How to stack a paired data structure like this?

Question

I have a data frame that looks like this:

df_dict = {'FamID' : [1, 2], 'Person_1' : ['Husband', 'Granpa'] , 'Person_2' : ['Wife', 'Grandson'], 'Higher_income' : [1, 0]}
df = pd.DataFrame(df_dict)
df = df.set_index('FamID')

It compares the income between household members. So for Higher_income column, 1 means Person_1 has the higher income and 0 means Person_2 does.

How can I stack this data frame so that the result looks like:

Asked By: NonSleeper

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Source

Answer 1

You can use wide_to_long:

df=pd.wide_to_long(df.reset_index(),['Person'],i=['FamID'],j='Key',sep='_').reset_index(level=1).assign(Higher_income=lambda x : x['Higher_income'].ne(x['Key']-1).astype(int)).sort_index()
#you can add the .drop('Key',1) at the end 

Out[51]: 
       Key  Higher_income    Person
FamID                              
1        1              1   Husband
1        2              0      Wife
2        1              0    Granpa
2        2              1  Grandson

Answered By: BENY

Answer 2

For your data:

s = (df_tmp.filter(like='Person').stack()
         .reset_index(level=-1, drop=True)
         .reset_index(name='Person')
    )

s.loc[::2, 'Higher_income'] = df_tmp.Higher_income.values
s.loc[1::2,'Higher_income'] = 1 - df_tmp.Higher_income.values

Output:

   FamID    Person  Higher_income
0      1   Husband            1.0
1      1      Wife            0.0
2      2    Granpa            0.0
3      2  Grandson            1.0

Answered By: Quang Hoang

Answer 3

You can create dummy columns with the same suffixes to figure out who has the highest_income. Then wide_to_long. This would scale well to many people, so long as the Higher_income label corresponds to the suffix of the Person_i column.

# Make labels match Person_i format. 
df['Higher_income'] = df['Higher_income'].replace(0, 2)

df = pd.get_dummies(df, columns=['Higher_income']).reset_index()
#   FamID Person_1  Person_2  Higher_income_1  Higher_income_2
#0      1  Husband      Wife                1                0
#1      2   Granpa  Grandson                0                1

(pd.wide_to_long(df, i='FamID', j='num', stubnames=['Person', 'Higher_income'], sep='_')
   .reset_index('num', drop=True))

#         Person  Higher_income
#FamID                         
#1       Husband              1
#2        Granpa              0
#1          Wife              0
#2      Grandson              1

Answered By: ALollz

How to stack a paired data structure like this?

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