FILWD • 216 implied HN points • 21 Jan 24
- Filtering data is important for gaining clarity in data analysis and communication.
- Different ways to filter data include by value, by ranking, and manually.
- Filtering data can lead to changes in visualizations like object removal, overplotting reduction, rescaling, resizing, and value change.