Dive log

A record of recreational and scientific diving, usually on shipwrecks.

I am Alec

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library(tidyverse)
library(patchwork)
library(leaflet)
library(sf)
library(gt)
library(DT)
library(dplyr)
library(ggrepel)
theme_set(theme_minimal())

dive_log <- read_csv("dive_log.csv") %>% 
  mutate(across(c(
    category, entry, group, nitrox, night, water),
                as_factor))

dive_log %>% mutate(depth_bins = cut(depth,
                        breaks=c(0,10,20,30, 40),
                        labels=c('< 10m', '10-20m',
                                 '20-30m', '30-40m'))) %>% 
  group_by("depth range" = depth_bins) %>% 
  summarise(dives = n(),
            hours = round(sum(duration)/60,1)) %>% 
  pivot_longer(-`depth range`, names_to = 'depth') %>% 
  pivot_wider(names_from = `depth range`) %>% 
  gt() %>% tab_options(table.width = pct(100)) %>% 
  fmt_number(
    columns = 2:5,
    rows = 1,
    decimals = 0
  )

depth	< 10m	10-20m	20-30m	30-40m
dives	72	37	28	13
hours	60	27.2	20.6	9

Show code

depth_hist <- ggplot(dive_log) + 
  geom_histogram(aes(depth), binwidth = 1,
                 fill = "#48497F", alpha = 0.9) +
  geom_vline(xintercept = 18, lty=2) +
  labs(
    title = paste0(nrow(dive_log),
                   " dives since 2007"),
    subtitle = paste0(sum(dive_log$depth > 18),
                      ' dives deeper than 18m'))

time_hist <- ggplot(dive_log) + 
  geom_histogram(aes(duration), binwidth = 5,
                 fill = "#48497F", alpha = 0.9) + 
  geom_vline(xintercept = mean(dive_log$duration), lty=2) +
  labs(
    title = paste0(round(sum(dive_log$duration)/60),
      " hours underwater"),
    subtitle = paste0("mean dive time is ",
                         round(mean(dive_log$duration)), ' mins'))

depth_hist + time_hist

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dive_log_training <- filter(dive_log, category == "Training")
dive_log_volunteer <- filter(dive_log, category == "Volunteer")
dive_log_work <- filter(dive_log, category == "Work")
dive_log_recreational <- filter(dive_log, category == "Recreational")

category_count <- dive_log %>% 
  group_by(category) %>% 
  summarise(total_count=n(), .groups = 'drop') %>%   
  as.data.frame()


# Get the positions
df2 <- category_count %>% 
  mutate(csum = rev(cumsum(rev(total_count))), 
         pos = total_count/2 + lead(csum, 1),
         pos = if_else(is.na(pos), total_count/2, pos))

ggplot(category_count, aes(x = "" , y = total_count, fill = fct_inorder(category))) +
  geom_col(width = 1, color = 1) +
  coord_polar(theta = "y") +
  scale_fill_brewer(palette = "Pastel1") +
  geom_label_repel(data = df2,
                   aes(y = pos, label = paste0(total_count, "%")),
                   size = 4.5, nudge_x = 1, show.legend = FALSE) +
  guides(fill = guide_legend(title = "Group")) +
  theme_void()

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map_labels <- paste0(dive_log$date, " ", dive_log$name)

dive_log %>%
  st_as_sf(coords=c('lon', 'lat')) %>% 
leaflet(options=leafletOptions(
    minZoom = 3,
    maxZoom = 10,
  )) %>% 
  setView(lng = 115, lat = -26, zoom = 4) %>% 
  addProviderTiles(provider = providers$CartoDB.Voyager) %>% 
  addCircleMarkers(radius = 7, label = map_labels,
                   stroke = FALSE, fillOpacity = .7,
                   clusterOptions = markerClusterOptions(
                     maxClusterRadius=30,
                     spiderfyDistanceMultiplier=1.2))

Show code

dive_log %>% 
  select(date, time, mins = duration,
         depth, place, category, name) %>% 
  mutate(time = substr(time,1,2)) %>% 
datatable(filter = 'top',
          class = 'compact nowrap',
          options = list(scrollX = TRUE,
                         pageLength=10,
  order = list(list(1, 'desc'),list(2, 'desc'))
))