Task 1: Practice with Pandas

import pandas as pd

Task 1.1: Join/Merge three datasets together

Your task is to take three separate datasets (grades1a.csv, grades1b.csv, grades1c.csv -> find them in the data folder) and merge them together. You may find the documentation helpful as it contains some visualizations to help you understand the different merges and joins that are possible.

Restriction: There are no restrictions for this task.

The final dataset should look like this:

Sample Output

final_df

	Name	Student ID	Chemistry	Physics	Math
0	Lila Oni	12001	59	90	45
1	Amina Chimwala	12002	54	42	85
2	Neda Makena	12003	42	88	54
3	Shanthi Catrina	12004	66	48	64
4	Deirbhile Bhavna	12005	60	80	72
5	Ige Aifric	12006	78	73	64
6	Firouzeh Rudo	12007	64	43	67
7	Desta Jahanara	12008	82	69	70
8	Taiwo Sona	12009	63	54	80
9	Fíona Finnguala	12010	41	52	70

#Your Answer Here

Task 1.2: Combine two datasets with different keys

Your task is to merge two datasets together on the “Student ID” column in grades2a.csv and the “SID” column in the file grades2b.csv (csv files are located in the data folder).

You can do this any way you like that matches the Sample Output (there are multiple ways of doing it) but please explain how you did it (and why).

Restriction: There are no restrictions for this task.

Sample Output

	Name	Student ID	Chemistry	Physics	Math
0	Lila Oni	12001	59	90	45
1	Amina Chimwala	12002	54	42	85
2	Neda Makena	12003	42	88	54
3	Shanthi Catrina	12004	66	48	64
4	Deirbhile Bhavna	12005	60	80	72
5	Ige Aifric	12006	78	73	64
6	Firouzeh Rudo	12007	64	43	67
7	Desta Jahanara	12008	82	69	70
8	Taiwo Sona	12009	63	54	80
9	Fíona Finnguala	12010	41	52	70

#Your Answer Here

Task 1.3: Merge dataframes and keep only overlapping rows

Often it is useful to try a bunch of different merge operations on a dataset to identify what parts of the data overlap, and what parts are disparate. With the overlapping rows, you can then look at the value from the left, and the value from the right to compare them to see if there is any ambiguity if you chose to merge the dataframes.

In this question, you will use the same data as in Task 2 (grades2a.csv and grades2b.csv) and try to identify which rows are duplicates, or appear in both datasets.

Restriction: For this Task, you CANNOT rename columns.

Sample Output

	Name_x	Student ID	Chemistry_x	Physics_x	Math_x	Name_y	SID	Chemistry_y	Physics_y	Math_y
0	Shanthi Catrina	12004	66	48	64	Shanthi Catrina	12004	66	48	64
1	Deirbhile Bhavna	12005	60	80	72	Deirbhile Bhavna	12005	60	80	72
2	Ige Aifric	12006	78	73	64	Ige Aifric	12006	78	73	64

#Your Answer Here