Data-Science-Assignments

Repository for the Data Science learning track to host assignments.

Find powerpoints and helpful resources in the course_material folder of this repo! You'll need to clone the repo to see most of them.

Find a great quick python reference here: https://www.w3schools.com/python/

Homework tips

Think ‘process’ not ‘product’. The goal is to learn. The goal is not to hand in a perfect assignment.

Skim your homework assignment BEFORE you do the readings. It will help focus your attention!

SQR3: Scan, Question, Read, Recall, Review!!!!

Week 1 - Introductions and Python

In Class Assignment due Friday, September 17, 2021 @ 8pm

1. Finish any installs not completed in class.
2. Skim the Survival Guide presentation. We will discuss this in more detail throughout the first 8 wks.
3. Submit the in-class activity to canvas. You can submit a link to your repo or the ipynb file itself.

Homework due Wednesday, September 22, 2021 @ 5:30pm

Readings

1. Hello World

2. Data Structures

3. Intro to Git Please complete 1-2

4. Intro to Python - Please complete 1-2

5. Go through the Provided python_click_through.ipynb.

   • Open another notebook and copy each cell and play with it in the new notebook.

   • Ask yourself a question and experiment.

     • What if I change this variable?

       • What’s the outcome?

     • What if I intentionally write code I think will fail?

       • Does it fail?

     • What if I combine the concept in the cell above with this cell?

Notebook

• Complete the week 1 homework notebook found here. You can also find it in the week 1 folder inside the course materials folder here on the github page.
• Submit a link to your week 1 homework on Canvas. Week 1 you are allowed to submit the file itself, but in the future you will have to submit a link.

Optional Readings:

String Manipulation

Optional Videos:

https://www.youtube.com/watch?v=YYXdXT2l-Gg&list=PL-osiE80TeTskrapNbzXhwoFUiLCjGgY7

• Suggest only Videos 2-7 and 9

Week 2 - Python: Math, Strings, If-Else, Expressions

In Class Assignment due Friday, September 24, 2021 @ 8pm

1. Read the following: http://swcarpentry.github.io/shell-novice/01-intro/index.html http://swcarpentry.github.io/shell-novice/02-filedir/index.html
2. Create your own week 02 repository. (If you have not done so in class)
3. Skim the 'In a nutshell' links for 'Learning how to Learn' and 'Deep Work' in the Survival Guide.
   • Find something in those readings that interests you and explore further.
   • These topics can have profound effects outside the classroom as well.
4. Submit a link to your group activity on Canvas.

Homework due Wednesday, September 29, 2021 @ 5:30pm

Readings/Videos/DataCamp

1. Loops

   • In DataCamp, complete Intermediate Python, Chapter 4: Loops (Click here to start)

2. Functions

   • Intro to Python - Please complete 3

3. Classes

   • Working with classes can be challenging. Focus your attention on:

     1. Creating classes.
     2. Adding attributes.
     3. Creating class methods. (methods that operate on the entire class)
     4. Creating instance methods. (methods that act only on the instance)
     5. Creating objects from classes. (foo = MyClass(attr1, attr2)

   • Focus less (but be aware) of:

     1. Inheritance

   • Read this introduction to classes. (Don't worry about the exercises or any notes about Python 2.7.)

   • Read this and complete the exercise at the end. You do not need to submit these, but they will prepare you for the homework.

   • Read this Python's Methods Demystified

4. Intro to Git Please complete 3

Notebook

5. Complete the week_02_homework.ipynb found here. You can also find it in the week 2 folder in the course materials folder at the top of the github page. Submit a link to your repo or submit the .ipynb file.

Optional Videos:

https://www.youtube.com/watch?v=YYXdXT2l-Gg&list=PL-osiE80TeTskrapNbzXhwoFUiLCjGgY7

• Only videos 7 & 8

https://www.youtube.com/watch?v=tJxcKyFMTGo&list=PL-osiE80TeTskrapNbzXhwoFUiLCjGgY7&index=11

https://www.youtube.com/watch?v=ZDa-Z5JzLYM&list=PL-osiE80TeTsqhIuOqKhwlXsIBIdSeYtc

• Only videos 1,2 & 3

Optional Reading: Only do this if you have completed your homework. And have deleted it and done it again.

introduction to functions. Read more on functions here.

