Series.str
can be used to access the values of the series as strings and apply several methods to it. Pandas
Series.str.extract()
function is used to extract capture groups in the regex pat as columns in a DataFrame. For each subject string in the Series, extract groups from the first match of regular expression
pat
.
Syntax: Series.str.extract(pat, flags=0, expand=True) Parameter : pat : Regular expression pattern with capturing groups. flags : int, default 0 (no flags) expand : If True, return DataFrame with one column per capture group. Returns : DataFrame or Series or Index
Example #1:
Use
Series.str.extract()
function to extract groups from the string in the underlying data of the given series object.
# 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)
Output :

Now we will use
Series.str.extract()
function to extract groups from the strings in the given series object.
# extract groups having a vowel followed by
# any character
result = sr.str.extract(pat = '([aeiou].)')
# print the result
print(result)
Output :

As we can see in the output, the
Series.str.extract()
function has returned a dataframe containing a column of the extracted group.
Example #2 :
Use
Series.str.extract()
function to extract groups from the string in the underlying data of the given series object.
# 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)
Output :

Now we will use
Series.str.extract()
function to extract groups from the strings in the given series object.
# extract groups having any capital letter
# followed by 'i' and any other character
result = sr.str.extract(pat = '([A-Z]i.)')
# print the result
print(result)
Output :

As we can see in the output, the
Series.str.extract()
function has returned a dataframe containing a column of the extracted group.