Outliers#

TODO

Instructions#

  1. Download the csv dataset in the Data Set section and place it in the Linux Files folder on your folder system where you save your .py scripts.

  2. Create a Python .py script named NAME_project_five.py in your Linux Files folder on your file system. You can do this by opening an IDLE session, creating a new file and then saving it. Replace NAME with your name.

  3. Create a docstring at the very top of the script file. Keep all written answers in this area of the script.

  4. Read the Background section.

  5. Read the Loading In Data section.

  6. Load in the data from the .csv file using the technique outlined in the Loading In Data section.

  7. Perform all exercises and answer all questions in the Project section. Label your script with comments as indicated in the instructions of each problem.

  8. When you are done,zip your script and the csv file in a zip file named NAME_project_five.zip

  9. Upload the zip file to the Google Classroom Project Five Assignment.

Loading In Data#

The following code snippet will load in a CSV spreadsheet named example.csv, parse it into a list and then print it to screen, assuming that CSV file is saved in the same folder as your script. Modify this code snippet to fit the datasets in this lab and then use it to load in the provided datasets in Datasets section.

import csv

# read in data
with open('example.csv') as csv_file:
    csv_reader = csv.reader(csv_file)
    raw_data = [ row for row in csv_reader ]

# separate headers from data
headers = raw_data[0]
columns = raw_data[1:]

# grab first column from csv file and ensure it's a number (not a string)
column_1 = [ float(row[0]) for row in columns ]

print(column_1)

Background#

TODO

Project#

TODO

Data Set#

TODO