Week 3 - Python: Loops, Functions, Classes

In Class Assignment due Friday, October 1, 2021 @ 8pm

1. Submit your group activity on Canvas. Make sure it works, first!
2. OPTIONAL: DataCamp PIP Tutorial

Homework due Wednesday, October 6, 2021 @ 5:30pm

1. DataCamp: NumPy

   • Intro to Python - Please complete 4
   • Complete the whole chapter: “NumPy” through “Blend it all together”

2. Cheat Sheets (just for your reference)

   • NumPy

3. Readings (The Unix Shell)

   • Read these but spend most of your time this week on Numpy.
   • Introducing the Shell
   • Navigating Files and Directories
   • Working with Files and Directories
   • Pipes and Filters

4. Intro to Git Please complete 4-5

Notebook

5. Complete the week_03_homework.ipynb here. You can also find the notebook and the csv file you'll need in the week 4 folder in the course materials folder at the top of the page.
6. Embed screenshots at the end of your jupyter notebook to show you completed the Intro to Git and Intro to Python DataCamp courses.
   • Do your own research on how to do this. There are a couple "correct" ways to embed images in ipynb files
   • Make sure they render when you push your notebook to github
7. List three things you learned about the unix shell in Markdown below the screenshots. Title the section "The Unix Shell"

Optional Videos:

DataCamp-Numpy

Numpy-Part1

[Numpy-Part2](https://www.youtube.com/watch?v=d6O_bXgnjb4

Week 4 - Python: Pandas

In Class Assignment due Friday, October 8, 2021 @ 8pm

1. Submit your group activity to Canvas
2. Read, Click Through and Digest: pandas_part_1.ipynb'
3. Read, Click Through and Digest: pandas_part_2.ipynb'

Homework due Wednesday, October 13, 2021 @ 5:30pm

Readings/Videos/DataCamp

1. Pandas DataFrames - please read and review as needed
2. Time Series tutorial with Pandas - please read and review as needed
3. In DataCamp, Data Manipulation with Pandas - please complete
4. In DataCamp, Into to DataViz - Matplotlib - Please complete 1-2

Notebook

5. Complete the week_04_starter.ipynb. You can find it in the week 4 folder in the course materials folder at the top of the github page. Submit a link to your repo.

• See README.md in the week_04/homework folder for full homework instructions. NOTE: Best viewed in github.
• Output_examples.ipynb is provided as a reference.
• View in Jupyter or Github. (Github sometimes mis-formats documents.)
• NOTE: Your numerical results should be very close to the examples.
  • Your formatting may be very different than provided examples. Focus on getting the data and less on the formatting.

6. Create a simple graph (any type) using Matplotlib and any of the data in the dataframe. Briefly explain what the graph shows.
7. Embed an image indicating that you completed Data Manipulation with Pandas from DataCamp

Optional Videos:

• CoreyMS Youtube - Pandas Playlist

Optional Reading:

• Visual Guide to Joins

• Pandas Merging

• Pandas Cheatsheet

• Data Wrangling Section

• Formatting

• Pandas Documentation

Week 5 - Python: Plotting (matplotlib and Seaborn)

In Class Assignment due Friday, October 15, 2021 @ 8pm

1. Submit your group activity to Canvas using the git url!
2. Read REST API Tutorial if you did not in class or need a refresher

Homework due Wednesday, October 20, 2021 @ 5:30pm

Readings/Videos/DataCamp

1. In DataCamp, complete the rest of Into to DataViz - Matplotlib

2. In DataCamp, complete all of Intro to DataViz - Seaborn

Notebook

4. Complete the WeatherAPI_homework_starter.ipynb. You can find it in the week 5 folder in the course materials folder at the top of the github page. Submit a link to your repo.

• This homework is likely your first opportunity to build your portfolio.
  • Start early, make it neat.
  • This is a real project you can showcase!
  • API calls can be really slow (it is a free service), so limit the number of calls you are making while testing

5. Embed screenshots at the end of your jupyter notebook to show you completed the Intro to Data Visualization with Matplotlib and Intro to Data Visualization with Seaborn from DataCamp

Optional Videos:

• CoreyMS Youtube - matplotlib Playlist

Optional Reading:

• Matplotlib Cheatsheet
• Seaborn Cheatsheet