Pandas pivot dataframe with unequal columns

Question

I have a dataframe containing a categorical variable in one column and a continuous variable in another column like so:

    gender  contVar
    Male     22379
    Female   24523
    Female   23421
    Male     23831
    Male     29234

I want to get a table like so:

    Male   Female
    22379   24523
    23831   23421
    23831
    29234

Is this possible in pandas? When I do:

    df.pivot(index = df.index.tolist(), columns='gender', values='contVar')

I get that the index is out of bounds (obviously since there arent rows as there are indices but I also presume that its because the number of rows in each column are not equal). Any ideas are appreciated.

Colonel Beauvel · Accepted Answer · 2016-04-26 12:47:52Z

5

You can do:

pd.concat([pd.DataFrame({g:d.contVar.tolist()}) for g,d in df.groupby('gender')], axis=1)

Out[416]:
   Female   Male
0   24523  22379
1   23421  23831
2     NaN  29234

answered Apr 26, 2016 at 12:47

Colonel Beauvel

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7 Comments

dter Over a year ago

Or is it possible to get two separate lists? I don't really need the pivotted data in a table (and fill empty cells with NaN) but even separate lists.

Colonel Beauvel Over a year ago

I do not use pivot here, and I actually construct a list of dataframes (one for female, the other for male) so you can access 'separate' dataframes from this list.

Abbas Over a year ago

[d.contVar.tolist() for g,d in df.groupby('gender')] do this will give you a list of two lists like this [[24523, 23421], [22379, 23831, 29234]]

Abbas Over a year ago

[{g:d.contVar.tolist()} for g,d in df.groupby('gender')] do this will give you a list of two dicts like this [{'Female': [24523, 23421]}, {'Male': [22379, 23831, 29234]}]

Colonel Beauvel Over a year ago

it is a list of dictionnary indeed, not clear what the OP means by 'two separate lists'

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