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Combining DataFrames with Pandas

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  • Last Updated : 08 Nov, 2022
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Pandas DataFrame consists of three principal components, the data, rows, and columns. To combine these DataFrames, pandas provides multiple functions like concat() and append().

Method #1: Using concat() method

Initially, creating two datasets and converting them into dataframes. 

Python3




# import required module
import pandas as pd
 
# making  a dataset
data1 = {
    'Serial_No.': ['1', '2', '3', '4', '5'],
    'First': ['F0', 'F1', 'F2', 'F3', 'F4'],
    'Second': ['S0', 'S1', 'S2', 'S3', 'S4'],
}
 
# creating a dataframe
df1 = pd.DataFrame(data1, columns=['Serial_No.',
                                   'First',
                                   'Second'])
 
# display dataframe
df1
 
 
# making  a dataset
data2 = {
    'Serial_No.': ['6', '7', '8', '9', '10'],
    'First': ['F10', 'F11', 'F12', 'F13', 'F14'],
    'Second': ['S10', 'S11', 'S12', 'S13', 'S14'],
}
 
# creating  a dataset
df2 = pd.DataFrame(data2, columns=['Serial_No.',
                                   'First',
                                   'Second'])
 
# display dataset
df2

Output: 

Now, concatenating the two dataframes, we will use concat() to combine two dataframes. If ignore_index = True the index of df will be in a continuous order. 

Python3




# combining the two dataframes
df = pd.concat([df1, df2], ignore_index=True)
 
# display combined dataframes
df

Output:

Using keys we can specify the labels of the dataframes.

Python3




# we can also separate 2 datasets using keys
frames = [df1, df2]
df_keys = pd.concat(frames, keys=['x', 'y'])
 
# display dataframe
df_keys

Output:

Method #2: Using append() method

Initially, creating two datasets and converting them into dataframes. 

Python3




# import required module
import pandas as pd
 
# making  a dataset
data1 = {
    'Serial_No.': ['1', '2', '3', '4', '5'],
    'First': ['F0', 'F1', 'F2', 'F3', 'F4'],
    'Second': ['S0', 'S1', 'S2', 'S3', 'S4'],
}
 
# creating a dataframe
df1 = pd.DataFrame(data1, columns=['Serial_No.',
                                   'First',
                                   'Second'])
 
# display dataframe
df1
 
 
# making  a dataset
data2 = {
    'Serial_No.': ['6', '7', '8', '9', '10'],
    'First': ['F10', 'F11', 'F12', 'F13', 'F14'],
    'Second': ['S10', 'S11', 'S12', 'S13', 'S14'],
}
 
# creating  a dataset
df2 = pd.DataFrame(data2, columns=['Serial_No.',
                                   'First',
                                   'Second'])
 
# display dataset
df2

Output: 

The dataframe.append() method performs the operation of combining two dataframes similar to that of the concat() method.

Python3




# combining dataframes
result = df1.append(df2, sort=False, ignore_index=True)
 
# display combined dataframe
result

Output:


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