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modules/week02/hw-02.qmd

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3. Use the relationship between the three cover columns (Snow, Water, Land) to infer missing values where possible and recompute the `Total_cover` column as needed
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**Add comments to your quarto document about your decisions and assumptions**, this will be part of the grading.
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**Add comments to your quarto document about your decisions and assumptions**, this will be a large part of the grading (see below).
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### Setup
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### The expectations are:
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- The Quarto document `eds213_data_cleaning_assign_YOURNAME.qmd` should run if your repo is cloned locally
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- The code should be well commented and output a csv file named `all_cover_fixed_YOURNAME.csv` in the `data/processed` folder
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- Your quarto document should have all the necessary explanations about the decisions you made and potential assumptions you used (don't forget to look at the metadata!)
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- The Quarto document `eds213_data_cleaning_assign_YOURNAME.qmd` should run if your repo is cloned locally (5pts; Reproducibility)
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- The code should output a csv file named `all_cover_fixed_YOURNAME.csv` in the `data/processed` folder (5pts; Code)
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- Comment well you code (10pts; Documentation)
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- Your quarto document should provide all the necessary explanations about your decisions and discuss potential assumptions you used (don't forget to look at the metadata!) (30pts; Documentation)
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- The code should perform the 3 data cleaning steps describe above to enable ingestion into a database (50pts; Technical concepts)
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**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](https://github.com/UCSB-Library-Research-Data-Services/bren-meds213-data-cleaning/blob/later/data-cleaning.qmd))
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- Download your repository as a `.zip` file and upload it to canvas
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**Credit: 100pts**

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