Python Pandas Column 删除特殊字符并排列值

Question

我有一个如下所示的数据框。

    columnA                                                                                                                     columnB                         columnC
[['Beauty & Wellness/Beauty Mavens', '21', '17', '22'], ['Beauty & Wellness/Frequently Visits Salons', '22', '21', '25']]   GA_All_B2B_Visitors_Jan20       2020-01-10 to 2020-01-15
[['Banking & Finance/Avid Investors', '585', '455', '700'], ['Beauty & Wellness/Beauty Mavens', '414', '339', '467']]       GA_Oven_Page_Visitors_Nov2019   2020-01-10 to 2020-01-15

我正在尝试将其安排为如下所示，但我从哪里开始卡住了：

columnA                                     cola   colb    colc        columnB                          columnC
Beauty & Wellness/Beauty Mavens             21      17      22      GA_All_B2B_Visitors_Jan20       2020-01-10 to 2020-01-15
Beauty & Wellness/Frequently Visits Salons  22      21      25      GA_All_B2B_Visitors_Jan20       2020-01-10 to 2020-01-15
Banking & Finance/Avid Investors            585     455     700     GA_Oven_Page_Visitors_Nov2019   2020-01-10 to 2020-01-15
Beauty & Wellness/Beauty Mavens             414     339     467     GA_Oven_Page_Visitors_Nov2019   2020-01-10 to 2020-01-15

我的方法如下所示，但从哪里开始就卡住了。 我首先尝试拆分第一列的值，但它不起作用。

df_seg = pd.concat([df_seg[['columnB', 'columnC']], df_seg['columnA'].str.split(', ', expand=True)], axis=1)

任何人都可以帮忙吗？

Answer 1

使用DataFrame.explode能够创建一个DataFrame两个列表内容的DataFrame.join并将其与DataFrame.join

new_df = df.explode('columnA').reset_index(drop=True)
new_df = (pd.DataFrame(new_df['columnA'].tolist(),
                       columns = ['columnA','cola','colb','colc'])
            .join(new_df[['columnB','columnC']]))
print(new_df)
                                      columnA cola colb colc  \
0             Beauty & Wellness/Beauty Mavens   21   17   22   
1  Beauty & Wellness/Frequently Visits Salons   22   21   25   
2            Banking & Finance/Avid Investors  585  455  700   
3             Beauty & Wellness/Beauty Mavens  414  339  467   

                         columnB                   columnC  
0      GA_All_B2B_Visitors_Jan20  2020-01-10 to 2020-01-15  
1      GA_All_B2B_Visitors_Jan20  2020-01-10 to 2020-01-15  
2  GA_Oven_Page_Visitors_Nov2019  2020-01-10 to 2020-01-15  
3  GA_Oven_Page_Visitors_Nov2019  2020-01-10 to 2020-01-15