I am using water sample data that were collected from my research site in Northeast
Arkansas. The samples were collected from three groundwater monitoring wells and one
surface reservoir. Two .csv spreadsheets with water sample data will be used in R, one from
a sample date in February and one from March. The farmer of the land from which the samples
were collected is last named Wimpy, hence the use of the name throughout my code. The data
are composed of measured water quality data, such as concentrations of major cations and
anions, pH values, and water temperature. The data tables provide coordinates of latitude
and longitude for each Sample.ID, which I can use to create spatial objects.
library("plyr")
library("dplyr")
library("sp")
library("sf")
library("readr")
library("data.table")
#load data
WimpySamples_Mar <- read.csv("data/Mar.csv", header = T)
WimpySamples_Feb <- read.csv("data/Feb.csv", header = T)
# I now have 2 data frames.
# I want my data contained in one single data.frame.
# Both data frames have the same variables, allowing me to join the two vertically, using the rbind() function:
WimpyDF <- rbind(WimpySamples_Feb, WimpySamples_Mar)
str(WimpyDF)
# The data.frame contains 8 rows of observations of 41 columns of values of variables
lm(Temp..C.~DO..mg.L., data = WimpyDF)
#> Call:
lm(formula = Temp..C. ~ DO..mg.L., data = WimpyDF)
Coefficients: (Intercept) DO..mg.L.
15.5750 -0.5438