DATA 101

The overall goal of this class is to engage in curious exploration. Please be patient with yourself and others! Along the way you will learn how to make pretty graphs, some basics of programming in Python, and how to think like a Data Scientist.

Pre-class: Each class day will have content that you should explore before class. I build my lectures, labs, and discussions assuming that you have done the work beforehand. Each day you will submit what you have completed. It does not have to be perfect, but it must show your attempt to engage in the material. (Note: If you leave tabs open, remember to refresh the page!)

Class time & materials:

• Notes — What is Data Science?
• Slides — What is Data Science?
• Notes — Set up your computer (Important that this is done this week)
• Homework — Day 1 (.ipynb)

Download each day's notebook from this page and move it into that Day's folder in your GitHub repo.

Announcements: Start prepping for Day 2 — click on the Day 2 link and complete the pre-class materials.

Pre-class:

• Video: How to be Successful — Walks you through being a successful student in this class, the workflow, submitting homework, etc.
• Notes — Hello World!
• Video: Hello World!

(Note: If you leave tabs open, remember to occasionally refresh the page!)

Class time:

• Go over syllabus and course expectations
• Finish setting up conda
• Slides — Hello World - Our first data science exploration!
• Homework — Day 2 (download .ipynb)

Download each day's notebook from this page and move it into that Day's folder in your GitHub repo.

Homework

• Homework — Day 1 & 2 (Due Sunday 9/6 11:59pm)

Announcements:

Submit Day 1 & Day 2 homework by pushing to your GitHub repo by Sunday 9/6 11:59pm.
Start prepping for Day 3 — click on the Day 3 link and complete the pre-class materials.

Pre-class:

• Python Vocabulary (will help with the quiz)
• Pre-Class Quiz / Survey on canvas

(Note: If you leave tabs open, remember to occasionally refresh the page!)

Class time:

• Data Visualization Presentation - Class Slides
• Homework — Day 3 (download .ipynb)
• Notes to Help with the Homework
• Video to Help with the Homework

Homework

• Homework — Day 3 (Due Sunday 9/13 11:59pm)

Pre-class:

• Numerical vs Categorical Data Introduction
• Do the Day 4 Pre-Class Quiz on Canvas

(Note: If you leave tabs open, remember to occasionally refresh the page!)

Class time:

• In Class Slides - Day 4
• Video - Day 4 HW Help
• Notebook Notes - Day 4 HW Help
• Homework — Day 4 (download .ipynb)

Homework

• Homework — Day 4 & 5 (Due Sunday 9/20 11:59pm)

Pre-class:

• Video - Day 5 Data Wrangling
• Notes - Day 5 Data Wrangling

(Note: If you leave tabs open, remember to occasionally refresh the page!)

Class time:

• In Class Slides - Day 5
• Homework — Day 5 (download .ipynb)

Homework

• Homework — Day 4 & 5 (Due Sunday 9/20 11:59pm)

Pre-class:

• Video - Day 6 Data Wrangling Continued
• Notes - Day 6 Data Wrangling Continued
• Do the Day 6 Pre-class quiz on Canvas

(Note: If you leave tabs open, remember to occasionally refresh the page!)

Class time:

• In Class Slides - Day 6
• Homework — Day 6 (download .ipynb)

Homework

• Homework — Day 6 & 7 (Due Sunday 9/27 11:59pm)

Pre-class:

• Video - Day 7 DataWranglingJoins
• Notes - Day 7 Multiple Dataframes

(Note: If you leave tabs open, remember to occasionally refresh the page!)

Class time:

• In Class Slides - Day 7
• Homework — Day 7 (download .ipynb)

Homework

• Homework — Day 6 & 7 (Due Sunday 9/27 11:59pm)

Pre-class:

• Video - Day 8 Reading Data and Data Types
• Notes - Day 8 Reading Data and Data Types
• Pre-Class Quiz on Canvas - Review of pd.merge
• Go to the Cal Fire Incidents page, scroll to the bottom, download ALL DATA AS CSV, and move mapdataall.csv into your Day8 folder. If the Cal Fire site gives you trouble, download mapdataall.csv here instead.

(Note: If you leave tabs open, remember to occasionally refresh the page!)

Class time:

• In Class Slides - Day 8
• Homework — Day 8 (download .ipynb)
• Talk about the Command Cheat Sheet

Homework

• Homework — Day 8 (Due Sunday 9/4 11:59pm)
• Homework — Day 9 (Due Sunday 10/11 11:59pm)

(Note: If you leave tabs open, remember to occasionally refresh the page!)

Pre-class:

• Do the practice exam from day 7. Come prepared with questions about the practice exam.
• Come prepared with questions from any of the homeworks

Class time:

• Review Practice Exam From Day 7 Together
• Go over any questions from any of the homeworks
• Go over how the exam works

Homework

• Homework — Day 8 (Due Sunday 10/4 11:59pm)
• Exam 1 Part 1 (Due Monday 10/5 10:49am aka right before class)

Pre-class:

• Exam 1 opens on Canvas Wednesday 9/30.
  • This exam is open notes, open computer, etc - but you cannot use any type of human or AI intervention. This includes asking how to do an entire problem online, asking ChatGPT or any other AI, or working with friends.
  • The pre-class work on the exam must be COMPLETELY ON YOUR OWN!
  • Upload the the Exam1.ipynb in the main folder of your repo (not inside a Day folder). Commit and Push your first draft before class starts on Monday 10/5.

(Note: If you leave tabs open, remember to occasionally refresh the page!)

