report_code/farmer_reports_iter1/farmerReports1_rScript.R

In dbturner/c4bi: Coding for broader impact

# RScript for First Round of southeatern PA Farm Reports
# Authors: Daniel B. Turner, Jocelyn E. Behm, & Matthew R. Helmus
# Description - This script will complete the following tasks in sections:
#     1. Load data from farm biodiversity surveys.
#     2. Create objects or lists of some plots to be used in the reports.
#     3. Run a "for loop" that will cycle through the datasets to create individualized reports.

# SECTION 1: Load data from farm biodiversity surveys.           --------------------------------------------------

# a. Load relevant R packages
library(RColorBrewer)
library(plyr)
library(rmarkdown)
library(knitr)
library(ggplot2)


# b. Load data files

load(here::here("data/abun.rich.sepa.rda"))
print(abun.rich.sepa) # Check to see if the dataframe is complete.
abun.rich.sepa$farmName <- factor(abun.rich.sepa$farmName, levels = abun.rich.sepa$farmName) # Make names a factor for ordering of columns in subsequent plots.

load(here::here("data/arth.div.pie.sepa.rda"))
print(arth.div.pie.sepa) # Check to see if the dataframe is complete.

# SECTION 2: Create objects or lists of some plots to be used in the reports.           --------------------------------------------------

pie <- ggplot(data = arth.div.pie.sepa, mapping = aes(x = "", y = prop, fill = family)) +
  geom_bar(width = 1, stat = "identity") +
  coord_polar("y", start = 0) +
  scale_fill_brewer(palette = "Set3") +
  theme(axis.text = element_blank(),
        axis.ticks = element_blank(),
        panel.grid  = element_blank(),
        axis.title = element_blank(),
        plot.title = element_text(size=18),
        panel.background = element_blank(),
        legend.text = element_text(size=14),
        legend.title = element_text(size = 16),
        strip.text.x = element_text(size = 12.5)) +
  labs(fill = "Family of insect or spider") # These lines make an object with a pie chart of the predator families.


famPies <- plyr::dlply(arth.div.pie.sepa, .(farmName), function(x) pie %+% x) # dlply here applies the object created above across all "farm names" and returns a list of all plots.

famPies[1] # Plot the first plot in the "famPies" list of pie charts.

nfarms <- nrow(abun.rich.sepa) # Create an object with the number of farms in the first data frame that will be used to index the for loop and name each .html output file.

# SECTION 3: Run a "for loop" that will cycle through the datasets to create individualized biodiversity reports.           --------------------------------------------------
i = 1

for (i in 1:(nfarms-3)) { # We subtract by three because we don't want to create .html docs for the category means.
  urbanCat <- abun.rich.sepa$urbanCat[i] # This object will be fed to the .Rmd file to display each farm's urbanization category.

  abun_bar_plot <- ggplot(abun.rich.sepa[c(i, (nfarms-2):nfarms),], aes(x = farmName, y = meanAbun)) +
    geom_bar(stat = "identity", aes(fill = farmName)) +
    labs(y = "Average number of beneficial predators\nfound in each trap",
         fill = "Your farm and other categories of farms") +
    theme_classic() +
    theme(axis.ticks.x = element_blank(),
          axis.text.x = element_blank(),
          axis.title.x = element_blank()) +
    scale_fill_brewer(palette = "Set2") # Create an object with the farm's predator abundance that will be called in the .rmd file.

  rich_bar_plot <- ggplot(abun.rich.sepa[c(i, (nfarms-2):nfarms),], aes(x = farmName, y = meanRich)) +
    geom_bar(stat = "identity", aes(fill = farmName)) +
    labs(y = "Average number of beneficial predator\ntypes found in each trap",
         fill = "Your farm and other categories of farms") +
    theme_classic() +
    theme(axis.ticks.x = element_blank(),
          axis.text.x = element_blank(),
          axis.title.x = element_blank()) +
    scale_fill_brewer(palette = "Set2") # Create an object with the farm's predator richness that will be called in .rmd file.

  real_pie_plot <- famPies[[i]] # Create an object with the farm's pie chart that will be called in .rmd file.

  render(here::here("report_code/farmer_reports_iter1/farmerReports1_rmd.Rmd"), output_file = paste0(here::here('report_code/farmer_reports_iter1/report_output/farmerReport1_example_'), abun.rich.sepa$farmName[i], ".html"), "html_document") # This line actually executes each farm's .html report by calling the .rmd file.
  # NOTE: The .rmd should be located in the same workspace directory as this R script.
  # ANOTHER NOTE: The .html files will be located in the same workspace directory as this R script.
}