The covid19sf package provides a daily summary of the covid19 cases in San Francisco. The package includes the following datasets:
covid19sf_age - Cases summarized by age groupcovid19sf_demo - Cases summarized by date, transmission and case dispositioncovid19sf_gender - Confirmed cases summarized by gendercovid19sf_geo - Confirmed cases and deaths summarized by geographycovid19sf_homeless - Confirmed cases by homelessnesscovid19sf_hospital - Hospital capacity datacovid19sf_hospitalizations - Hospitalizations datacovid19sf_housing - Alternative housing sitescovid19sf_summary - Cases summarized by date, transmission and case dispositioncovid19sf_test_loc - Testing locationscovid19sf_tests - Daily number of testsData soucre: San Francisco, Department of Public Health - Population Health Division through the San Francisco Opne Data protal website
The ccovid19sf package provides different views for the covid19 cases in San Francisco. That includes case distribution by age, gender, race, etc. The following examples demonstrate some of the data use cases.
The covid19sf_age provides a daily summary of the cumulative positive cases by age group:
data(covid19sf_age)
head(covid19sf_age)
#> specimen_collection_date age_group new_confirmed_cases cumulative_confirmed_cases last_updated
#> 1 2020-03-12 51-60 2 6 2020-11-13 14:15:03
#> 2 2020-03-13 51-60 3 9 2020-11-13 14:15:03
#> 3 2020-03-14 51-60 1 10 2020-11-13 14:15:03
#> 4 2020-03-15 51-60 0 10 2020-11-13 14:15:03
#> 5 2020-03-16 51-60 8 18 2020-11-13 14:15:03
#> 6 2020-03-17 51-60 3 21 2020-11-13 14:15:03The following box-plot shows the distribution of the positive cases by age group:
library(plotly)
covid19sf_age$age_group <- factor(covid19sf_age$age_group,
levels = c("under 18", "18-30",
"31-40", "41-50",
"51-60", "61-70",
"71-80","81+"))
plot_ly(covid19sf_age,
color = ~ age_group,
y = ~ new_confirmed_cases,
boxpoints = "all",
jitter = 0.3,
pointpos = -1.8,
type = "box" ) %>%
layout(title = "Case Dist. by Age Group",
yaxis = list(title = "Number of Cases"),
xaxis = list(title = "Source: San Francisco Department of Public Health"),
legend = list(x = 0.9, y = 0.9))
Here is the overall distribution of cases by age group as of 2020-11-12:
library(dplyr)
library(plotly)
covid19sf_age %>%
filter(specimen_collection_date == max(specimen_collection_date)) %>%
plot_ly(values = ~ cumulative_confirmed_cases,
labels = ~ age_group,
type = "pie",
textposition = 'inside',
textinfo = 'label+percent',
insidetextfont = list(color = '#FFFFFF'),
hoverinfo = 'text',
text = ~paste("Age Group:", age_group, "<br>",
"Total:", cumulative_confirmed_cases)) %>%
layout(title = "Total Cases Distribution by Age Group")
The covid19sf_tests provides a daily summary of the daily number of tests and their results (positive, negative, and indeterminate):
data(covid19sf_tests)
head(covid19sf_tests)
#> specimen_collection_date tests pos pct neg indeterminate last_updated
#> 1 2020-02-28 2 0 0.00000000 2 0 2020-11-13 14:15:00
#> 2 2020-03-01 2 0 0.00000000 2 0 2020-11-13 14:15:00
#> 3 2020-03-02 2 0 0.00000000 2 0 2020-11-13 14:15:00
#> 4 2020-03-03 8 2 0.25000000 6 0 2020-11-13 14:15:00
#> 5 2020-03-04 12 0 0.00000000 12 0 2020-11-13 14:15:00
#> 6 2020-03-05 23 6 0.26086957 17 0 2020-11-13 14:15:00The plot below shows the daily distribution of the results of the tests:
covid19sf_tests %>%
plotly::plot_ly(x = ~ specimen_collection_date,
y = ~ pos,
name = "Positive",
type = 'scatter',
mode = 'none',
stackgroup = 'one',
fillcolor = "red") %>%
plotly::add_trace(y = ~ neg, name = "Negative", fillcolor = "green") %>%
plotly::add_trace(y = ~ indeterminate, name = "Indeterminate", fillcolor = "gray") %>%
plotly::layout(title = "Tests Results Distribution",
yaxis = list(title = "Tests Count"),
xaxis = list(title = "Source: San Francisco Department of Public Health"),
legend = list(x = 0.1, y = 0.9))
The covid19sf_demp dataset provides a daily summary of the covid19 positive cases by race and ethnicity:
data(covid19sf_demo)
head(covid19sf_demo)
#> specimen_collection_date race_ethnicity new_confirmed_cases cumulative_confirmed_cases last_updated
#> 1 2020-05-19 Asian 0 312 2020-11-13 14:15:03
#> 2 2020-05-31 Asian 5 348 2020-11-13 14:15:03
#> 3 2020-06-01 Asian 5 353 2020-11-13 14:15:03
#> 4 2020-06-02 Asian 3 356 2020-11-13 14:15:03
#> 5 2020-06-03 Asian 2 358 2020-11-13 14:15:03
#> 6 2020-06-04 Asian 5 363 2020-11-13 14:15:03Below is a plot of the cumulative positive cases by race and ethnicity:
covid19sf_demo %>%
dplyr::arrange(specimen_collection_date) %>%
plotly::plot_ly(x = ~ specimen_collection_date,
y = ~ cumulative_confirmed_cases,
# name = 'Cases',
type = 'scatter',
mode = 'none',
color = ~race_ethnicity,
stackgroup = 'one') %>%
layout(title = "Total Cases Dist. by Race and Ethnicity",
legend = list(x = 0.1, y = 0.9),
yaxis = list(title = "Number of Cases", tickformat = ".0f"),
xaxis = list(title = "Source: San Francisco Department of Public Health"))