Concat the content of one or more data frames

Using Pandas concat method, we can concatenate the cotent of one ore more data frames.

Example

data1 = { 'Name': ['Krishna', 'Chamu', 'Joel'],
         'Age': [34, 25, 29],
        'City': ['Bangalore', 'Chennai', 'Hyderabad'],
        'Gender': ['Male', 'Female', 'Male'],
         'Weight': [74, 58, 85]}

data2 = { 'Name': ['Gopi', 'Sravya', "Raj"],
         'Age': [41, 52, 23],
        'City': ['Hyderabad', 'Bangalore', 'Chennai'],
        'Gender': ['Male', 'Female', 'Male'],
         'Weight': [87, 63, 79]}

df1 = pd.DataFrame(data1)
df2 = pd.DataFrame(data2)

final_df = pd.concat([df1, df2])

In the above example, I defined two dataframe df1, df2 and used concat method to concatenate the content of dtaaframes df1 and df2. 'final_df' point to below content.

      Name  Age       City  Gender  Weight
0  Krishna   34  Bangalore    Male      74
1    Chamu   25    Chennai  Female      58
2     Joel   29  Hyderabad    Male      85
0     Gopi   41  Hyderabad    Male      87
1   Sravya   52  Bangalore  Female      63
2      Raj   23    Chennai    Male      79

 As you see the above output, index numbers are preserved from original dataframes. We can ignore the indexes from original dataframes by passing the argument ignore_index to True.

 

Find the below working application.

 

concat_dfs.py

import pandas as pd

data1 = { 'Name': ['Krishna', 'Chamu', 'Joel'],
         'Age': [34, 25, 29],
        'City': ['Bangalore', 'Chennai', 'Hyderabad'],
        'Gender': ['Male', 'Female', 'Male'],
         'Weight': [74, 58, 85]}

data2 = { 'Name': ['Gopi', 'Sravya', "Raj"],
         'Age': [41, 52, 23],
        'City': ['Hyderabad', 'Bangalore', 'Chennai'],
        'Gender': ['Male', 'Female', 'Male'],
         'Weight': [87, 63, 79]}

df1 = pd.DataFrame(data1)
df2 = pd.DataFrame(data2)

print('df1')
print(df1)

print('\ndf2')
print(df2)

final_df = pd.concat([df1, df2])
print('\nDataframe after concatenating df1 and df2 data')
print(final_df)

final_df = pd.concat([df1, df2], ignore_index=True)
print('\nDataframe after concatenating df1 and df2 data by ignoring index')
print(final_df)

 

Output

df1
      Name  Age       City  Gender  Weight
0  Krishna   34  Bangalore    Male      74
1    Chamu   25    Chennai  Female      58
2     Joel   29  Hyderabad    Male      85

df2
     Name  Age       City  Gender  Weight
0    Gopi   41  Hyderabad    Male      87
1  Sravya   52  Bangalore  Female      63
2     Raj   23    Chennai    Male      79

Dataframe after concatenating df1 and df2 data
      Name  Age       City  Gender  Weight
0  Krishna   34  Bangalore    Male      74
1    Chamu   25    Chennai  Female      58
2     Joel   29  Hyderabad    Male      85
0     Gopi   41  Hyderabad    Male      87
1   Sravya   52  Bangalore  Female      63
2      Raj   23    Chennai    Male      79

Dataframe after concatenating df1 and df2 data by ignoring index
      Name  Age       City  Gender  Weight
0  Krishna   34  Bangalore    Male      74
1    Chamu   25    Chennai  Female      58
2     Joel   29  Hyderabad    Male      85
3     Gopi   41  Hyderabad    Male      87
4   Sravya   52  Bangalore  Female      63
5      Raj   23    Chennai    Male      79

 

 

 

  

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