CODEWITHSUNDEEP
pythonpandaspandas-groupby
Gidon
Gidon

Reputation: 537

pandas select specific groups

I have a dataframe with an ID column and a measurement column

ID measurement
1 A
1 B
1 C
1 D
2 A
2 B
2 C
2 D
3 A
4 A
4 B
4 C
4 D
4 E

I want to select only rows which have full measurements (A-D) per ID and remove rows which either have fewer (for example ID 3) or more measurements (for example ID 4) per ID.

Is there an efficient way to achieve that?

Upvotes: 1

Views: 572

Answers (2)

Zero
Zero

Reputation: 76927

Using transform

In [1001]: df[df.groupby('ID')['measurement'].transform(lambda x: set(x) == set('ABCD'))]
Out[1001]:
   ID measurement
0   1           A
1   1           B
2   1           C
3   1           D
4   2           A
5   2           B
6   2           C
7   2           D

Upvotes: 1

MaxU - stand with Ukraine
MaxU - stand with Ukraine

Reputation: 210852

In [92]: df.groupby('ID').filter(lambda x: set(x['measurement']) == set('ABCD'))
Out[92]:
   ID measurement
0   1           A
1   1           B
2   1           C
3   1           D
4   2           A
5   2           B
6   2           C
7   2           D

Upvotes: 2

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