Week 2 - Data Cleaning

Please use Canvas to return the assignments: https://ucsb.instructure.com/courses/19301/assignments/238393

We cleaned the Snow_cover column during class. Inspiring yourself from the steps we followed, do the following in a quarto document:

  1. Clean the Water_cover column to transform it into the correct data type and respect expectations for a percentage

  2. Clean the Land_cover column to transform it into the correct data type and respect expectations for a percentage

  3. Use the relationship between the three cover columns (Snow, Water, Land) to infer missing values where possible and recompute the Total_cover column

Add comments to your quarto document about your decisions and assumptions, this will be part of the grading.

Setup

You should start a new quarto document named eds213_data_cleaning_assign_YOURNAME.qmd in your fork of the GitHub repository bren-meds213-data-cleaning.

The expectations are:

  • The qmd eds213_data_cleaning_assign_YOURNAME.qmd should run if your repo is cloned locally and
  • the code should output a csv file named all_cover_fixed_YOURNAME.csv in the data/processed folder

Note: We recommend starting by importing the csv file with the corrected Snow_cover column (data/processed/snow_cover.csv) we generated during class (my code here)

On Canvas:

  • Add the URL to your fork on GitHub at the top of your quarto document

  • Upload the qmd & csv files to Canvas (those versions will be the ones evaluated for grading)

This work is licensed under CC BY 4.0

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