What is the difference between join and merge in Pandas?

Question

Suppose I have two DataFrames like so:

left = pd.DataFrame({\'key1\': [\'foo\', \'bar\'], \'lval\': [1, 2]})

right = pd.DataFrame({\'key2\': [\'foo\', \'bar         


        

Answer 1

• Join: Default Index (If any same column name then it will throw an error in default mode because u have not defined lsuffix or rsuffix))

df_1.join(df_2)

• Merge: Default Same Column Names (If no same column name it will throw an error in default mode)

df_1.merge(df_2)

• on parameter has different meaning in both cases

df_1.merge(df_2, on='column_1')

df_1.join(df_2, on='column_1') // It will throw error
df_1.join(df_2.set_index('column_1'), on='column_1')