使用groupby创建百分比堆积条形图

Question

我正在寻找不同贷款状态水平的房屋所有权，我想用百分比的堆积条形图来显示它。

我已经能够使用以下代码创建频率堆积条形图：

df_trunc1=df[['loan_status','home_ownership','id']]
sub_df1=df_trunc1.groupby(['loan_status','home_ownership'])['id'].count()
sub_df1.unstack().plot(kind='bar',stacked=True,rot=1,figsize=(8,8),title="Home ownership across Loan Types")

这给了我这张照片：1

但我无法弄清楚如何将图形转换为百分比。因此，例如，我想进入默认组，哪个百分比有抵押，拥有等等。

这是context2的groupby表：

谢谢！！

Answer 1

我相信你需要自己转换百分比：

d = {('Default', 'MORTGAGE'): 498, ('Default', 'OWN'): 110, ('Default', 'RENT'): 611, ('Fully Paid', 'MORTGAGE'): 3100, ('Fully Paid', 'NONE'): 1, ('Fully Paid', 'OTHER'): 5, ('Fully Paid', 'OWN'): 558, ('Fully Paid', 'RENT'): 2568, ('Late (16-30 days)', 'MORTGAGE'): 1101, ('Late (16-30 days)', 'OWN'): 260, ('Late (16-30 days)', 'RENT'): 996, ('Late (31-120 days)', 'MORTGAGE'): 994, ('Late (31-120 days)', 'OWN'): 243, ('Late (31-120 days)', 'RENT'): 1081}

sub_df1 = pd.DataFrame(d.values(), columns=['count'], index=pd.MultiIndex.from_tuples(d.keys()))
sub_df2 = sub_df1.unstack()
sub_df2.columns = sub_df2.columns.droplevel()  # Drop `count` label.
sub_df2 = sub_df2.div(sub_df2.sum())
sub_df2.T.plot(kind='bar', stacked=True, rot=1, figsize=(8, 8), 
               title="Home ownership across Loan Types")

sub_df3 = sub_df1.unstack().T
sub_df3.index = sub_df3.index.droplevel()  # Drop `count` label.
sub_df3 = sub_df3.div(sub_df3.sum())
sub_df3.T.plot(kind='bar', stacked=True, rot=1, figsize=(8, 8), 
               title="Home ownership across Loan Types")

Answer 2

我通过将数据帧转置两次来计算百分比。是否一步一步地更明确地显示逻辑。

#transpose
to_plot =sub_df1.unstack()
to_plot_transpose = to_plot.transpose()

#calc %
to_plot_transpose_pct = to_plot_transpose.div(to_plot_transpose.sum())

#transpose back
to_plot_pct=to_plot_transpose_pct.transpose()

#plot
to_plot_pct.plot(kind='bar',stacked=True,rot=1,figsize= . 
  (8,8),title="Home ownership across Loan Types")