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Python - Merge Pandas DataFrame with Left Outer Join
To merge Pandas DataFrame, use the merge() function. The left outer join is implemented on both the DataFrames by setting under the “how” parameter of the merge() function i.e. −
how = “left”
At first, let us import the pandas library with an alias −
import pandas as pd
Let’s create two DataFrames to be merged −
# Create DataFrame1
dataFrame1 = pd.DataFrame(
{
"Car": ['BMW', 'Lexus', 'Audi', 'Mustang', 'Bentley', 'Jaguar'],"Units": [100, 150, 110, 80, 110, 90]
}
)
# Create DataFrame2
dataFrame2 = pd.DataFrame(
{
"Car": ['BMW', 'Lexus', 'Tesla', 'Mustang', 'Mercedes', 'Jaguar'],"Reg_Price": [7000, 1500, 5000, 8000, 9000, 6000]
}
)Merge DataFrames with common column Car and "left" in "how" parameter implements Left Outer Join −
mergedRes = pd.merge(dataFrame1, dataFrame2, on ='Car', how ="left")
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 "left" in "how" parameter implements Left Outer Join
mergedRes = pd.merge(dataFrame1, dataFrame2, on ='Car', how ="left")
print"\nMerged dataframe with left outer join...\n", mergedResOutput
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 left outer join... Car Units Reg_Price 0 BMW 100 7000.0 1 Lexus 150 1500.0 2 Audi 110 NaN 3 Mustang 80 8000.0 4 Bentley 110 NaN 5 Jaguar 90 6000.0
Updated on: 20-Sep-2021
1K+ Views
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