Dataset Selection - Githubissues

westrany / Data-Scrubbing-and-Cleaning-for-Improved-Analysis

A demonstration of data cleaning techniques using Python's Panda libraries with the aim to prepare raw datasets for analysis by addressing inconsistencies, missing values, outliers, and other data quality issues.

MIT License

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Dataset Selection #1

Closed westrany closed 5 months ago

westrany commented 5 months ago

[x] Choose a couple of datasets from a reliable source such as Kaggle, UCI Machine Learning Repository, or government databases. Ensure they represent different types of data (e.g., tabular, time series, text).
[x] Select datasets with noticeable data quality issues like missing values, duplicate entries, inconsistent formats, or outliers.

westrany commented 5 months ago

Used an unclean dataset with 386 entries from my Goodreads