column bind in python pandas – concatenate columns in python pandas

Column bind in python pandas. In this Section we will learn how to concatenate columns to the python pandas dataframe using concat() Function with example i.e. how to column bind two data frames in python pandas.

Column binding is pictographically shown below

Create dataframe 1:

import pandas as pd
import numpy as np


#Create a DataFrame

d = {
'Name':['Alisa','Bobby','Cathrine','Madonna','Rocky','Sebastian','Jaqluine',
'Rahul','David'],
'Score1':[62,47,55,74,31,77,85,63,42],
'Score2':[89,87,67,55,47,72,76,79,44]}

df1 = pd.DataFrame(d)
df1

so the resultant dataframe will be

Create dataframe 2:

import pandas as pd
import numpy as np

#Create a DataFrame
d = {
'Score3':[56,86,77,45,73,62,74,89,71]}

df2 = pd.DataFrame(d)
df2

and the resultant dataframe will be

Column bind or concatenate columns of two dataframes in python pandas:

Now lets concatenate or column bind two dataframes df1 and df2. The concatenation of two dataframes are performed with  concat() function by takes two dataframes as argument, axis=1 performs the column wise operation.

import pandas pd

pd.concat([df1, df2], axis=1, ignore_index=True)

argument axis=1 binds the dataframes on column wise, so the resultant column binded dataframe will be

other related topics:

• Rename the column in pandas
• Reindex in python pandas
• Row bind in pandas
• Rank the dataframe in pandas
• Drop the duplicate row in pandas
• Find the duplicate rows in pandas
• Drop the row in pandas with conditions
• Drop or delete column in pandas

for further details on merging , joining and concatenation in pandas one can refer the documentation.