How to Use rbind in Python?

In this article, we will discuss rbind() in python.

Method 1: Use rbind() function with equal columns

Here we have to take 2 dataframes with equal columns and apply concat() function. This will combine the rows based on columns.

Syntax:

pandas.concat([dataframe1, dataframe2])

where

• dataframe1 is the first dataframe
• dataframe2 is the second dataframe

Example:

Python3

# import pandas module
import pandas as pd

# create first dataframe
data1 = pd.DataFrame({'fruits': ['apple', 'guava', 'mango', 'banana'],
                      'cost': [34, 56, 65, 45]})

# create second dataframe
data2 = pd.DataFrame({'fruits': ['cuatard apple', 'guava', 'mango', 'papaya'],
                      'cost': [314, 86, 65, 51]})

# concat two columns
pd.concat([data1, data2])

Output:

Method 2: Use rbind() function with unequal columns 

Here the two dataframes columns are not equal, In this scenario, the unmatched column will get NAN replaced rows in its column.

Syntax:

pandas.concat([dataframe1, dataframe2])

where,

• dataframe1 is the first dataframe
• dataframe2 is the second dataframe

Example:

Python3

# import pandas module
import pandas as pd

# create first dataframe with 2 columns
data1 = pd.DataFrame({'fruits': ['apple', 'guava', 'mango', 'banana'],
                      'cost': [34, 56, 65, 45]})

# create second dataframe with 3 columns
data2 = pd.DataFrame({'fruits': ['cuatard apple', 'guava', 'mango', 'papaya'],
                      'cost': [314, 86, 65, 51],
                      'city': ['guntur', 'tenali', 'ponnur', 'hyd']})

# concat two columns
pd.concat([data1, data2])

Output:

Here we observed that the index of the rows again starts from 0, in order to avoid this, we have to use the .reset_index() method. This will reset the index of the new dataframe.

Syntax:

pandas.concat([dataframe1, dataframe2]).reset_index(drop=True)

Example:

Python3

# import pandas module
import pandas as pd

# create first dataframe with 2 columns
data1 = pd.DataFrame({'fruits': ['apple', 'guava', 'mango', 'banana'],
                      'cost': [34, 56, 65, 45]})

# create second dataframe with 3 columns
data2 = pd.DataFrame({'fruits': ['cuatard apple', 'guava', 'mango', 'papaya'],
                      'cost': [314, 86, 65, 51],
                      'city': ['guntur', 'tenali', 'ponnur', 'hyd']})

# concat two columns
pd.concat([data1, data2]).reset_index(drop=True)

Output: