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fix episode 11 objectives #184

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fix episode 11 objectives #184

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7 changes: 5 additions & 2 deletions episodes/tidy.md
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Expand Up @@ -5,8 +5,11 @@ exercises: 10
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* Identify the characteristics of tidy data and explain its benefits, listing the three principles and discussing how it facilitates data analysis during a review session.
* Use pandas functions like concat(), melt(), and data filtering to manipulate and clean a complex dataset, successfully combining multiple files into a single DataFrame and reshaping it using melt()
* Define the three core principles of tidy data and contrast wide-format vs. long-format structures.
* Reshape wide DataFrames into long format using `pd.melt()`.
* Filter and sort DataFrame rows based on quantitative logical conditions (e.g., value thresholds) and `.sort_values()`.
* Calculate summary statistics across groups using `pd.DataFrame.groupby()` paired with `.agg()`.
* Construct and set temporal indexes by concatenating date string columns, parsing them with `pd.to_datetime()`, and declaring the index via `.set_index()`.
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