import numpy as np
import pandas as pd


# Create a dictionary
dict1 = {
        'company':['Google', 'Microsoft', 'Apple', 'Google', 'Microsoft', 'Apple'],
        'year': [2017, 2017, 2017, 2018, 2018, 2018],
        'Profit':[20000,40000,60000,80000,70000,50000]
       }

dict2 = {
        'company':['Disney', 'Walmart', 'AT&T', 'Disney', 'Walmart', 'AT&T'],
        'year': [2017, 2017, 2017, 2018, 2018, 2018],
        'Profit':[10000,20000,30000,40000,50000,60000]
       }

dict3 = {
        'company':['Verizon', 'Volkswagen', 'Nestlé', 'Verizon', 'Volkswagen', 'Nestlé'],
        'year': [2017, 2017, 2017, 2018, 2018, 2018],
        'Profit':[30000,20000,30000,40000,60000,60000]
       }


# Create a dataframe
df1 = pd.DataFrame(dict1, index=[0,1,2,3,4,5])
df2 = pd.DataFrame(dict2, index=[6,7,8,9,10,11])
df3 = pd.DataFrame(dict3, index=[12,13,14,15,16,17])

# Concat
pd.concat([df1,df2,df3])











import numpy as np
import pandas as pd


# Create a dictionary
dict1 = {
        'company':['Google', 'Microsoft', 'Apple', 'Google', 'Microsoft', 'Apple'],
        'year': [2017, 2017, 2017, 2018, 2018, 2018],
        'Profit':[20000,40000,60000,80000,70000,50000]
       }

dict2 = {
        'company':['Disney', 'Walmart', 'AT&T', 'Disney', 'Walmart', 'AT&T'],
        'year': [2017, 2017, 2017, 2018, 2018, 2018],
        'Profit':[10000,20000,30000,40000,50000,60000]
       }

dict3 = {
        'company':['Verizon', 'Volkswagen', 'Nestlé', 'Verizon', 'Volkswagen', 'Nestlé'],
        'year': [2017, 2017, 2017, 2018, 2018, 2018],
        'Profit':[30000,20000,30000,40000,60000,60000]
       }


# Create a dataframe
df1 = pd.DataFrame(dict1, index=[0,1,2,3,4,5])
df2 = pd.DataFrame(dict2, index=[6,7,8,9,10,11])
df3 = pd.DataFrame(dict3, index=[12,13,14,15,16,17])

# Concat
pd.concat([df1,df2,df3], axis = 1)







Posted By  -  Karan Gupta
 
Posted On  -  Friday, April 26, 2019

Query/Feedback


Your Email Id  
 
Subject 
 
Query/FeedbackCharacters remaining 250