Pivot - 通过重复的熊猫数据框转置列

Question

I have a DataFrame with a column named 'ID' that has duplicate observations. Each 'ID' row has one or more 'Article' values columns. I want to transpose the whole dataframe grouping by 'ID' adding new columns at the same row of a unique 'ID'.

What I have:

ID  Article_1   Article_2
1   Banana      Coconut
2   Apple       Strawberry
1   Apple   
3   Tomatoe 
1   Pineapple   
2   Banana  
4   Apple   
5   Apple       Strawberry
3   Apple   

What I want:

ID     Article_1    Article_2   Article_3   Article_4
0001    Banana      Coconut     Apple       Pineapple
0002    Apple       Strawberry  Banana      NaN
0003    Tomatoe     Apple       NaN         NaN
0004    Apple       NaN         NaN         NaN
0005    Apple       Strawberry  NaN         NaN

NEW EDIT:

I had some situations where order is important.

My DF:

ID  Article     Article_2
1   Banana      NaN
2   Apple       NaN
1   Apple       Coconut
3   Tomatoe     Coconut
1   Pineapple   Tropical
2   Banana      Coconut
4   Apple       Coconut
5   Apple       Coconut
3   Apple       Pineapple

Output with first @Erfan solution:

        Article_1   Article_2   Article_3   Article_4   Article_5   Article_6
0001    Banana      Apple       Pineapple   NaN         Coconut     Tropical
0002    Apple       Banana      NaN         Coconut     NaN         NaN
0003    Tomatoe     Apple       Coconut     Pineapple   NaN         NaN
0004    Apple       Coconut     NaN         NaN         NaN         NaN
0005    Apple       Coconut     NaN         NaN         NaN         NaN

What i need:

        Article_1   Article_2   Article_3   Article_4   Article_5   Article_6
0001    Banana      Apple       Pineapple   Coconut     Tropical    NaN     
0002    Apple       Banana      Coconut     NaN         NaN         NaN
0003    Tomatoe     Apple       Coconut     Pineapple   NaN         NaN
0004    Apple       Coconut     NaN         NaN         NaN         NaN
0005    Apple       Coconut     NaN         NaN         NaN         NaN

I can't have Article_5 with a NaN value and Article_6 with a value at the same row.

Answer 1

If order of the articles is not important, we can use DataFrame.melt to unpivot your articles to rows.

Then we use DataFrame.pivot_table to aggregate to each ID . While we use GroupBy.cumcount to give a unique identifier to each article within a ID :

dfn = df.melt(id_vars='ID', value_vars=['Article_1', 'Article_2'])
dfn = dfn.pivot_table(index='ID', 
                      columns=dfn.groupby('ID')['value'].cumcount().add(1),
                      values='value',
                      aggfunc='first').add_prefix('Article_').rename_axis(None, axis='index')

     Article_1   Article_2   Article_3 Article_4
0001    Banana       Apple   Pineapple   Coconut
0002     Apple      Banana  Strawberry       NaN
0003   Tomatoe       Apple         NaN       NaN
0004     Apple         NaN         NaN       NaN
0005     Apple  Strawberry         NaN       NaN