使用groupby创建百分比堆积的条形图

106

yogz123

我正在查看处于不同贷款状态级别的房屋所有权，我想使用堆积的条形图以百分比形式显示此信息。

我已经可以使用以下代码创建频率堆叠的条形图：

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

但我不知道如何将图表转换为百分比。因此，例如，我想进入默认组，哪个百分比有抵押贷款，哪个拥有抵押等等。

这是上下文2的groupby表：

谢谢！！

亚历山大大帝

我相信您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")