Stack 4 - Week 3 - Core 002 - Hypothesis Testing with Insurance Data

For this assignment, we will be working with the US Health Insurance Dataset from Kaggle.

We have been asked to use our hypothesis testing skills to answer the following questions:

- Q1. Do smokers have higher insurance charges than non-smokers?
- Q2. Are men more likely to smoke than women?
- Q3. Do different regions have different charges, on average?

For each question, make sure to:

1. State your Null Hypothesis and Alternative Hypothesis

2. Select the correct test according to the data type and number of samples

3. Test the assumptions of your selected test.

4. Execute the selected test, or the alternative test (if you do not meet the assumptions)

5. Interpret your p-value and reject or fail to reject your null hypothesis 

6. Show a supporting visualization that helps display the result

My Submission

Stack 4 - Week 3 - Core 001 - Describing Distributions (Core)

In this assignment, you will be analyzing & visualizing several features in the Medical Dataset.

• The features to analyze: 

  • VitD_levels

  • Doc_visits

  • TotalCharge

For each feature listed:

1. Plot a histogram with a kde (kernel density estimate)

   1. Add a line for the mean (red)

   2. Add a line for the median (green)

   3. Add a line for for +1 std from the mean (black)

   4. Add a line for the - 1 std from the mean (black)

   5. Highlight the range between +1 and =1 std (yellow)

2. Answer the following questions:
   

   • Is it Discrete or Continuous?

   • Does it have a skew? If so, which direction (+/-)

   • What type of kurtosis does it display? (Mesokurtic, Leptokurtic, Platykurtic)

My Submission

Stack 4 - Week 2 - Core 002 - Applying Advanced Transformations

The Data

You will be working with a heavily modified version of the Superheroes dataset from Kaggle.

The dataset includes two csv's:

• superhero_info.csv:

  • Contains Name, Publisher, Demographic Info, and Body measurements.

• superhero_powers.csv:

  • Contains Hero name and list of powers

The Task

Your task is two-fold:

I. Clean the files and combine them into one final DataFrame.

• This dataframe should have the following columns:

  • Hero (Just the name of the Hero)

  • Publisher

  • Gender

  • Eye color

  • Race

  • Hair color

  • Height (numeric)

  • Skin color

  • Alignment

  • Weight (numeric)

  • Plus, one-hot-encoded columns for every power that appears in the dataset. E.g.:

    • Agility

    • Flight

    • Superspeed

    • etc.

Hint: There is a space in "100 kg" or "52.5 cm"

II. Use your combined DataFrame to answer the following questions.

1. Compare the average weight of super powers who have Super Speed to those who do not.

2. What is the average height of heroes for each publisher?

(Source)

Submit your notebook or a link to a GitHub repository with your work.

Complete Project

My Submission

Stack 4 - Week 1 - Core 001 - Efficient Yelp API Calls

For this assignment, you will be working with the Yelp API.

As before, you will use the Yelp API to search your favorite city for a cuisine type of your choice.

Extract all of the results from your search and compile them into one dataframe using a for loop as shown in the lesson "Code for Efficient API Extraction"

Save your notebook, commit the change to your repository and submit the repository URL for this assignment.

My Github Submission