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Write a function to concatenate two DataFrames by the clumns 'B' of first DataFrame. And if there are other columns with same label, for example C in the sample dataframes of df5 and df6, providing the suffix labels for data sources, i.e., 'C_firs...

Sure! Here is the function that concatenates two DataFrames based on the ‘B’ column and handles duplicate columns with suffix labels:

import pandas as pd

def concatenate_dataframes(df1, df2):
    merged = pd.merge(df1, df2, on='B', suffixes=('_first', '_second'))
    return merged

# Sample Input
df5 = make_df('ABC', [1, 2])
df6 = make_df('BCD', [1, 2])
print('Dataframes before concatenation:')
display('df5', 'df6')

# Concatenate two DataFrames by the sample index 'B'
df_con = concatenate_dataframes(df5, df6)

print('Concatenated DataFrame:')
display(df_con)

To select values with row index 1 from df_con and return it as df_sel, you can use the following function:

def select_idx(df_con):
    df_sel = df_con.loc[1]
    return df_sel

# Select values with row index 1 from df_con
df_se1 = select_idx(df_con)

print('Values after selection:')
display(df_se1)

You can modify and write your own tests according to your requirements.


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