python - 显示带有比例和填充的条形图不起作用

Question

我正在使用plotnine绘制一些图。当我尝试显示比例条形图而不是计数时，该fill参数变得无用。我注意到删除group=1参数有助于让fill参数再次“活跃”。但是，如果没有group=1参数，则无法正确计算比例。

这是我的功能：

def plot_churn(df_):
   color_dict = {
       'Stayed': 'green',
       'Churned': 'red'
   }

   myplot = ggplot(data=df_, mapping=aes(x='Flag_Churned', fill='Flag_Churned'))
   myplot += geom_bar(mapping=aes(y="stat(prop)", group=1))
   myplot += theme(subplots_adjust={'right': 0.71})
   myplot += facet_wrap('Flag_Treat')
   myplot += scale_fill_manual(color_dict)
   myplot += scale_y_continuous(labels=percent_format())
   print(myplot)

例如，当使用以下 pandas DataFrame 时：

data = {'Churn': [0,0,0,1,1,0,1,1], 'Flag_Treat': ['treated','treated','treated','treated','not treated','not treated','not treated','not treated'],
    'Flag_Churned': ['Stayed', 'Stayed', 'Stayed', 'Churned', 'Churned', 'Stayed', 'Churned', 'Churned']}
df = pd.DataFrame(data=data)

结果输出没有被“Flag_Churned”填充：

我究竟做错了什么？

标签： pythonplotnine

Answer 1

问题是stat(prop)计算每个方面的道具。虽然设置group美学会给你正确的道具，但它会覆盖分组fill。拥有 R 背景，我知道如何在 R 中即时进行此计算。但是，R 中建议的更简单的方法和大部分时间是在将数据传递给之前聚合您的数据ggplot并使用geom_col代替geom_bar：

from mizani.formatters import percent_format
from plotnine import *
import pandas as pd
import numpy as np

data = {'Churn': [0,0,0,1,1,0,1,1], 'Flag_Treat': ['treated','treated','treated','treated','not treated','not treated','not treated','not treated'],
    'Flag_Churned': ['Stayed', 'Stayed', 'Stayed', 'Churned', 'Churned', 'Stayed', 'Churned', 'Churned']}
df = pd.DataFrame(data=data)

df_.group_by(['Flag_Churned', 'Flag_Treat']).agg(len)

color_dict = {
  'Stayed': 'green',
  'Churned': 'red'
}

def plot_churn(df_):
   color_dict = {
       'Stayed': 'green',
       'Churned': 'red'
   }
                                                 
   df_ = df_.groupby(['Flag_Churned', 'Flag_Treat']).agg(len)
   df_ = df_.groupby(level=0).apply(lambda x: x / float(x.sum())).reset_index()
  
   myplot = ggplot(data=df_, mapping=aes(x='Flag_Churned', y='Churn', fill='Flag_Churned'))
   myplot += geom_col()
   myplot += theme(subplots_adjust={'right': 0.71})
   myplot += facet_wrap('Flag_Treat')
   myplot += scale_fill_manual(color_dict)
   myplot += scale_y_continuous(labels=percent_format())
   print(myplot)

plot_churn(df)