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pythonpandasdataframesklearn-pandas

Split list into columns in pandas

I have a dataframe like this

df = (pd.DataFrame({'ID': ['ID1', 'ID2', 'ID3'], 
                    'Values': [['AB', 'BC'], np.NaN, ['AB', 'CD']]}))

df

    ID  Values
0   ID1 [AB, BC]
1   ID2   NaN
2   ID3 [AB, CD]

I want to split the item inside list into column such that

    ID  AB  BC  CD
0   ID1 1   1   0
1   ID2 0   0   0
2   ID3 1   0   1
Solution

  • Pandas functions working with missing values nice, so use Series.str.join with Series.str.get_dummies, DataFrame.pop is for extract column and last join to original data:

    df = df.join(df.pop('Values').str.join('|').str.get_dummies())
print (df)
    ID  AB  BC  CD
0  ID1   1   1   0
1  ID2   0   0   0
2  ID3   1   0   1

    EDIT: If values are not lists, only string representation of lists use ast.literal_eval for converting to lists:

    import ast

df = (df.join(df.pop('Values')
        .apply(ast.literal_eval)
        .str.join('|')
        .str.get_dummies()))