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

Pandas contains() Converting char case slice() split()

Numpy arrays Python & MySQL Python- Tutorials

Subhendu Mohapatra

Author & Instructor at plus2net

I write and maintain practical tutorials on Python, PHP, SQL, JavaScript, HTML, jQuery, and web development at plus2net. The tutorials focus on clear explanations, working examples, and code that readers can test and adapt while learning.

About the author Watch on YouTube

Connect:

Subscribe to our YouTube Channel here