Count common occurrence of elements in Pandas dataframe

Asked Aug 21 '19 at 10:51

Active Aug 21 '19 at 10:51

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I have a dataframe of the form :

element1  |  element2  |  element3
  'dog'        'cat'         'pig'
  'dog'        'weasel'      'parrot'
  'dog'        'cat'         'pig'
  'cat'        'dog'         'pig'
  'buffalo'    'cow'         'snake'

where all elements are strings. How can I count the number of occurrences of each triplet (from every row) and set it as an additional column ? The desired result should be:

element1  |  element2  |  element3   |  count  |
  'dog'        'cat'         'pig'         2
  'dog'        'weasel'      'parrot'      1
  'cat'        'dog'         'pig'         1
  'buffalo'    'cow'         'snake'       1

where duplicate rows are also removed.

asked Aug 21 '19 at 10:51

Qubix

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Check [this](https://stackoverflow.com/a/32801170/2901002) – jezrael Aug 21 '19 at 10:52
@jezrael df[['col1', 'col2', 'col3', 'col4']].groupby(['col1', 'col2']).agg(['count']) ? This? I will try it now. – Qubix Aug 21 '19 at 10:54
Ok, so use `df1 = df.groupby(['element1','element2','element3']).size().reset_index(name='count')` – jezrael Aug 21 '19 at 10:55
1

oh, ok, that works. Thanks. :) – Qubix Aug 21 '19 at 10:58

Count common occurrence of elements in Pandas dataframe

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