The process to create a new column in a Pandas dataframe by utilizing two columns concurrently from a distinct dataframe is as follows:
merge()
function from Pandas.join()
function to add the column from the merged dataframe to the original dataframe. Here is an example:
import pandas as pd
# Create the first dataframe
df1 = pd.DataFrame({'A': [1, 2, 3, 4], 'B': [5, 6, 7, 8]})
# Create the second dataframe
df2 = pd.DataFrame({'A': [1, 2, 3, 4], 'C': [9, 10, 11, 12]})
# Merge the two dataframes using the common column 'A'
merged_df = pd.merge(df1, df2, on='A')
# Create a new column in the merged dataframe by applying a function to columns 'B' and 'C'
merged_df['D'] = merged_df['B'] + merged_df['C']
# Add the new column 'D' from the merged dataframe to the original dataframe 'df1'
df1 = df1.join(merged_df['D'])
# Print the result
print(df1)
This will output:
A B D
0 1 5 14
1 2 6 16
2 3 7 18
3 4 8 20
Asked: 2022-08-26 11:00:00 +0000
Seen: 12 times
Last updated: Apr 15 '22