macleish.R
In macleish: Retrieve Data from MacLeish Field Station

## ----include=FALSE------------------------------------------------------------
library(knitr)
opts_chunk$set(fig.width = 6, fig.height = 4)

## ----message=FALSE------------------------------------------------------------
library(macleish)

## -----------------------------------------------------------------------------
head(whately_2015)
tail(whately_2015)

## ----eval=FALSE---------------------------------------------------------------
# head(orchard_2015)
# tail(orchard_2015)

## ----eval=FALSE---------------------------------------------------------------
# help("etl_extract.etl_macleish")

## ----daily, message=FALSE, warning=FALSE--------------------------------------
library(ggplot2)
library(dplyr)
library(lubridate)
daily <- whately_2015 |>
  mutate(the_date = as.Date(when, tz = "EST")) |>
  group_by(the_date) |>
  summarize(
    N = n(), avg_temp = mean(temperature),
    max_temp = max(temperature),
    min_temp = min(temperature)
  )

## ----temp-plot, message=FALSE-------------------------------------------------
temp_plot <- ggplot(data = whately_2015, aes(x = when, y = temperature)) +
  geom_line(color = "lightgray") +
  geom_line(data = daily, aes(
    x = as.POSIXct(the_date),
    y = avg_temp
  )) +
  xlab(NULL) +
  ylab("Temperature (Celsius)")

if (require(mgcv)) {
  temp_plot + geom_smooth()
} else {
  temp_plot
}

## ----temp-table---------------------------------------------------------------
monthly_w <- whately_2015 |>
  mutate(the_month = month(when, label = TRUE, abbr = FALSE)) |>
  group_by(the_month) |>
  summarize(avg_temp = mean(temperature))
monthly_o <- orchard_2015 |>
  mutate(the_month = month(when, label = TRUE, abbr = FALSE)) |>
  group_by(the_month) |>
  summarize(avg_temp = mean(temperature))
monthly_w |>
  inner_join(monthly_o, by = "the_month")

## ----temp-extremes------------------------------------------------------------
whately_2015 |>
  arrange(desc(temperature)) |>
  head(1)
whately_2015 |>
  arrange(temperature) |>
  head(1)

## -----------------------------------------------------------------------------
daily <- daily |>
  mutate(temp_range = max_temp - min_temp)
daily |>
  select(temp_range) |>
  summary()

## -----------------------------------------------------------------------------
daily |>
  arrange(desc(temp_range)) |>
  head(1)
daily |>
  arrange(temp_range) |>
  head()

## ----orchard-anolomies--------------------------------------------------------
orchard_2015 |>
  filter(month(when) == 11) |>
  ggplot(aes(x = when, y = temperature)) +
  geom_line()

## ----humidity-table-----------------------------------------------------------
monthly_w <- whately_2015 |>
  mutate(the_month = month(when, label = TRUE, abbr = FALSE)) |>
  group_by(the_month) |>
  summarize(avg_humidity_w = mean(rel_humidity))
monthly_o <- orchard_2015 |>
  mutate(the_month = month(when, label = TRUE, abbr = FALSE)) |>
  group_by(the_month) |>
  summarize(avg_humidity_o = mean(rel_humidity))
monthly_w |>
  inner_join(monthly_o, by = "the_month")

## ----message=FALSE, warning=FALSE---------------------------------------------
orchard_2015 |>
  mutate(wind_dir_bin = factor(floor(wind_dir / 31))) |>
  ggplot(aes(y = wind_speed, x = wind_dir_bin)) +
  geom_boxplot() +
  coord_radial() +
  scale_x_discrete("Wind direction (degrees from North)") +
  scale_y_continuous("Wind speed (meters per second)")

## ----message=FALSE------------------------------------------------------------
whately_2015 |>  
  mutate(wind_dir_bin = factor(floor(wind_dir / 31))) |>
  ggplot(aes(y = wind_speed, x = wind_dir_bin)) +
  geom_boxplot() +
  coord_radial() +
  scale_x_discrete("Wind direction (degrees from North)") +
  scale_y_continuous("Wind speed (meters per second)")

## -----------------------------------------------------------------------------
whately_2015 |>
  summarize(total_rainfall = sum(rainfall))

## ----rain-table---------------------------------------------------------------
monthly_w <- whately_2015 |>
  mutate(the_month = month(when, label = TRUE, abbr = FALSE)) |>
  group_by(the_month) |>
  summarize(total_precip_w = sum(rainfall))
monthly_o <- orchard_2015 |>
  mutate(the_month = month(when, label = TRUE, abbr = FALSE)) |>
  group_by(the_month) |>
  summarize(total_precip_o = sum(rainfall))
monthly_w |>
  inner_join(monthly_o, by = "the_month")

## ----message=FALSE------------------------------------------------------------
daily_precip <- whately_2015 |>
  mutate(the_date = as.Date(when, tz = "EST")) |>
  group_by(the_date) |>
  summarize(N = n(), total_precip = sum(rainfall)) |>
  mutate(
    cum_precip = cumsum(total_precip),
    cum_rescale = (cum_precip / max(cum_precip)) * max(total_precip)
  )

## ----daily-precip, message=FALSE----------------------------------------------
ggplot(
  data = daily_precip,
  aes(x = the_date, y = total_precip)
) +
  geom_bar(stat = "identity") +
  geom_line(aes(y = cum_rescale), color = "blue") +
  ylab("Daily Precipitation (mm)") +
  xlab(NULL)

## -----------------------------------------------------------------------------
names(macleish_layers)

## ----eval=FALSE, message=FALSE------------------------------------------------
# library(leaflet)
# leaflet() |>
#   addTiles() |>
#   addPolygons(
#     data = macleish_layers[["boundary"]],
#     weight = 1
#   ) |>
#   addPolygons(
#     data = macleish_layers[["buildings"]],
#     weight = 1
#   ) |>
#   addMarkers(
#     data = filter(macleish_layers[["landmarks"]], grepl("Met", Label)),
#     popup = ~Label
#   )