Merge Pandas DataFrame with a common column

To merge two Pandas DataFrame with common column, use the merge() function and set the ON parameter as the column name.

At first, let us import the pandas library with an alias −

import pandas as pd

Let us create the 1^st DataFrame −

dataFrame1 = pd.DataFrame(
   {
      "Car": ['BMW', 'Lexus', 'Audi', 'Mustang', 'Bentley', 'Jaguar'],"Units": [100, 150, 110, 80, 110, 90]
   }
)

Next, create the 2^nd DataFrame −

dataFrame2 = pd.DataFrame(
   {
      "Car": ['BMW', 'Lexus', 'Audi', 'Mustang', 'Mercedes', 'Jaguar'],"Reg_Price": [7000, 1500, 5000, 8000, 9000, 6000]

   }
)

Now, merge the two DataFrames with a column column “Car” −

mergedRes = pd.merge(dataFrame1, dataFrame2, on ='Car')

Example

Following is the complete code −

import pandas as pd

# Create DataFrame1
dataFrame1 = pd.DataFrame(
   {
      "Car": ['BMW', 'Lexus', 'Audi', 'Mustang', 'Bentley', 'Jaguar'],"Units": [100, 150, 110, 80, 110, 90]
   }
)

print"DataFrame1 ...\n",dataFrame1

# Create DataFrame2
dataFrame2 = pd.DataFrame(
   {
      "Car": ['BMW', 'Lexus', 'Audi', 'Mustang', 'Mercedes', 'Jaguar'],"Reg_Price": [7000, 1500, 5000, 8000, 9000, 6000]

   }
)

print"\nDataFrame2 ...\n",dataFrame2

# merge DataFrames with common column Car
mergedRes = pd.merge(dataFrame1, dataFrame2, on ='Car')
print"\nMerged data frame with common column...\n", mergedRes

Output

This will produce the following output −

DataFrame1 ...
       Car   Units
0      BMW     100
1    Lexus     150
2     Audi     110
3  Mustang      80
4  Bentley     110
5   Jaguar      90

DataFrame2 ...
        Car   Reg_Price
0       BMW        7000
1     Lexus        1500
2      Audi        5000
3   Mustang        8000
4  Mercedes        9000
5    Jaguar        6000

Merged data frame with common column...
       Car   Units   Reg_Price
0      BMW     100        7000
1    Lexus     150        1500
2     Audi     110        5000
3  Mustang      80        8000
4   Jaguar      90        6000