Class time:

• Work on Exam 1 in Groups

Homework

• You have until end of day (Monday 10/5 @11:59pm) to finish your exam. Same rules as before class (NO AI and NO HUMAN help)
• Homework — Day 9 (Due Sunday 10/11 11:59pm)

Pre-class:

• Nothing this time, chill out and relax a little after the exam. You all earned it

(Note: If you leave tabs open, remember to occasionally refresh the page!)

Class time:

• Do the Survey On Canvas, let me know how the exam went. (In class participation)
• Homework — Day 9 (download .ipynb)
• Homework Exercise 2 Data: file_name = 'https://joannabieri.com/introdatascience/data/sales.xlsx'
• In Class Slides - Day 9

Homework

• Homework — Day 9 (Due Sunday 10/11 11:59pm)

Class time:

• No Class - Fall Break

Pre-class:

• Pre-Class Quiz on Canvas - Review Pivots and Melts

(Note: If you leave tabs open, remember to occasionally refresh the page!)

Class time:

• Day 10 Notes (Joanna)
• Day 10 Video (Joanna)
• In Class Slides - Day 10
• Homework — Day 10 (download .ipynb)
• Canvas In Class Activity

Homework

• Homework — Day 10 (Due Sunday 10/18 11:59pm)
• Final Project - Data Exploration (Due Wednesday 10/21 10:50 am)

Pre-class:

• Nothing due - you should be focusing on your Final Project Data Exploration
• Video - Day 11 (Prof. Joanna)
• Notes - Day 11 (Prof. Joanna)

(Note: If you leave tabs open, remember to occasionally refresh the page!)

Class time:

• In Class Slides - Day 11
• Data Ethics Readings - Pick one to read and complete the Essay Response in the Homework
• Homework — Day 11 (download .ipynb)

Homework

• Final Project - Data Exploration (Due Wednesday 10/21 10:50 am)
• Homework — Day 11 (Due Sunday 10/25 11:59pm)

Pre-class:

• Final Project - Exploration due before class
• Two Parts to Today's Lesson, you can review ahead of time:
• Notes - Doing Data Science (Prof. Joanna)
• Video - Doing Data Science (Prof. Joanna)


• Notes - Web Scraping (Prof. Joanna)
• Video - Web Scraping (Prof. Joanna)

(Note: If you leave tabs open, remember to occasionally refresh the page!)

Class time:

• In Class Slides - Day 12
• Canvas In Class Activity
• Homework — Day 12 (download .ipynb)

Homework

• Homework — Day 11 (Due Sunday 10/25 11:59pm)
• Homework — Day 12 (Due Sunday 10/25 11:59pm)

Pre-class:

• Pre Class Assignment on Canvas
• Notes - Data Ethics (Prof. Joanna)
• Video - Data Ethics (Prof. Joanna)

(Note: If you leave tabs open, remember to occasionally refresh the page!)

Class time:

• Day 13 Slides
• Data Ethics Discussion - come prepared with your Data Ethics readings and questions

Homework

• Homework — Day 13 (download .ipynb)
• Homework — Day 13(Due Sunday 11/01 11:59pm)
• Final Project - Project Proposal due Sunday Nov 8

Pre-class:

• Notes - Data Ethics Algorithmic Bias (Prof. Joanna)
• Video - Data Ethics Algorithmic Bias(Prof. Joanna)

(Note: If you leave tabs open, remember to occasionally refresh the page!)

Class time:

• Canvas In Class Activity
• In Class Slides - Day 14

Homework

• Homework — Day 14 (download .ipynb)
• Homework — Day 13 (Due Sunday 11/01 11:59pm)
• Homework — Day 14 (Due Sunday 11/08 11:59pm)
• Final Project - Project Proposal (Due Sunday 11/08 11:59pm)

Pre-class:

• Look over the Cheat Sheet of Commands 2 and write down any commands you are not sure about. Look back at your homework from Days 10-14. What gave you trouble? Bring your questions!

(Note: If you leave tabs open, remember to occasionally refresh the page!)

Class time:

• Your questions about anything from Days 10-14.
• Practice with the topics on Exam 2 (see the list below).

Announcements:

Exam 2 opens on Canvas today, Tuesday 11/3. Do the first draft on your own and push Exam2.ipynb to your repo before class on Thursday 11/5.
Exam 2 will cover:

• Loading data and doing basic analysis - shape, describe(), columns, look for weird data.
• The data in this exam will include NaNs
• Masking data to find specific information.
• Creating new columns in the data frame - doing a calculation using other columns.
• Using groupby(), value_counts(), and sort_values()
• Merging two data frames into one data frame

Homework — Day 14 (Due Sunday 11/08 11:59pm)

Final Project Proposals are due Sunday 11/8 11:59pm.

Pre-class:

• Exam 2 opens on Canvas Tuesday 11/3.
• This exam is open notes, open computer, etc - but you cannot use any type of human or AI intervention. This includes asking how to do an entire problem online, asking ChatGPT or any other AI, or working with friends.
• The pre-class work on the exam must be COMPLETELY YOUR OWN!
• Download the notebook called Exam2.ipynb from canvas and place in the main folder of your repo (not inside a Day folder). Commit and Push your first draft before class starts on Wednesday 11/4.

Cheat Sheet of Commands 1

Cheat Sheet of Commands 2

Common Errors In Python - Video

(Note: If you leave tabs open, remember to occasionally refresh the page!)

Class time:

• Exam 2 in Groups

Announcements:

• After class, keep working on the exam on your own (same rules as before class) and push your final version by Thursday 11/5 11:59pm. Whatever is in your repo at the deadline is what gets graded.
• Final Project Proposals are due Sunday 11/8 11:59pm.
• Homework 14 is due Sunday 11/8 11:59pm.
• Start Prepping for Day 15 - click on the Day 15 link and complete the PRE-CLASS materials.