Pandas delete all duplicate rows in one column if values in another column is higher than a threshol-CodePudding

I have a dataframe where there are duplicate values in column A that have different values in column B.

I want to delete rows if one of column A duplicated values has values higher than 15 in column B.

Original Datafram

A Column	B Column
1	10
1	14
2	10
2	20
3	5
3	10

Desired dataframe

A Column	B Column
1	10
1	14
3	5
3	10

CodePudding user response：

This works:

dfnew = df.groupby('A Column').filter(lambda x: x['B Column'].max()<=15 )
dfnew.reset_index(drop=True, inplace=True) 
dfnew = dfnew[['A Column','B Column']] 
print(dfnew)

output:

   A Column  B Column
0         1        10
1         1        14
2         3         5
3         3        10

CodePudding user response：

Here is another way using groupby() and transform()

df.loc[~df['B Column'].gt(15).groupby(df['A Column']).transform('any')]