---
title: Action Items
---

## Priority
- [ ] 1. Designing Portal Visualizaiton
- [ ] Overview
- [ ] Trend by Country
- [ ] 2. Content of plots
- [ ] Global map
- [ ] US map
- [ ] Daily trend: confirmed & death
- [ ] Cumulative trend: confirmed & death
- [ ] 3. Data Table Pipeline
- [ ] 4. Forecasting

## Breakdown

- Visualizations (plotly + ggplot2)
- [x] 1. Fix U.S. top 10 time-series plot (Peter)
- [x] 2. Add # of active cases to the odometers (Peter)
- [ ] 3. Change the trend plot to: (Wenyan)
- [x] Daily news cases as histogram
- Moving Average
- [ ] Overlay moving average (short-term EMA, long-term EMA)
- [ ] Remove moving average days feature
- [ ] Check boxes for `Short-term Trend` and `Long-term Trend` (Multiple selections)
- Consider using EMA over SMA
- [ ] Check boxes for `90 Days` or `All` (Single selection)
- [ ] Add `Active` to metric selection
- [ ] 4. Global heat map w/ animation or timeline (Peter)
- can we try to plot confirmed_per_million (easy distinguish)?
- can we customize the colors with own scale?
- can we add a scale bar in the plot: 1, 5, 10, 50, 100, 250, >500?
- Split the project into 2 scripts
- [x] 1. Data ingestion + preprocessing with scheduler (Peter)

## Tables
- [ ] 1. Global Cases
- Index: country
- Metrics: total confirmed, deaths, recovered, active, confirmed_per_million, deaths_per_million, active_per_million
- Link: overall summary, top 10 county

- [ ] 2. Global Time Series Cases
- Index: country
- Metrics: daily confirmed cases
- Link: EMA?

- [ ] 3. US cases
- Index: FIPS, State-id
- Metrics: total confirmed, deaths, recovered, active, confirmed_per_1000, deaths_per_1000, active_per_1000
- Link: overall summary, top 10 county/state (linear)

- [ ] 4. US Time Series Cases
- Index: FIPS, State-id
- Metrics: daily confirmed cases
- Link: EMA?

- [ ] 5. US daily confirmed vs daily test
- Index: State-id
- Metrics: test_per_1000, confirmed_per_1000