Python - Panda's dataframes - generate column with group level information

Question

I generated a Panda's DataFrame with:

data={'id': [1.0, 1, 2, 3, 3, 3, 4.0,4.0,5,5],'some':['Yes','No','No','Yes','Yes','Yes','No','No','No','Yes']}
df=DataFrame(data)

In this DataFrame I would like to add a column "someIDlevel" which contains the "some" information "at the ID" level. The following rules apply: whenever within an ID there is at least one "Yes" in "some" than "someIdlevel" should be all yes for that particular "id", otherwise it should be "No" for that particular ID.

So the final dataframe should look like as if created by this code:

data_fin={'id': [1.0, 1, 2, 3, 3, 3, 4.0,4.0,5,5],'some':'Yes','No','No','Yes','Yes','Yes','No','No','No','Yes'],'someIDlevel':['Yes','Yes','No','Yes','Yes','Yes','No','No','Yes','Yes']}       df_fin=pd.DataFrame(data_fin)

Answer 1

You could do the following.

First perform a left-merge on a groupby:

df = pd.merge(
    df,
    df.some.groupby(df.id).apply(lambda g: 'Yes' if 'Yes' in g.values else 'No').reset_index(),
    how='left')

Following that, simply rename the new column to your desired name:

>>> df.rename(columns={0: 'someIdlevel'})
    id  some    someIdlevel
0   1   Yes Yes
1   1   No  Yes
2   2   No  No
3   3   Yes Yes
4   3   Yes Yes
5   3   Yes Yes
6   4   No  No
7   4   No  No
8   5   No  Yes
9   5   Yes Yes