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Pandas Series: str.count() function

Series-str.count() function

The str.count() function is used to count occurrences of pattern in each string of the Series/Index.

This function is used to count the number of times a particular regex pattern is repeated in each of the string elements of the Series.

Syntax:

Series.str.count(self, pat, case=True, flags=0, na=nan, regex=True)
Pandas Series: str.count() function

Parameters:

Name Description Type/Default Value Required / Optional
pat  Valid regular expression. str Required
flags  Flags for the re module. For a complete list, int, default 0, meaning no flags Required
**kwargs  For compatibility with other string methods. Not used.   Required

Returns: Series or Index
Same type as the calling object containing the integer counts.

Example:

Python-Pandas Code:

import numpy as np
import pandas as pd
s = pd.Series(['P', 'Q', 'Abbi', 'Babi', np.nan, 'CBCA', 'bag'])
s.str.count('b')

Output:

0    0.0
1    0.0
2    2.0
3    1.0
4    NaN
5    0.0
6    1.0
dtype: float64

Example - Escape '$' to find the literal dollar sign:

Python-Pandas Code:

import numpy as np
import pandas as pd
s = pd.Series(['$', 'Q', 'A$bi', '$a$i', 'C$CA', 'bag'])
s.str.count('\$')

Output:

0    1
1    0
2    1
3    2
4    1
5    0
dtype: int64
Pandas Series: str.count() function

Example - This is also available on Index:

Python-Pandas Code:

import numpy as np
import pandas as pd
pd.Index(['P', 'P', 'Abbi', 'bag']).str.count('b')

Output:

Int64Index([0, 0, 2, 1], dtype='int64')

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