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Pandas Series string | contains method

schedule Aug 12, 2023
Last updated
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Pandas Series str.contains(~) method checks whether or not each value of the source Series contains the specified substring or regex pattern.

Parameters

1. pat | string

The substring or regex to check for.

2. case | boolean | optional

If True, then check is case sensitive. By default, case=True.

3. flags | int | optional

A rule, which is available in Python's re module, to respect (e.g. re.IGNORECASE). By default, flags=0, that is, no rule is set.

4. na | scalar | optional

The value to replace NaN. By default, NaN are left as is.

5. regex | boolean | optional

Whether or not pat should be parsed as regex. By default, regex=True.

Return Value

A Series of booleans, where True indicates entries that contain the specified substring or regex pattern.

Examples

To check for values in a Series that contain a specific substring:

s = pd.Series(["abc","abd","efg"])
s.str.contains("ab", regex=False)
0 True
1 True
2 False
dtype: bool

Using regex

Since regex=True by default, we can just provide the regex directly:

s = pd.Series(["a2a","a5a","aaa"])
s.str.contains("\d")
0 True
1 True
2 False
dtype: bool

Here, we are checking for values that contain a single digit.

Specifying na

We can fill NaN values by providing the na parameter like so:

s = pd.Series(["abc",np.nan])
s.str.contains("a", na="**")
0 True
1 **
dtype: object
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Published by Isshin Inada
Edited by 0 others
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