Pandas

Overview

Due:

11:00pm, Friday October 23, 2020

Max grace days:

2

The purpose of this assignment is to use Jupyter notebooks and basic Pandas data manipulation.

Description

Make a Jupyter notebook named main.ipynb that reads in the file toycars.csv into a Pandas DataFrame. Information about the file can be found here: https://vincentarelbundock.github.io/Rdatasets/doc/DAAG/toycars.html

Create a new DataFrame that satisfies the following criteria:

• Distance measurements must be in centimeters.
• The angle values are the index.
• The DataFrame rows are sorted in ascending order based on the index.
• There is a column for each car.
• There is a column that is the mean of the distance measurements.
• There is a column that is the standard deviation of the distance measurements.

The standard header information must be in a markdown cell. The code must be in a code cell. You must only use basic Pandas array operations to implement your solution. The use of the following functions will result in a grade of zero for the assignment: groupby, pivot, pivot_table.

Turning in the Assignment

You must turn in a file named main.ipynb. Submit the program source file to the appropriate folder on D2L.

Grading Criteria

Grading (out of 100 points):

• 20 points – correct Jupyter notebook criteria
• 20 points – correct index
• 20 points – correct distance conversion
• 20 points – correct car columns
• 10 points – correct mean column
• 10 points – correct standard deviation column