Pandas DataFrame Merge and Join Quiz

multiplechoice

Which of the following combinations is `NOT valid` when merging dataframes?

multiplechoice

When performing a `left join` between two dataframes, which rows are included in the resulting dataframe?

multiplechoice

Which type of merge includes all rows from both dataframes and fills missing values with `NaN`?

multiplechoice

What is the purpose of the indicator parameter in the `pd.merge()` function?

multiplechoice

When merging two dataframes using an `inner join`, under what circumstances would you expect to see repeated values in the resulting merged dataframe?

multiplechoice

What is the difference between `merging on indices` and `merging on columns`?

multiplechoice

What is the result of performing an `inner join` on two dataframes with `no common values`?

multiplechoice

In pandas, what is the function used to join two dataframes based on their indexes?

multiplechoice

Which parameter of the `pd.merge()` function is used to indicate that the merge operation should be performed based on the index values of the dataframes?

multiplechoice

Which parameter of the `pd.merge()` function is used to sort the join keys lexicographically in the resulting DataFrame?

multiplechoice

To merge two dataframes `df1` and `df2` on a column named `key`, which line of code is correct?

multiplechoice

Which line of code should be used to create a cartesian product from two dataframes, while preserving the order of the left keys?

multiplechoice

Which merge operation should you use to achieve this result?

Suppose you have two dataframes, students and grades, with the following structures:

The `students` Dataframe:

	student_id	name	age
0	1	John Smith	18
1	2	Jane Doe	17
2	3	Sarah Dane	16

The `grades` Dataframe:

	student_id	subject	grade
0	1	Math	A
1	2	Science	B
2	4	English	C

You want to merge the two dataframes to get the following result:

	student_id	name	age	subject	grade
0	1	John Smith	18	Math	A
1	2	Jane Doe	17	Science	B

multiplechoice

Which merge operation should you use to achieve this result?

Suppose you have two dataframes, employees and departments, with the following structures:

The `employees` Dataframe:

	employee_id	name	department_id
0	1	John Smith	3
1	2	Jane Doe	2
2	3	Sarah Dane	3
3	4	Joe Martin	5

The `departments` Dataframe:

	department_id	department_name
0	2	Sales
1	3	Marketing
2	4	Finance

You want to merge the two dataframes to get the following result:

	employee_id	name	department_id	department_name
0	1	John Smith	3	Marketing
1	3	Sarah Dane	3	Marketing
2	2	Jane Doe	2	Sales
3	4	Joe Martin	5	nan
4	nan	nan	4	Finance

multiplechoice

Which merge operation should you use to achieve this result?

Suppose you have two dataframes, df1 and df2, with the following structures:

The `df1` Dataframe:

	left
0	foo
1	bar

The `df2` Dataframe:

	right
0	7
1	8

You want to merge the two dataframes to get the following result:

	left	right
0	foo	7
1	foo	8
2	bar	7
3	bar	8

multiplechoice

Which merge operation should you use to achieve this result?

Suppose you have two dataframes, df1 and df2, with the following structures:

The `df1` Dataframe:

	ID	Value1
0	2	100
1	3	200
2	1	300

The `df2` Dataframe:

	ID	Value2
0	3	400
1	2	500
2	1	600

You want to merge the two dataframes to get the following result:

	ID	Value1	Value2
0	1	300	600
1	2	100	500
2	3	200	400

Vidhi Shah

Project Activities

Which of the following combinations is `NOT valid` when merging dataframes?

When performing a `left join` between two dataframes, which rows are included in the resulting dataframe?

Which type of merge includes all rows from both dataframes and fills missing values with `NaN`?

What is the purpose of the indicator parameter in the `pd.merge()` function?

When merging two dataframes using an `inner join`, under what circumstances would you expect to see repeated values in the resulting merged dataframe?

What is the difference between `merging on indices` and `merging on columns`?

What is the result of performing an `inner join` on two dataframes with `no common values`?

In pandas, what is the function used to join two dataframes based on their indexes?

Which parameter of the `pd.merge()` function is used to indicate that the merge operation should be performed based on the index values of the dataframes?

Which parameter of the `pd.merge()` function is used to sort the join keys lexicographically in the resulting DataFrame?

To merge two dataframes `df1` and `df2` on a column named `key`, which line of code is correct?

Which line of code should be used to create a cartesian product from two dataframes, while preserving the order of the left keys?

Which merge operation should you use to achieve this result?

The `students` Dataframe:

The `grades` Dataframe:

Which merge operation should you use to achieve this result?

The `employees` Dataframe:

The `departments` Dataframe:

Which merge operation should you use to achieve this result?

The `df1` Dataframe:

The `df2` Dataframe:

Which merge operation should you use to achieve this result?

The `df1` Dataframe:

The `df2` Dataframe:

Vidhi Shah

Data Wrangling with Pandas

Set Operations using Sakila

LIKE Operator using World

Membership and Range Operators with World Database

Pandas DataFrame Merge and Join Quiz

Vidhi Shah

Project Activities

Which of the following combinations is `NOT valid` when merging dataframes?

When performing a `left join` between two dataframes, which rows are included in the resulting dataframe?

Which type of merge includes all rows from both dataframes and fills missing values with `NaN`?

What is the purpose of the indicator parameter in the `pd.merge()` function?

When merging two dataframes using an `inner join`, under what circumstances would you expect to see repeated values in the resulting merged dataframe?

What is the difference between `merging on indices` and `merging on columns`?

What is the result of performing an `inner join` on two dataframes with `no common values`?

In pandas, what is the function used to join two dataframes based on their indexes?

Which parameter of the `pd.merge()` function is used to indicate that the merge operation should be performed based on the index values of the dataframes?

Which parameter of the `pd.merge()` function is used to sort the join keys lexicographically in the resulting DataFrame?

To merge two dataframes `df1` and `df2` on a column named `key`, which line of code is correct?

Which line of code should be used to create a cartesian product from two dataframes, while preserving the order of the left keys?

Which merge operation should you use to achieve this result?

The students Dataframe:

The grades Dataframe:

Which merge operation should you use to achieve this result?

The employees Dataframe:

The departments Dataframe:

Which merge operation should you use to achieve this result?

The df1 Dataframe:

The df2 Dataframe:

Which merge operation should you use to achieve this result?

The df1 Dataframe:

The df2 Dataframe:

Vidhi Shah

Data Wrangling with Pandas

Set Operations using Sakila

LIKE Operator using World

Membership and Range Operators with World Database

The `students` Dataframe:

The `grades` Dataframe:

The `employees` Dataframe:

The `departments` Dataframe:

The `df1` Dataframe:

The `df2` Dataframe:

The `df1` Dataframe:

The `df2` Dataframe: