Brooklyn Bridge Bicycling Visualization Weblet

load_packages <- function(pkg_list) {
  for (pkg in pkg_list) {
    if (!require(pkg, character.only = TRUE)) {
      install.packages(pkg, dependencies = TRUE)
      library(pkg, character.only = TRUE)
    }
  }
}

packages <- c("tidyverse", "readxl", "pander")
load_packages(packages)

knitr::opts_chunk$set(echo = TRUE,      
                      warning = FALSE,   
                      message = FALSE,  
                      results = TRUE,
                      comment = NA,
                      fig.align = "center"
                      )   
url <- "https://raw.githubusercontent.com/ncbrechbill/STA321/refs/heads/main/STA321/BrooklynBridge.csv"
data <- read.csv(url)

data$AvgTemp <- (data$HighTemp + data$LowTemp) / 2

data <- data %>%
  mutate(data, PrecipFactor = ifelse(Precipitation > 0, "Yes", "No"))


model.quasi.freq <- glm(BrooklynBridge ~ AvgTemp + PrecipFactor + Day,
                        family = quasipoisson,
                        data = data)


qcoefs <- model.quasi.freq$coefficients

qnomon <- exp(qcoefs[1] + (qcoefs[2]*data$AvgTemp) + qcoefs[4])
qnotue <- exp(qcoefs[1] + (qcoefs[2]*data$AvgTemp) + qcoefs[8])
qnowed <- exp(qcoefs[1] + (qcoefs[2]*data$AvgTemp) + qcoefs[9])
qnothu <- exp(qcoefs[1] + (qcoefs[2]*data$AvgTemp) + qcoefs[7])
qnofri <- exp(qcoefs[1] + (qcoefs[2]*data$AvgTemp))
qnosat <- exp(qcoefs[1] + (qcoefs[2]*data$AvgTemp) + qcoefs[5])
qnosun <- exp(qcoefs[1] + (qcoefs[2]*data$AvgTemp) + qcoefs[6])

qyesmon <- exp(qcoefs[1] + (qcoefs[2]*data$AvgTemp) + qcoefs[3] + qcoefs[4])
qyestue <- exp(qcoefs[1] + (qcoefs[2]*data$AvgTemp) + qcoefs[3] + qcoefs[8])
qyeswed <- exp(qcoefs[1] + (qcoefs[2]*data$AvgTemp) + qcoefs[3] + qcoefs[9])
qyesthu <- exp(qcoefs[1] + (qcoefs[2]*data$AvgTemp) + qcoefs[3] + qcoefs[7])
qyesfri <- exp(qcoefs[1] + (qcoefs[2]*data$AvgTemp) + qcoefs[3])
qyessat <- exp(qcoefs[1] + (qcoefs[2]*data$AvgTemp) + qcoefs[3] + qcoefs[5])
qyessun <- exp(qcoefs[1] + (qcoefs[2]*data$AvgTemp) + qcoefs[3] + qcoefs[6])

plot_quasi_no <- data.frame(
  AvgTemp = data$AvgTemp,
  Monday = qnomon,
  Tuesday = qnotue,
  Wednesday = qnowed,
  Thursday = qnothu,
  Friday = qnofri,
  Saturday = qnosat,
  Sunday = qnosun
)

plot_quasi_long.no <- pivot_longer(
  plot_quasi_no,
  cols = -AvgTemp,
  names_to = "Day",
  values_to = "ModeledCount"
)


plot_quasi_yes <- data.frame(
  AvgTemp = data$AvgTemp,
  Monday = qyesmon,
  Tuesday = qyestue,
  Wednesday = qyeswed,
  Thursday = qyesthu,
  Friday = qyesfri,
  Saturday = qyessat,
  Sunday = qyessun
)

plot_quasi_long.yes <- pivot_longer(
  plot_quasi_yes,
  cols = -AvgTemp,
  names_to = "Day",
  values_to = "ModeledCount"
)

# Combine all modeled values
quasi_all_counts <- c(qnomon, qnotue, qnowed, qnothu, qnofri, qnosat, qnosun,
                qyesmon, qyestue, qyeswed, qyesthu, qyesfri, qyessat, qyessun)

# Get min and max for consistent y-axis
ymin <- min(quasi_all_counts)
ymax <- max(quasi_all_counts)

library(highcharter)

hchart(plot_quasi_long.no, "line", hcaes(x = AvgTemp, y = ModeledCount, group = Day)) %>%
  hc_title(text = "Brooklyn Bridge Bikers (No Precipitation)") %>%
  hc_yAxis(title = list(text = "Modeled Biker Count"), min = ymin, max = ymax) %>%
  hc_xAxis(title = list(text = "Average Temperature (°F)"))

hchart(plot_quasi_long.yes, "line", hcaes(x = AvgTemp, y = ModeledCount, group = Day)) %>%
  hc_title(text = "Brooklyn Bridge Bikers (With Precipitation)") %>%
  hc_yAxis(title = list(text = "Modeled Biker Count"), min = ymin, max = ymax) %>%
  hc_xAxis(title = list(text = "Average Temperature (°F)"))