Split columns of lists into multiple columns

Question

I have columns values inside a list

df1 = pd.DataFrame(
    {
        "column0": [["xx, aa", "xx, aa"]],
        "column1": [["yy, bb","yy, aa"]],
        "column2": [["cc, xx", "cc, xx"]]})

         column0         column1               column2
0   [xx, aa, xx, aa]    [yy, bb, yy, aa]    [cc, xx, cc, xx]

I want to separate all of them into multiple columns

outcome:

   column0 column1 column2 column3 column4 column5  column6  column7 column8 column9  
0   xx    aa   xx     aa    yy    bb    yy     aa      cc       xx     cc     xx

Any ideas?

EDIT:

The suggested question is not relevant to by problem as I have multiple columns and not just one

It's not clear if there should be 8 or 12 columns in the final dataframe. (Each list has 2 string values, not 4.) — Bill the Lizard
– Bill the Lizard, Commented Dec 2, 2021 at 19:33

irahorecka · Accepted Answer · 2021-12-02 19:46:33Z

0

I think it's a better approach to clean your data prior to instantiating a pandas DataFrame.

Here's an option you can take given the data structure you posted:

import pandas as pd

init_dict = {"column0": [["xx, aa", "xx, aa"]], "column1": [["yy, bb", "yy, aa"]], "column2": [["cc, xx", "cc, xx"]]}

pd_dict = {}
col_counter = 0
for _, value in init_dict.items():
    for item in value.pop():
        for inner_item in item.split(","):
            pd_dict[f"column{col_counter}"] = [inner_item.strip()]
            col_counter += 1

pd.DataFrame(pd_dict)

>>>  column0 column1 column2 column3 column4 column5 column6 column7 column8  \
0      xx      aa      xx      aa      yy      bb      yy      aa      cc   

  column9 column10 column11  
0      xx       cc       xx

answered Dec 2, 2021 at 19:46

irahorecka

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