Python | Pandas Series.str.contains()

Series.str can be used to access the values of the series as strings and apply several methods to it. Pandas Series.str.contains() function is used to test if pattern or regex is contained within a string of a Series or Index. The function return boolean Series or Index based on whether a given pattern or regex is contained within a string of a Series or Index.

Syntax: Series.str.contains(pat, case=True, flags=0, na=nan, regex=True)

Parameter :
pat : Character sequence or regular expression.
case : If True, case sensitive.
flags : Flags to pass through to the re module, e.g. re.IGNORECASE.
na : Fill value for missing values.
regex : If True, assumes the pat is a regular expression.

Returns : Series or Index of boolean values

Example #1: Use Series.str.contains() function to find if a pattern is present in the strings of the underlying data in the given series object.

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# importing pandas as pd
import pandas as pd
  
# importing re for regular expressions
import re
  
# Creating the Series
sr = pd.Series(['New_York', 'Lisbon', 'Tokyo', 'Paris', 'Munich'])
  
# Creating the index
idx = ['City 1', 'City 2', 'City 3', 'City 4', 'City 5']
  
# set the index
sr.index = idx
  
# Print the series
print(sr)

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Output :

Now we will use Series.str.contains() function to find if a pattern is contained in the string present in the underlying data of the given series object.

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# find if 'is' substring is present
result = sr.str.contains(pat = 'is')
  
# print the result
print(result)

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Output :

As we can see in the output, the Series.str.contains() function has returned a series object of boolean values. It is True if the passed pattern is present in the string else False is returned.

Example #2 : Use Series.str.contains() function to find if a pattern is present in the strings of the underlying data in the given series object. Use regular expression to find pattern in the strings.

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# importing pandas as pd
import pandas as pd
  
# importing re for regular expressions
import re
  
# Creating the Series
sr = pd.Series(['Mike', 'Alessa', 'Nick', 'Kim', 'Britney'])
  
# Creating the index
idx = ['Name 1', 'Name 2', 'Name 3', 'Name 4', 'Name 5']
  
# set the index
sr.index = idx
  
# Print the series
print(sr)

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Output :

Now we will use Series.str.contains() function to find if a pattern is contained in the string present in the underlying data of the given series object.

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# find if there is a substring such that it has
# the letter 'i' follwed by any small alphabet.
result = sr.str.contains(pat = 'i[a-z]', regex = True)
  
# print the result
print(result)

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Output :

As we can see in the output, the Series.str.contains() function has returned a series object of boolean values. It is True if the passed pattern is present in the string else False is returned.



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