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05-Final Project

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Final Project

This is your project. It accounts for maximum 20% of the final grade.

Instructions

  • You should work on this project individually.
  • This project will be partially auto-graded and partially manually graded: the auto-grading will check that your answers to the question is correct (or close to be correct) and the manual grading will check your python coding and visualization style. If your submission fails the auto-grade, you will get 0.

Note

  • Write your code after you see # YOUR CODE HERE
  • Read the instruction of each question. You have a limited time to submit: May 24th 11:59 PM. Only your last submission counts.
  • Copying the solution of other student is forbidden.
  • For each example, the symbol -> indicates the value the function should return.
  • After the deadline, submission is only possible by email attachment (.ipynb file) to your TA and cc your instructor. Late submission will be penalized (up to 100%, if late > 72 hours).
ZH

期末项目

这是你的项目,它占最终成绩的最高20%。

说明

  • 你应该个人完成这个项目。
  • 这个项目将部分自动评分和部分手动评分:自动评分将检查你对问题的答案是否正确(或接近正确),手动评分将检查你的Python编码和可视化风格。如果你的提交未通过自动评分,你将得到0分。

注意

  • 在看到# YOUR CODE HERE之后编写你的代码
  • 阅读每个问题的说明。你有有限的提交时间:5月24日晚上11:59。只有你的最后提交会被计算。
  • 禁止抄袭其他学生的解决方案。
  • 对于每个示例,符号“->”表示函数应该返回的值。
  • 截止日期后,只能通过电子邮件附件(.ipynb文件)提交给你的TA并抄送你的讲师。迟交将受到惩罚(最高可达100%,如果超过72小时迟交)。

Project Description

EN

Project Description

This data set CardioGoodFitness.csv is for customers of the treadmill product(s) of a retail store called Cardio Good Fitness. It contains the following variables Product, Age, Gender, Education, MaritalStatus, Usage, Fitness, Income, and Miles.

  • Product: the model of the treadmill

  • Age: in number of years, of the customer

  • Gender: of the customer

  • Education: in number of years, of the customer

  • MaritalStatus: of the customer

  • Usage: average number of times the customer wants to use the treadmill per week

  • Fitness: self rated fitness score of the customer (5 - very fit, 1 - very unfit)

  • Income: of the customer

  • Miles: expected to run

To understand products, your project focuses on the following two parts:

  1. Process and analyze the data
  2. Create visualizations

Guidelines

  • You will read instructions and hints carefully and apply your best judgement to answer the questions.
  • For each question, you need to write Python codes to answer and you need to assign the value to a variable.
  • For Part 1, you need to store your answers in the answers dictionary with keys "1", "2", "3", ... "10" and corresponding values (the answer to each question).
# You will need to import these two packages.
import pandas as pd
import matplotlib.pyplot as plt
# This is your dataset.
data = pd.read_csv("CardioGoodFitness.csv")
data.head()

Questions (50 points)

EN

Run preliminary data analysis on the dataset to answer the following questions:

  1. How many records in the dataset?

  2. How many unique products in the dataset?

  3. What is the largest age difference in the dataset (maximun age - minimum age)?

  4. What is ratio between 'Female' and 'Male' in the column 'Gender' (Female/Male)?

  5. What is the median year of education of the customers in the dataset?

  6. How many of the customers are not single?

  7. How frequent do customers want to use the treadmill per week in average?

  8. What is the percentage of customers self rated to be very fit (in float, e.g., 0.12)?

  9. What is the highest income in the dataset?

  10. How many customers expected to run farther than 150 miles (150 not included)?

Write all your answers in a dictionary named answers. This dictionary has keys "1", "2", "3", ... "10" and values a1, a2, a3, ... a10 respectively. (e.g., a1 is the variable storing the answer to question 1)

Visualization (50 points)

EN

You should create plots using the dataset. Your python coding, visualization style, and the appearance of the plots will be manually graded.

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