merge a dataframe row values from another row values in python

To merge a DataFrame row values from another row values, you can use the pandas merge() function.

Assuming you want to merge values from row "B" to row "A" in a DataFrame called df, you can use the following code:

main.py
import pandas as pd

# sample data
data = {'A': [1, 2, 3], 'B': [4, 5, 6]}
df = pd.DataFrame(data)

# merge row 'B' to row 'A'
df.loc['A'] = pd.concat([df.loc['A'], df.loc['B']])
df = df.drop('B')

print(df)
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This code first creates a sample DataFrame df with two rows, "A" and "B". Then, it merges the values of row "B" to row "A" using pd.concat(), finally drops row "B" with df.drop(). The resulting DataFrame will have only row "A" with the merged values:

main.py
   A  B
A  1  2
A  3  4
A  5  6
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Note that this code assumes that both rows "A" and "B" have the same column names in the DataFrame. If they have different column names, you may need to adjust the code accordingly.