python pandas assignment of missing value as an copy

Question

I'm trying to set the mean value of group of products in my dataset (wants to iterate each category and fill the missing data eventually)

df.loc[df.iCode == 160610,'oPrice'].fillna(value=df[df.iCode == 160610].oPrice.mean(), inplace=True)

it's not working (maybe treating it like a copy)

Thanks

Good Hint, df.oPrice.fillna(df.groupby(by='iCode').oPrice.transform('mean'), inplace=True) Worked — Yuval Asher, Nov 22 '19 at 17:31

score 0 · Answer 1 · answered Nov 22 '19 at 16:01

0

df.loc[(df.iCode == 160610) & (df.oPrice.isna()),'oPrice'] = df.loc[df.iCode == 160610].oPrice.mean()

answered Nov 22 '19 at 16:01

Joshua Cabanas

1

Mind adding some explanation of what you're doing here? – CBredlow Nov 22 '19 at 18:52
what he is doing is a form of chain indexing. First indexing `df.loc[df.iCode == 160610,'oPrice']` the next is `isna()`. by doing `df.loc[(df.iCode == 160610) & (df.oPrice.isna()),'oPrice']` allows you to index the dataframe only once. then explicitly assigning the values to the NAs `oPrice column` with the mean of the `oPrice column`. read https://stackoverflow.com/a/23296545/11724956 for more details. – Joshua Cabanas Nov 27 '19 at 14:13

1 Answers1