## Class

Reopen your `vis-for-gds` project and save this `.Rmd` to the `reports` folder. When working through the materials from this session run each code chunk separately by clicking the small green arrow beside each code chunk. By default I have set `eval=FALSE` on most code chunks, so when you knit the code chunk will not execute.

The technical element demonstrates how to recreate in `ggplot2` the *glyphmap* appearing in [The Washington Post](https://www.washingtonpost.com/nation/2020/05/24/coronavirus-rural-america-outbreaks/?arc404=true) to tell a story of growth in Covid-19 cases by US county.

### Setup

The code block below points to the packages you need to do the work discussed in the session. U

```{r setup, echo=TRUE, eval=FALSE, message=FALSE}
library(tidyverse) # Bundle of packages for doing modern data analysis.
library(sf) # Spatial operations
```

### Import

Run the code block below to download the staged Covid-19 case data by US county.

```{r download-data, echo=TRUE, eval=FALSE, message=FALSE}
# Dataset of US county Covid data -- derived fields already incorporated.
county_data <- read_csv("https://www.roger-beecham.com/datasets/county_data_covid.csv") %>%
  # Cast binned_growth_rate to factor.
  mutate(binned_growth_rate=factor(binned_growth_rate))
state_boundaries <- st_read("https://www.roger-beecham.com/datasets/state_boundaries.geojson")
```
