How to count the number of occurrences of elements in a pandas data frame column in python ?

Published: April 15, 2020

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Examples of how to count the number of occurrences of elements in a pandas data frame column in python

Create a simple date frame with pandas

Let's create a simple data frame called df:

>>> import pandas as pd
>>> import numpy as np

>>> df = pd.DataFrame(columns=['target','a','b'])

>>> df = df.append({"target": 0, "a":  "no", "b":  "M"}, ignore_index=True)
>>> df = df.append({"target": 1, "a":  "yes", "b":  "F"}, ignore_index=True)
>>> df = df.append({"target": 1, "a":  "yes", "b":  "M"}, ignore_index=True)
>>> df = df.append({"target": 1, "a":  "no", "b":  "F"}, ignore_index=True)
>>> df = df.append({"target": 0, "a":  "no", "b":  "F"}, ignore_index=True)

>>> df

returns

  target    a  b
0      0   no  M
1      1  yes  F
2      1  yes  M
3      1   no  F
4      0   no  F

Get the number of occurrences

To get the number of occurrences of elements in the column 'target', a solution is to use the function value_counts

>>> df['target'].value_counts()

returns

1    3
0    2

meaning value 1 (has 3 occurrences in the column) and 0 (has 2 occurrences in the column).

Another solution:

>>> sub_df = df[ df['target'] == 0 ]
>>>  sub_df 
  target   a  b
0      0  no  M
4      0  no  F
>>> len(sub_df) 
2

References