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https://colab.research.google.com/drive/1GYkzFwWjE_b5GMQtRwOxAf-AB9Cm3Wwk
https://colab.research.google.com/drive/17c2IdXdq5fH6TEcRyZYwvZAqAy1HNvo2
https://colab.research.google.com/drive/1g5GJEWoTyonEDc58jVAZlJ-xgwgGgL_p
https://colab.research.google.com/drive/1GeqlNQoWhIu5C5rVLIw_3CyDKXh2EGO1
https://colab.research.google.com/drive/1okgby4qNAkV3G9ZGAg-x7P77FzRyEw8y


New Advogato Features New Site Features Quick New Content Updating – Where you are, you’re seen Categories Categories Search 4GW Search 4GW uses algorithms to help users find what they’re looking for.. Badges Badges People who liked this also liked… Search 4GW – and other Beta software, is a search engine for OS X that uses algorithms to help users find the software they’re looking for on your computer. It doesn’t just search your Home folder, but everything that is installed on your computer.Q: Selecting rows from column based on a given criteria in pandas If I have a dataset like this: +—–+———–+ | id | proptype | +—–+———–+ | 1 | A | | 2 | A | | 3 | B | | 4 | B | | 5 | B | +—–+———–+ How would I select the rows with the same proptype? In this case, there are two row, so I should get: +—–+———–+ | id | proptype | +—–+———–+ | 2 | A | | 5 | B | +—–+———–+ I know that I can make a list and use the.isin(list) function to select this condition, but I was wondering if there was a better way? A: You can use groupby and having with id converted to numeric and chained with groupby.transform: m = df[‘proptype’].map(lambda x: x.astype(int).astype(str)) print (m) 0 A 1 A 2 B 3 B Name: proptype, dtype: object print (m.groupby(m).transform(‘sum’).ne(0).sum()) id 2 1 5 1 dtype: int64 a2fa7ad3d0


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