20. A data science intern is confused on which method to use to combine 2 or more pandas objects. She has asked for help from you. Which of the following statements about merge and join are correct? Select all correct.Join combines 2 or more pandas objects horizontally while merge combines exactly two dataframes horizontallyBoth merge and join Handles duplicate values on the joining columns or index by performing a cartesian productBoth merge and join Aligns the calling DataFrame's column(s) or index with the other object's index (and not the columns)Join defaults to left join with options for inner, outer, and right while merge defaults to inner join with options for left, outer, and right

19. A data analyst wants to combine multiple dataframes using the concat found in pandas. He is looking for advice on how the concat works. Which of the following are True about the concat found in pandas? - A. Combines two or more pandas objects vertically or horizontally- B. Aligns only on the index- C. Errors whenever a duplicate appears in the index- D. Defaults to outer join with the option for inner join1 of the 4 listed2 of the 4 listed3 of the 4 listed4 of the 4 listed0 of the 4 listed

Which of the following can be used to merge two data frames by common columns?concatenate()bind()join()merge()

Given the following code:df1 = pd.DataFrame([100, 200, 300, 400],index=['a', 'b', 'c', 'd'],columns=['A'])df2 = pd.DataFrame([200, 150, 50],index=['f', 'b', 'c'],columns=['B'])a. Create the le� join of df1 and df2 [2 marks]Ans:b. Create the right join of df1 and df2 [2 marks]Ans:c. Create the inner join of df1 and df2 [2 marks]Ans:d. Create the outer join of df1 and df2 [2 marks]Ans:

What will the following code do?employee_all_df = pd.concat(employee_names_df,employee_age_df, on = 'Employee ID')A.Generate an error message.B.Concatenate both DataFrames using Employee ID.C.Merge both DataFrames using Employee ID.

Question 1Fill in the blank: To combine rows from two or more tables based on a _____ column, data professionals use the SQL JOIN clause.1 point