pandas.Series.str.count

Series.str.count(pat, flags=0, **kwargs) [source]

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.

Parameters:	pat : str Valid regular expression. flags : int, default 0, meaning no flags Flags for the re module. For a complete list, see here. **kwargs For compatability with other string methods. Not used.
Returns:	counts : Series or Index Same type as the calling object containing the integer counts.

See also

re

Standard library module for regular expressions.

str.count

Standard library version, without regular expression support.

Notes

Some characters need to be escaped when passing in pat. eg. '$' has a special meaning in regex and must be escaped when finding this literal character.

Examples

>>> s = pd.Series(['A', 'B', 'Aaba', 'Baca', np.nan, 'CABA', 'cat'])
>>> s.str.count('a')
0    0.0
1    0.0
2    2.0
3    2.0
4    NaN
5    0.0
6    1.0
dtype: float64

Escape '$' to find the literal dollar sign.

>>> s = pd.Series(['$', 'B', 'Aab$', '$$ca', 'C$B$', 'cat'])
>>> s.str.count('\$')
0    1
1    0
2    1
3    2
4    2
5    0
dtype: int64

This is also available on Index

>>> pd.Index(['A', 'A', 'Aaba', 'cat']).str.count('a')
Int64Index([0, 0, 2, 1], dtype='int64')