Dataframe 根据条件替换为另一行

Question

I have a dataframe like the following:

    ean           product_resource_id        shop
----------------------------------------------------
    123           abc                        xxl
    245           bed                        xxl
    456           dce                        xxl
    123           0                          conr
    245           0                          horec

I want to replace 0 "product_resource_id" s with an id where " ean "s are same.

I want to get a result like:

    ean           product_resource_id        shop
----------------------------------------------------
    123           abc                        xxl
    245           bed                        xxl
    456           dce                        xxl
    123           abc                        conr
    245           bed                        horec

Any help would be really helpful. Thanks in advance!

Answer 1

Idea is filter rows with 0 values in product_resource_id , remove duplicates by ean column if exist and create Series by DataFrame.set_index for mapping, if no match values are replace by original by values by Series.fillna , because non match values return NaN s:

#mask = df['product_resource_id'].ne('0')
#if 0 is integer
mask = df['product_resource_id'].ne(0)
s = df[mask].drop_duplicates('ean').set_index('ean')['product_resource_id']
df['product_resource_id'] = df['ean'].map(s).fillna(df['product_resource_id'])
print (df)
   ean product_resource_id   shop
0  123                 abc    xxl
1  245                 bed    xxl
2  456                 dce    xxl
3  123                 abc   conr
4  245                 bed  horec