cat() to concatenate strings in Pandas.str methods

Concatenate strings with different options .
Returns str, Series or Index

Options

Without using any separator sep = None ( default )

import pandas as pd 
my_dict={'NAME':['Ravi','Raju','Alex']}
df = pd.DataFrame(data=my_dict)
print(df.NAME.str.cat())

Output ( without any separator all are joined )

RaviRajuAlex

Let us try with separator

import pandas as pd 
my_dict={'NAME':['Ravi','Raju','Alex']}
df = pd.DataFrame(data=my_dict)
print(df.NAME.str.cat(sep=' '))

Output

Ravi Raju Alex

We can use , as separator.

print(df.NAME.str.cat(sep=','))

Output

Ravi,Raju,Alex

Using domain name and userid

import pandas as pd 
my_dict={'NAME':['Ravi','Raju','Alex'],
         'DOMAIN':['example.com','example.net','example.org'] }
df = pd.DataFrame(data=my_dict)
print(df.NAME.str.cat(df['DOMAIN'],sep='@'))

Output

0    Ravi@example.com
1    Raju@example.net
2    Alex@example.org

Handling missing data

By using option na_rep='#' we will say how to handle missing data.

import pandas as pd 
import numpy as np
my_dict={'NAME':['Ravi','Raju','Alex',np.nan],
   'DOMAIN':['example.com','example.net','example.org','example.co']}
df = pd.DataFrame(data=my_dict)
print(df.NAME.str.cat(df['DOMAIN'],sep='@',na_rep='#'))

Output

0    Ravi@example.com
1    Raju@example.net
2    Alex@example.org
3        #@example.co

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Subhendu Mohapatra

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