Project 2 - K8 Coding

K-8 Coding #2

Here is a link to my folder that contains this week's work (Jupyter Notebook, csv file):
Work Folder (use Py3 environment)

This week I continued working on Peter's survey data that he collected from k-8 coding teachers across the globe.

My tasks included:
1) Clean up my notebook from last week to make it more viewer friendly.
2) Prepare data for visualization. I ended up "stacking" my data because I couldn't get any of my pie charts to work. Bob showed me how to use pie charts without stacking. I deleted my code for stacking, but wish I had kept it now so I could reference it later.
3) Create visualizations of the data.

Score
10/10

Project 1 - Peter's Coding Data

Peter's Coding Data

Here is a link to my folder that contains this week's work (Jupyter Notebook, csv files):
Work Folder (use Py3 environment)

This week I started working on Peter's survey data that he collected from coding teachers across the globe.

My tasks included:
1) Decide which data to analyze.
2) Decide to focus on data visualization for this project.
3) Setup a Jupyter Notebook and importing relevant data and libraries.
4) Begin to explore the data.
5) Begin to clean the data.

Score
10/10

Practice 7 - Titanic Project

Titanic Project

Here is a link to my folder that contains this week's work (Jupyter Notebook, csv files):
Work Folder (use Py3 environment)

This week I analyzed data about Titanic passengers without the help of any starter code. I was pleasantly surprised by how much I was able to do. I used .describe( ) more than anything else.

I am pretty sure my analysis could have been done a lot more efficiently. I think there is probably a way I could have looked at the data I got by using .describe ( ) without having to have a separate line of code for each category I wanted to describe. I also was not able to get any visualizations to work. I kept getting weird results and was not able to control my x/y axis.

I plan on talking to Bob to get some ideas about more efficient analysis and visualization.

Score
9/10

Practice 6 - Pandas 2D Data

Pandas - 2D Data

Here is a link to my folder that contains this week's work (Jupyter Notebook, environment file, csv files):
Work Folder

Some of the things I did this week were:
1) Access elements of a dataframe
2) Perform vectorized operations
3) Use apply( )
4) Use groupby( )

Udacity provided me with some datasets and starter code. I worked through the process of learning how to use Udacity's code and adding my own code. Check out my Work Folder to see the work I've done.

Score
10/10

Practice 5 - Pandas and NumPy 1D Data

Pandas and NumPy - 1D Data

Here is a link to my folder that contains this week's work (Jupyter Notebook, environment file, csv files):
Work Folder

Some of the things I did this week were:
1) Work with NumPy Arrays
2) Standardize data
3) Work with series in Pandas
4) Plot in Pandas
5) Make things look nice with Seaborn

Udacity provided me with some datasets and starter code. I worked through the process of learning how to use Udacity's code and adding my own code. Check out my Work Folder to see the work I've done.

Score
10/10