Python - Merge Pandas DataFrame with Inner Join

To merge Pandas DataFrame, use the merge() function. The inner join is implemented on both the DataFrames by setting under the “how” parameter of the merge() function i.e. −

how = “inner”

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

import pandas as pd

Create DataFrame1 −

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

Now, create DataFrame2 −

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

   }
)

Merge DataFrames with a common column Car and "inner" in "how" parameter implements Inner Join −

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

Example

Following is the code −

#
# Merge Pandas DataFrame with Inner Join
#

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', 'Tesla', 'Mustang', 'Mercedes', 'Jaguar'],
      "Reg_Price": [7000, 1500, 5000, 8000, 9000, 6000]

   }
)

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

# merge DataFrames with common column Car and "inner" in "how" parameter implements Inner Join
mergedRes = pd.merge(dataFrame1, dataFrame2, on ='Car', how ="inner")
print"\nMerged dataframe with inner join...\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     Tesla       5000
3   Mustang       8000
4  Mercedes       9000
5    Jaguar       6000

Merged dataframe with inner join...
       Car   Units   Reg_Price
0      BMW    100      7000
1    Lexus    150      1500
2  Mustang     80      8000
3   Jaguar     90      6000