Longitudinal Waste data
In Covid19Wastewater: Prepare, Analyze, and Visualize Covid-19 Wastewater Data

knitr::opts_chunk$set(echo = FALSE, Warning = FALSE, message = FALSE)

Longitudinal data source

This vignette covers the wastewater data collected by the Wisconsin State Lab of Hygiene. This wastewater data covers 118 weeks of 1-5 measurements a week from 82 locations. This has 63 columns where 5 are categorical variables, 9 are measurement columns and the remaining are extra info about the measurements.

#add start and end date?
library(Covid19Wastewater)
library(dplyr)
library(ggplot2)

data(WasteWater_data, package = "Covid19Wastewater")

The data is broken down by site and data. Site is where it was collected from. The primary column's are N1 and N2 which are two different genes of Covid-19.

#could put in the work to explain all 62 columns but it should be fine for now
WasteWater_data%>%
  filter(site == "Madison")%>%
  ggplot(aes(x = date), size = .3, alpha = .5)+
  geom_point(aes(y = N1, color = "N1"))+
  geom_point(aes(y = N2, color = "N2"))+
  scale_y_log10()+
  theme(plot.title = element_text(hjust = 0.5))+
  labs(y = "Gene Concentration", color = "", title = "Log number of N1 and N2", x = "Date")

Below is the first 6 rows of the dataset.

Head_DF <- WasteWater_data%>%
  head()

Head_DF%>%
  select(sample_id:flow)%>%
  knitr::kable()

Head_DF%>%
  select(ph:n1_lod)%>%
  knitr::kable()

Head_DF%>%
  select(n1_loq:n2_loq)%>%
  knitr::kable()