class: center, middle, inverse # California Forest Fires ## 2000 - 2017 .footnote[ by [Umar Shaik](https://github.com/ufshaikc/cs6774) ] ---
Agenda
1. Input Dataset
2. Gantt Chart
3. Timeline Baloon Colored
4. Timeline Baloon Animated
5. Conclusion
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1. Input Dataset
Name
Start Date
End Date
Intensity
Alpha
01-10-2017
02-10-2017
0.1
Beta
01-11-2017
07-11-2017
0.5
Charlie
01-12-2017
30-12-2017
1
* Intensity is the acres of land burned, which is normalized on a scale of 0 to 1. * Name - Categorical * Start Date / End Date - Quantitative -> Sequential * Intensity - Ordinal --- # 2. Gantt Chart [*](./calfire-box.html) [#](https://www.w3schools.com/colors/colors_picker.asp) What is the dependency of intensity on the duration of the event? Why: {`Locate`, `Attributes -> Many -> Dependency` } How: {` Arrange -> Separate`, `Map - Ordered -> Color -> Saturation, Ordered -> Size -> length`} Channels: `Hue` instead of `Saturation` for Intensity (Ordinal) --- # 3. Timeline Baloon Colored [*](./calfire-box.html)[#](https://www.w3schools.com/colors/colors_picker.asp) What is the intensity dependency on the duration of the event? Why: {`Locate`, `Attributes -> Many -> Dependency` } How: {` Arrange -> Separate`, `Map - Ordered -> Color -> Saturation, Ordered -> Size -> length / Area`} Channels: `Saturation` instead of `Hue` for Duration Name (Categorical) --- # 4. Timeline Baloon Animated [*](./calfire-box.html)[#](https://www.w3schools.com/colors/colors_picker.asp) At what point did the intensity actually increase? Why: {`Locate`, `Attributes -> One -> Extremes` } How: {` Arrange -> Separate`, `Map - Ordered -> Color -> Saturation, Ordered -> Size -> length / Area`} Channel: `Hue` for Intensity (Animation) --- # 5. Take Away Points * Using `Hue` for ordinal and `Saturation` for categorical proved useful in our case. * Eyes beat memory, easy to compare visuals by moving side-by-side. * Animation's are good, if considered in small multiples instead of large scale. * Timeline balloons are only good for smaller dataset.