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Python | Pandas Series.str.match ()

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Series.str can be used to access the values ​​of a series as strings and apply multiple methods to it. Series.str.match() Pandas Series.str.match() is used to determine if each line in the underlying data of a given series object to a regular expression.

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

Parameter:
pat: Regular expression pattern with capturing groups.
case: If True, case sensitive
flags: A re module flag, for example re.IGNORECASE.
na: default NaN, fill value for missing values ​​

Returns: Series / array of boolean values ​​

Example # 1: Use Series.str .match () to match the supplied regular expressions against a string in the underlying data of this 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 an index

idx < / code> = [ ’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.match () to matching the passed regular expressions with a string in the underlying data of this series object.

# matches either Tokyo or Paris

result = sr. str . match (pat = ’ (Tokyo) | (Paris) ’ )

  
# print the result

print (result)

Output:

As we can see in the output, Series.str.match () returned a series of logical their values. It contains True for those values ​​that match successfully otherwise it contains the value False .

Example # 2: Use Series.str.match () to match the supplied regular expressions against a string in the underlying data of this series object.

# import pandas as pd

import pandas as pd

 
# import re for regular expressions

import re

 
# Create a 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:

We will now use Series.str.match () to match the supplied regular expressions against a string in the underlying data of this series object.

# match capitalized groups
# followed by & # 39; i & # 39; and any other character

result = sr . str . match (pat = ’([AZ] i.)’ )

  
# print the result

print (result )

Output:

As we can see in the output, Series.str.match () returned a series of booleans. It contains True for those values ​​that match successfully, otherwise it contains False .

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