How to filter Pandas dataframe based on grouped multiple column conditions?

Question

Given the following dataframe:

currency index product price
AUD      A     STOCK   $10.00
AUD      A     BOND    $10.00
AUD      B     OPTION  $11.00
AUD      B     STOCK   $12.00
USD      A     STOCK   $14.00
USD      A     BOND    $11.00
USD      A     OPTION  $19.00
USD      B     BOND    $12.00

For a given currency and given index, if that index & currency contains options, filter out stock and bond rows.

Therefore the expected output will be:

currency index product price
AUD      A     STOCK   $10.00
AUD      A     BOND    $10.00
AUD      B     OPTION  $11.00
USD      A     OPTION  $19.00
USD      B     BOND    $12.00

Asked By: youngdev

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Source

Answer 1

You can make the index & currency group with OPTION to True then filter the OPTION out with exclusive OR

m = df['product'].eq('OPTION')
m1 = m.groupby([df['currency'], df['index']]).transform('any')
out = df[~(m != m1)]
# or
out = df[(df.groupby(['currency', 'index'])['product']
          .transform(lambda col: col.eq('OPTION').any() == col.eq('OPTION')))]

print(out)

  currency index product   price
0      AUD     A   STOCK  $10.00
1      AUD     A    BOND  $10.00
2      AUD     B  OPTION  $11.00
6      USD     A  OPTION  $19.00
7      USD     B    BOND  $12.00

Answered By: Ynjxsjmh

How to filter Pandas dataframe based on grouped multiple column conditions?

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