Update a specific element in all a list of N lists

[hanan lamaazi]

Dear All,

I really need your assistance,

I have a dataset with 1005000 rows and 25 columns,

The main column that I repeatedly use are Time, ID, and Reputation

First I sliced the data based on the time, and I append the sliced data in
a list called "df_list". So I get 201 lists with 25 columns

The main code is starting for here:

for elem in df_list:

{do something.....}

{Here I'm trying to calculate the outliers}

Out.append(outliers)

Now my problem is that I need to locate those outliers in the df_list and
then update another column with is the "Reputation"

Note that the there is a duplicated IDs but at different time slot

example is ID = 1 is outliers, I need to select all ID = 1 in the list and
update their reputation column

I tried those solutions:
1)

grp = data11.groupby(['ID'])
        for i in GlobalNotOutliers.ID:
            data11.loc[grp.get_group(i).index, 'Reput'] += 1

        for j in GlobalOutliers.ID:
            data11.loc[grp.get_group(j).index, 'Reput'] -= 1


It works for a dataframe but not for a list

2)

for elem in df_list:

elem.loc[elem['ID'].isin(Outlier['ID'])]


It doesn't select the right IDs, it gives the whole values in elem

3) Here I set the index using IDs:

for i in Outlier.index:
    for elem in df_list:
        print(elem.Reput)
        if i in elem.index:
#             elem.loc[elem[i] , 'Reput'] += 1
            m = elem.iloc[i, :]
            print(m)


It gives this error:

IndexError: single positional indexer is out-of-bounds


I'm greatly thankful to anyone who can help me,