also let me know, which version are you using and running this code on: python 2.7.3 or other.

Send your complete code packet, so that I can check what exactly the issues is.

I'm getting an error while running code saying it cant find df_new.What should I do?

df_new is a variable that store a dataframe.And pandas provides various facilities for easily combining together Series, DataFrame, and Panel objects with various kinds of set logic for the indexes and relational algebra functionality in the case of join / merge-type operations.And You can concatenate a mix of Series and DataFrames. The Series will be transformed to DataFrames with the column name as the name of the Series in data frame.

@siva.singh

what is df_new in your code?

Hello Kajal,

The below code will help you in solving your issue:

#import modules

import datetime as dt
import pandas as pd
import scipy as s

#Create a dataframe
raw_data = {
        'subject_id': ['1', '2', '3', '4', '5'],
        'first_name': ['Shiva ', 'Rahul', 'Raghu', 'Akhi', 'Aaman'], 
        'last_name': ['Thakur', 'singh', 'singh', 'singh', 'singh']}
df_a = pd.DataFrame(raw_data, columns = ['subject_id', 'first_name', 'last_name'])
df_a

#Create a second dataframe
raw_data = {
        'subject_id': ['4', '5', '6', '7', '8'],
        'first_name': ['Viren', 'Brijesh', 'Sachin', 'Rakesh', 'Sumit'], 
        'last_name': ['kud', 'Mehra', 'singh', 'Pant', 'singh']}
df_b = pd.DataFrame(raw_data, columns = ['subject_id', 'first_name', 'last_name'])
df_b

#Create a third dataframe
raw_data = {
        'subject_id': ['1', '2', '3', '4', '5', '7', '8', '9', '10', '11'],
        'test_id': [51, 15, 15, 61, 16, 14, 15, 1, 61, 16]}
df_n = pd.DataFrame(raw_data, columns = ['subject_id','test_id'])
df_n

#Join the two dataframes along rows

pd.concat([df_a, df_b], axis=1)

#Merge two dataframes along the subject_id value

pd.merge(df_new, df_n, on='subject_id')

#Merge two dataframes with both the left and right dataframes using the subject_id key

pd.merge(df_new, df_n, left_on='subject_id', right_on='subject_id')
#Join the two dataframes along columns
pd.concat([df_a, df_b], axis=1)

#Merge two dataframes along the subject_id value
pd.merge(df_new, df_n, on='subject_id')

#Merge two dataframes with both the left and right dataframes using the subject_id key
pd.merge(df_new, df_n, left_on='subject_id', right_on='subject_id')

....