CODEWITHSUNDEEP
pythonpython-3.xpandasdataframe
SD_23
SD_23

Reputation: 421

Remove Rows from Dataframe Based on 2 Conditions

I have a python dataframe that contains NHL Player data from multiple seasons. I'm trying to remove all rows of players that didn't play in 2018-2019. For example if Joe Jones played in 2018-2019, I want to keep his data from that season, and any other season he has played in.

I'm thinking the code would look something like this:

for player in data.players:
      if data['Year'] == '2018-2019':
          save player's name
      else:
          remove player's data

For example, my dataframe looks like this

Year         Player     TM     GP
2018-2019    Joe        MTL    78
2017-2018    Joe        MTL    82
2016-2017    Joe        MTL    80
2017-2018    Jim        STL    76
2016-2017    Jim        STL    82
2018-2019    Jack       MIN    82

The result would be:

Year         Player     TM     GP
2018-2019    Joe        MTL    78
2017-2018    Joe        MTL    82
2016-2017    Joe        MTL    80 
2018-2019    Jack       MIN    82

Upvotes: 3

Views: 85

Answers (1)

piRSquared
piRSquared

Reputation: 294506

groupby.filter

df.groupby('Player').filter(lambda d: '2018-2019' in {*d.Year})

        Year Player   TM  GP
0  2018-2019    Joe  MTL  78
1  2017-2018    Joe  MTL  82
2  2016-2017    Joe  MTL  80
5  2018-2019   Jack  MIN  82

Same thing but use the values array instead of set

df.groupby('Player').filter(lambda d: '2018-2019' in d.Year.values)

Over engineered with Numpy

m = df.Year.values == '2018-2019'
i, u = pd.factorize(df.Player)
a = np.zeros(len(u), bool)
np.logical_or.at(a, i, m)

df[a[i]]

        Year Player   TM  GP
0  2018-2019    Joe  MTL  78
1  2017-2018    Joe  MTL  82
2  2016-2017    Joe  MTL  80
5  2018-2019   Jack  MIN  82

Upvotes: 5

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