CODEWITHSUNDEEP
pythonpandasdataframe
Hiccupxd
Hiccupxd

Reputation: 19

dataframe drop rows based on specific conditions of columns

Here is a part of df:

   NUMBER         MONEY
    12345           20
    12345          -20
    123456          10
    678910          7.6
    123457          3
    678910         -7.6

I want to drop rows which have the same NUMBER but opposite money.

The ideal outcome would like below:

   NUMBER         MONEY

    123456          10

    123457          3

Upvotes: 0

Views: 62

Answers (2)

shaik moeed
shaik moeed

Reputation: 5785

Try this,

>>> df[~df.assign(MONEY=df.MONEY.abs()).duplicated(keep=False)]

Output:

   NUMBER  MONEY
2  123456   10.0
4  123457    3.0

From comments(by @piRSquared):

By using assign, a new column was added to df and the subsequent drop_duplicates takes into account both NUMBER and the absolute value of MONEY

df[~df.assign(MONEY=df.MONEY.abs()).duplicated(keep=False)]

Upvotes: 1

anky
anky

Reputation: 75080

If there are just 2 rows in a group, use:

df[df.groupby('NUMBER').MONEY.transform('sum').ne(0)]

   NUMBER  MONEY
2  123456   10.0
4  123457    3.0

Upvotes: 1

Related Questions