Question

(adf, bdf, how='inner', on='col1')

1) Inner join on column 'col1'
2) Outer join on column 'col1'
3) Left join on column 'col1'
4) Right join on column 'col1'

Answer 1

The student's question refers to merging two dataframes in a programming context, specifically requesting an inner join on 'col1'. An inner join will combine rows with matching values in the 'col1' column from both dataframes.

Step-by-step explanation:

The student's question involves a syntax that is commonly associated with programming, more precisely with data manipulations in languages such as Python using libraries like Pandas. The syntax described (adf, bdf, how='inner', on='col1') indicates options for merging two dataframes. Depending on the value of the parameter how, different types of joins can be executed:

• Inner join: Merges rows from both dataframes where there are matching values in the 'col1' column of both dataframes.
• Outer join: Combines all rows from both dataframes, filling in missing values with NaN where necessary.
• Left join: Includes all rows from the 'left' dataframe (the first mentioned) and the matched rows from the 'right' dataframe.
• Right join: Includes all rows from the 'right' dataframe (the second mentioned) and the matched rows from the 'left' dataframe.

The specific operation requested in the question calls for an inner join on the column 'col1', which means that only the rows that have matching data in 'col1' in both dataframes will be included in the resulting dataframe.