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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