1: Using Numpy and Pandas

Due April 13 before 9 am Pacific

10 points

1. Create a public GitHub repository called gisc606-lab1 in your GitHub account using github/codespaces-jupyter as a template repository.

   1. See Creating a repository from a template in case you forgot how.

2. Open your repository in a GitHub Codespace

   1. See the Codespace docs for more.

3. Create a Jupyter Notebook for and complete each of the following lessons from Earth Lab CU Boulder's Introduction to Earth Data Science textbook. Follow the instructions in each of the labs and type them into your Jupyter Notebook. Make sure to commit changes to your repository often.

   1. Intro to Numpy Arrays: intro_to_numpy.ipynb

   2. Import Text Files Into Numpy Arrays: import_text_files.ipynb

   3. Run Calculations and Summary Statistics on Numpy Arrays: run_calculations.ipynb

   4. Slice (or Select) Data From Numpy Arrays: slice_or_select.ipynb

   5. Intro to Pandas Dataframes: intro_to_pandas.ipynb

   6. Import CSV Files Into Pandas Dataframes: import_csv.ipynb

   7. Run Calculations and Summary Statistics on Pandas Dataframes: run_calculations_pd.ipynb

   8. Select Data From Pandas Dataframes: select_data.ipynb

4. Once you are complete with all the lesson notebooks, navigate to Lab 1 assignment in Canvas

5. Input the url of your gisc606-lab1 GitHub repository then click submit

If you run into issues using GitHub Codespaces, try Google Colaboratory as an alternative development environment.

As you complete each lesson (in a separate Colaboratory Notebook), download the notebook to your computer and upload it to your GitHub.