或 5.22%。
到目前为止我有这个:
import seaborn as sns
fig, ax1 = plt.subplots(figsize=(20, 10))
sns.factorplot(x='variable',y='value', hue='Frequency', data=df, kind='bar', ax=ax1)
这是到达那里的路的一部分。我如何还按 1) 颜色和 2) 获取每个变量和频率值的比例，而不是计数？
最佳答案
这是您需要查找该组每个数字的部分的内容:
df['proportion'] = df['value'] / df.groupby(['Color','variable'])['value'].transform('sum')
输出:
variable Frequency Color value portion
0 x 2-3 times a month Red 22 0.052257
1 x A few days a week Red 45 0.106888
2 x At least once a day Red 344 0.817102
3 x Never Red 5 0.011876
4 x Once a month Red 1 0.002375
5 x Once a week Red 0 0.000000
6 x Once every few months Red 4 0.009501
7 x 2-3 times a month Blue 4 0.013605
8 x A few days a week Blue 49 0.166667
9 x At least once a day Blue 200 0.680272
10 x Never Blue 7 0.023810
11 x Once a month Blue 19 0.064626
12 x Once a week Blue 10 0.034014
13 x Once every few months Blue 5 0.017007
14 y 2-3 times a month Red 3 0.011905
15 y A few days a week Red 97 0.384921
16 y At least once a day Red 144 0.571429
17 y Never Red 4 0.015873
18 y Once a month Red 0 0.000000
19 y Once a week Red 0 0.000000
20 y Once every few months Red 4 0.015873
21 y 2-3 times a month Blue 44 0.099773
22 y A few days a week Blue 62 0.140590
23 y At least once a day Blue 300 0.680272
24 y Never Blue 2 0.004535
25 y Once a month Blue 4 0.009070
26 y Once a week Blue 23 0.052154
27 y Once every few months Blue 6 0.013605
28 z 2-3 times a month Red 4 0.031496
29 z A few days a week Red 12 0.094488
30 z At least once a day Red 101 0.795276
31 z Never Red 0 0.000000
32 z Once a month Red 0 0.000000
33 z Once a week Red 10 0.078740
34 z Once every few months Red 0 0.000000
35 z 2-3 times a month Blue 100 0.110375
36 z A few days a week Blue 203 0.224062
37 z At least once a day Blue 299 0.330022
38 z Never Blue 0 0.000000
39 z Once a month Blue 0 0.000000
40 z Once a week Blue 204 0.225166
41 z Once every few months Blue 100 0.110375
关于python - Seaborn和 Pandas : Make multiple x-category bar plot using multi index data in python，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/51546293/