EDS 217
  • 🏠 home
  • 📋 syllabus
  • 🗓️ daily materials
    • 0️⃣ Day 1 (9/3)
    • 1️⃣ Day 2 (9/4)
    • 2️⃣ Day 3 (9/5)
    • 3️⃣ Day 4 (9/6)
    • 4️⃣ Day 5 (9/9)
    • 5️⃣ Day 6 (9/10)
    • 6️⃣ Day 7 (9/11)
    • 7️⃣ Day 8 (9/12)
    • 8️⃣ Day 9 (9/13)
  • 💻 interactive sessions
    • Session 1a - ⚒️ JupyterLab Intro and IPython
    • Session 1b - ⚒️ Coding in Jupyter Notebooks
    • Session 1c - 🐍 Exploring Variable Types and Methods in Python
    • Session 1d - 🐍 Operators & Functions
    • Session 2a - 🐍 Lists
    • Session 2b - 🐍 Dissecting Dictionaries
    • Session 3a - 🐍 Introduction to Control Flows
    • Session 3c - 🔢 Arrays and Series
    • Session 4a - 🐼 DataFrames
    • Session 4c - 🐼 DataFrame Workflows
    • Session 4d - 🐼 Data Import and Export
    • Session 5a - 🐼 Selecing and Filtering Data
    • Session 5b - 🐼 Cleaning Data
    • Session 6a - 🐼 Grouping, Joining, and Sorting (Part I)
    • Session 6c - 📆 Working with Dates
    • Session 7a - 📊 Data Visualization with Seaborn & Matplotlib (Part I)
    • Session 7b - 📊 Data Visualization with Seaborn & Matplotlib (Part II)
  • 🙌 coding colabs
    • 🙌 Session 2c - Working with Lists, Dictionaries, and Sets
    • 🙌 Session 3b - Control Flows
    • 🙌 Session 3d - Pandas Series
    • 🙌 Session 4b - Pandas DataFrames
    • 🙌 Session 5c - Data Cleaning
    • 🙌 Session 6b - Data Manipulation
    • 🙌 Session 7c - Exploring data using visualizations
  • 👀 cheatsheets
  • 📚 resources
    • 📚 Python Documentation
    • 📚 Pandas Documentation
    • 📚 Numpy Documentation
    • 📚 Matplotlib Documentation
    • 📚 Seaborn Documentation
    • 📚 JupyterLab Documentation
    • 📚 Anaconda Documentation
    • 📚 Stack Overflow
    • 📚 Real Python
    • 📚 Towards Data Science
    • 📚 DataCamp
    • 📚 Kaggle
    • 🧰 Python Tutor
    • 🧰 Pandas Tutor
    • 📙 Python for Data Analysis
    • 📙 Python for Data Science Handbook
    • 📙 Python Data Science Handbook (GitHub)
    • 📻 Talk Python to Me

Python for Environmental Data Science

Master of Environmental Data Science (MEDS)

Summer 2024

import antigravity

Cartoon by XKCD

Course Description

Programming skills are critical when working with, understanding, analyzing, and gleaning insights from environmental data. In the intensive EDS 217 course, students will develop fundamental skills in Python programming, data manipulation, and data visualization, specifically tailored for environmental data science applications.

The goal of EDS 217 (Python for Environmental Data Science) is to equip incoming MEDS students with the programming methods, skills, notation, and language commonly used in the python data science stack, which will be essential for their python-based data science courses and projects in the program as well as in their data science careers. By the end of the course, students should be able to:

  • Manipulate and analyze data using libraries like pandas and NumPy

  • Visualize data using Matplotlib and Seaborn

  • Write, interpret, and debug Python scripts

  • Implement basic algorithms for data processing

  • Utilize logical operations, control flow, and functions in programming

  • Collaborate with peers to solve group programming tasks, and communicate the process and results to the rest of the class

Syncing your classwork to Github

Here are some directions for syncing your classwork with a GitHub repository

Teaching Team


Instructor

Kelly Caylor
Email: caylor@ucsb.edu
Learn more: Bren profile

TA

Anna Boser
Email: anaboser@ucsb.edu
Learn more: Bren profile

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