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Python - Merge Pandas DataFrame with Outer Join
To merge Pandas DataFrame, use the merge() function. The outer join is implemented on both the DataFrames by setting under the “how” parameter of the merge() function i.e. −
how = “outer”
At first, let us import the pandas library with an alias −
import pandas as pd
Let us create DataFrame1 −
dataFrame1 = pd.DataFrame(
{
"Car": ['BMW', 'Lexus', 'Audi', 'Mustang', 'Bentley', 'Jaguar'],
"Units": [100, 150, 110, 80, 110, 90]
}
)Let us 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 "outer" in "how" parameter implements Outer Join −
mergedRes = pd.merge(dataFrame1, dataFrame2, on ='Car', how ="outer")
Example
Following is the 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', 'Tesla', 'Mustang', 'Mercedes', 'Jaguar'],
"Reg_Price": [7000, 1500, 5000, 8000, 9000, 6000]
}
)
print"\nDataFrame2 ...\n",dataFrame2
# merge DataFrames with common column Car and "outer" in "how" parameter implements Outer Join
mergedRes = pd.merge(dataFrame1, dataFrame2, on ='Car', how ="outer")
print"\nMerged dataframe with outer 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 outer join... Car Units Reg_Price 0 BMW 100.0 7000.0 1 Lexus 150.0 1500.0 2 Audi 110.0 NaN 3 Mustang 80.0 8000.0 4 Bentley 110.0 NaN 5 Jaguar 90.0 6000.0 6 Tesla NaN 5000.0 7 Mercedes NaN 9000.0
Updated on: 14-Sep-2021
1K+ Views
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