迭代列中的每个类别，并将另一列中的值作为单独的df添加

Question

我想为Customer_Acquisition_Channel列中的每个类别将Days_To_Acquisition列中的所有值添加到单独的df中。

所有Customer_ID值在下面的数据集中都是唯一的

DF

Customer_ID Customer_Acquisition_Channel  Days_To_Acquisition
323         Organic                       2
583         Organic                       5
838         Organic                       2
193         Website                       7
241         Website                       7
642         Website                       1

所需输出: Days_To_Acq_Organic_Df

Index Days_To_Acquisition
0     2
1     5
2     2

Days_To_Acq_Website_Df

Index Days_To_Acquisition
0     7
1     7
2     1

这就是我到目前为止所尝试的方法，但我想使用for循环，而不是手动遍历每一列

sub_1 = df.loc[df['Customer_Acquisition_Channel'] == 'Organic']
Days_To_Acq_Organic_Df=sub_1[['Days_To_Acquisition']]

sub_2 = df.loc[df['Customer_Acquisition_Channel'] == 'Website']
Days_To_Acq_Website_Df=sub_2[['Days_To_Acquisition']]

Answer 1

您可以遍历通道列的唯一值，创建新的数据帧，更改列名，并将其附加到列表中：

dataframes = []
for channel in df.Customer_Acquisition_Channel.unique():
    new_df = df[df['Customer_Acquisition_Channel'] == channel][['Customer_ID','Days_To_Acquisition']]
    new_df.columns = ['Customer_ID',f'Days_To_Acquisition_{channel}_df']
    dataframes.append(new_df)

输出：

for df in dataframes:
    print(df,'\n__________')

   Customer_ID  Days_To_Acquisition_Organic_df
0          323                               2
1          583                               5
2          838                               2 
__________
   Customer_ID  Days_To_Acquisition_Website_df
3          193                               7
4          241                               7
5          642                               1 
__________

或者，您可以将数据帧存储到字典中，这样您就可以对它们进行命名并分别调用它们：

dataframes = {}
for channel in df.Customer_Acquisition_Channel.unique():
    new_df = df[df['Customer_Acquisition_Channel'] == channel][['Customer_ID','Days_To_Acquisition']]
    new_df.columns = ['Customer_ID',f'Days_To_Acquisition_{channel}']
    dataframes[f'Days_To_Acquisition_{channel}_df'] = new_df

输出：

print(dataframes['Days_To_Acquisition_Organic_df'])

   Customer_ID  Days_To_Acquisition_Organic
0          323                            2
1          583                            5
2          838                            2