Append list element in pandas dataframe column depending on value of another column

Whenever I try to append to a list given some condition, the value ends up being None instead of the list with the appended value. Example:

# sample data
data = {"bool_col": [True, False, True, True, False]}
my_df = pd.DataFrame.from_dict(data)

# instantiate column of empty lists
my_df["list_col"] = [[] for r in range(len(my_df))]

# append value to list_col when bool_col is True
my_df["list_col"] = my_df.apply(lambda x: x["list_col"].append("truth!") if x["bool_col"] else [], axis=1)


I’ve tried wrapping x["list_col"] in list() prior to calling append() to no avail. I’m not sure how to do this while retaining whatever list values may already be present and appending a new one.

>Solution :

In your case: append() appends item to list in place and returns None, which is allocated to my_df["list_col"]. You want to return the list in your apply lambda.

Try this: my_df["list_col"] = my_df.apply(lambda x: x["list_col"] + ["truth!"] if x["bool_col"] else [], axis=1)


   bool_col  list_col
0      True  [truth!]
1     False        []
2      True  [truth!]
3      True  [truth!]
4     False        []

This should work for your usecase, since if I repeat the apply twice, I get

   bool_col          list_col
0      True  [truth!, truth!]
1     False                []
2      True  [truth!, truth!]
3      True  [truth!, truth!]
4     False                []

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