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Concat Function In Pandas






Purpose





Example


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',
    'Nestl\xc3\xa9',
    'Verizon',
    'Volkswagen',
    'Nestl\xc3\xa9',
    ], '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])




Picture showing how the concat function is used to combine two data frames in pandas



Concat Row-Wise




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',
    'Nestl\xc3\xa9',
    'Verizon',
    'Volkswagen',
    'Nestl\xc3\xa9',
    ], '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)




Picture showing how to perform row-wuse concatenation of data frames in pandas



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

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