Assignment 1 #66
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Assignment 1 #66
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What changes are you trying to make? (e.g. Adding or removing code, refactoring existing code, adding reports)
adding new features to a dataset stored in Parquet files using Dask
What did you learn from the changes you have made?
Converting a large dataset from a Dask DataFrame to a pandas DataFrame (.compute()) can lead to memory issues and slow performance
Was there another approach you were thinking about making? If so, what approach(es) were you thinking of?
Instead of converting the Dask DataFrame to pandas, I could perform the rolling average calculations directly in Dask
Were there any challenges? If so, what issue(s) did you face? How did you overcome it?
You faced a challenge with duplicate labels causing errors during calculations, such as reindexing issues
How were these changes tested?
The results were tested by computing and displaying a sample (dd_feat.head()) using pandas. This helps verify if the new columns, such as lags and rolling averages, were calculated correctly.
A reference to a related issue in your repository (if applicable)
Checklist