staedi/streamlit_ncov19

Interactive Dashboard of Novel COVID-19 Using Streamlit for Python

Streamlit_nCov19 (v2)

Interactive Dashboard of COVID-19 infections and vaccinations employing Streamlit module . You can try here.

Primary objectives

• Basic options for users to choose
  • Cumulative or daily changes measures
  • Global aggregate stat or per-country information
• Display a basic statistics for selected area (Global or for specific country)
• Draw a heatmap detailing given a region and measure (e.g., Daily confirmed patients increases in the US)
• Draw a Choropleth with the same selection (Country-level or state-level comparisons)

Data sources and helpful resources

• Infections data source
  • Johns Hopkins University CSSE GitHub: Global nCov-19 infections dataset
  • South Korean CDC: South Korea's infections dataset providing province-level details
• Vaccinations data source
  • Johns Hopkins University GoVex GitHub: Global nCov-19 vaccinations (+ infections) dataset
  • South Korean CDC: South Korea's vaccinations dataset providing province-level details
  • COVID Live: Australia's vaccinations (+ infections) dashboard providing state-level details
  • Covid-19 Tracking Project: API for Canada's vaccinations (+ infections) dataset providing province-level details
  • Public Health England: UK's vaccinations dataset providing nation-level details (i.e., England, Scotland, Wales, Northern Ireland)
• Geographic data
  • NaturalEarth: Geographical shapedata for countries (admin0) and states-level (admin1) data to be used (1:10m data is used for selected countries for states details while 1:50m used for others)
• Useful resources
  • polygon conversion: To convert MultiPolygon geojson to Polygon form (Nick Doiron)
  • simplify: Using rmapshaper::simplify() in R to greatly reduce file sizes (Phil Mickey Johns)
  • dissolve: Merge small-scale districts into larger level ones (e.g., counties -> states) (Phil Mickey Johns)

Descriptions of objects

• Heatmap
  • Two separate charts are drawn (Infections: confirmed, casualties / Vaccinations: administered, fully vaccinated)
  • Regions on y-axis are pre-sorted by the figures (ordered in a descending manner for top-25 disricts)
• Barplot (Vaccinations-only)
  • For countries which don't provide province/state-level data, single stacked barplot with both measures are drawn (administered and fully vaccinated)
• Choropleth
  • Two measures are drawn on a single choropleth (Color depths: confirmed / administered, Elevations: casualties / fully vaccinated)
  • One measure is shown by the color depth while the other is represented by elevations of the regions

Selected modules used

• Altair: Altair chart module used to draw heatmap (streamlit.altair_chart)
• Pydeck: Pydeck mapping module used to draw Choropleth/PolygonLayer (streamlit.pydeck_chart)

Snapshots

Main Landing Page

Heatmap - Infections

Heatmap - Vaccinations

Barplot - Vaccinations (Country-level)

Choropleth - Infections

Choropleth - Vaccinations