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)
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
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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