Change language

Python | Pandas Series.str.contains ()

|

Series.str can be used to access the values ​​of a series as strings and apply multiple methods to it. Series.str.contains() Pandas Series.str.contains() is used to check if a template is contained or a regular expression on the Series or Index string. The function returns the Boolean value Series or Index depending on whether the specified pattern or regular expression is contained in the string 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, eg 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 () to find if the pattern is present in the underlying rows of the given series object.

# import pandas as pd

import pandas as pd

 
# import re for regular expressions

import re

 
# Create series

sr = pd.Series ([ ’ New_York’ , ’Lisbon’ , ’ Tokyo’ , ’Paris’ , ’ Munich’ ])

 
# Create index

idx = [ ’ City 1’ , ’City 2’ , ’City 3’ , ’ City 4’ , ’City 5’ ]

  
# set index

sr.index = idx

 
# Print series

print (sr)

Output:

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

# find if substring & # 39; is & # 39; present

result = sr. str . contains (pat = ’ is’ )

 
# print the result

print (result)

Output:

As we can see from the output, Series.str.contains () returned a series object with boolean values ... It is True if the passed template is present in the string, otherwise False is returned.

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

# import pandas as pd

import pandas as pd

  
# import re for regular expressions

import re

 
# Create series

sr = pd.Series ([ ’Mike’ , ’Alessa’ , ’Nick’ , ’ Kim’ , ’Britney’ ])

 
# Create an index

idx = [ ’Name 1’ , ’ Name 2’ , ’Name 3’ , ’ Name 4’ , ’Name 5’ ]

 
# set index

sr.index = idx

 
# Print series

print (sr)

Output:

Now we will use Series.str.contains () so that Series.str.contains () whether the pattern is contained in a string that is present in the underlying data of this series object.

# find if there is a substring that has
# the letter "i" followed by any small alphabet.

result = sr. str . contains (pat = ’i [az ] ’ , regex = True )

 
# print the result

print (result)

Output:

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

Shop

Learn programming in R: courses

$

Best Python online courses for 2022

$

Best laptop for Fortnite

$

Best laptop for Excel

$

Best laptop for Solidworks

$

Best laptop for Roblox

$

Best computer for crypto mining

$

Best laptop for Sims 4

$

Latest questions

NUMPYNUMPY

psycopg2: insert multiple rows with one query

12 answers

NUMPYNUMPY

How to convert Nonetype to int or string?

12 answers

NUMPYNUMPY

How to specify multiple return types using type-hints

12 answers

NUMPYNUMPY

Javascript Error: IPython is not defined in JupyterLab

12 answers


Wiki

Python OpenCV | cv2.putText () method

numpy.arctan2 () in Python

Python | os.path.realpath () method

Python OpenCV | cv2.circle () method

Python OpenCV cv2.cvtColor () method

Python - Move item to the end of the list

time.perf_counter () function in Python

Check if one list is a subset of another in Python

Python os.path.join () method