So i have a dataset like this

And what i want to do is basically, check if the list contains None values. And substitute every single None value by the "hello" string. But making sure, that the None filled list isnt filled.

Any takes on other ways to approach this issue? Btw couldnt display as a list bcs of weird error on stack

for lst in df_safe_l['CampaignSource']:
if None in lst:
    for j in set(lst):
        if j:
            lst[:] = [j] * len(lst)

Mine worked but i am looking for faster alternatives

CodePudding user response：

You can try turn the list to Series and then fill the None with other values

df['CampaignSource'] = df['CampaignSource'].apply(lambda lst: pd.Series(lst).bfill().ffill().tolist())

print(df)

    UserId                       CampaignSource
0   Potato         [hello, hello, hello, hello]
1   Carrot         [hello, hello, hello, hello]
2  Carrot2             [None, None, None, None]
3  Potato2  [kawai, kawai, kawai, kawai, kawai]

CodePudding user response：

First check if the list contains only None by using None in set(x) and len(set(x)) == 1. If yes, then you don't need to replace anything. But if it contains anything other than None then create a new list containing the type string len(x) times. Try using .apply(). :

df_safe_l['CampaignSource'] = df_safe_l['CampaignSource'].apply(lambda x: x if None in set(x) and len(set(x)) == 1 else [[i for i in x if isinstance(i, str)][0]] * len(x))

Output:

    userid                       CampaignSource
0   Potato         [hello, hello, hello, hello]
1   Carrot         [hello, hello, hello, hello]
2  Carrot2             [None, None, None, None]
3  Potato2  [kawai, kawai, kawai, kawai, kawai]