Christmas Bird Counts: TidyTuesday

Keywords

tech, DataAnalysis, R, Visualizations, TidyTuesday

Introduction

Visualizing bird watching data as collected in Hamilton area of Ontario during Christmas time since 1921. Working on the weekly social data project Tidy Tuesday.

Analysis

Load libraries

rm(list = ls())
library(tidyverse)
library(lubridate)
library(ggplot2)
library(gganimate)
library(gridExtra)
library(scales)
theme_set(theme_light())

bird_counts <- readr::read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2019/2019-06-18/bird_counts.csv")

bird_counts

## # A tibble: 18,706 x 6
##     year species    species_latin  how_many_counted total_hours how_many_counte…
##    <dbl> <chr>      <chr>                     <dbl>       <dbl>            <dbl>
##  1  1921 American … Botaurus lent…                0           8            0
##  2  1921 American … Anas rubripes                 0           8            0
##  3  1921 American … Fulica americ…                0           8            0
##  4  1921 American … Corvus brachy…                0           8            0
##  5  1921 American … Spinus tristis                0           8            0
##  6  1921 American … Falco sparver…                0           8            0
##  7  1921 American … Anthus rubesc…                0           8            0
##  8  1921 American … Turdus migrat…                1           8            0.125
##  9  1921 American … Picoides dors…                0           8            0
## 10  1921 American … Spizelloides …               12           8            1.5
## # … with 18,696 more rows

bird_counts %>%
  summary

##       year        species          species_latin      how_many_counted
##  Min.   :1921   Length:18706       Length:18706       Min.   :    0.0
##  1st Qu.:1947   Class :character   Class :character   1st Qu.:    0.0
##  Median :1970   Mode  :character   Mode  :character   Median :    0.0
##  Mean   :1970                                         Mean   :  193.5
##  3rd Qu.:1994                                         3rd Qu.:    5.0
##  Max.   :2017                                         Max.   :73000.0
##
##   total_hours    how_many_counted_by_hour
##  Min.   :  8.0   Min.   :  0.000
##  1st Qu.:149.5   1st Qu.:  0.000
##  Median :171.0   Median :  0.000
##  Mean   :170.8   Mean   :  1.336
##  3rd Qu.:203.8   3rd Qu.:  0.051
##  Max.   :251.0   Max.   :439.024
##  NA's   :3781    NA's   :3781

Which are the 5 most common birds over years?

bird_counts %>%
  group_by(year) %>%
  mutate(rank = min_rank(-how_many_counted) * 1) %>%
  ungroup() %>%
  filter(rank <= 5) %>%
  ggplot(aes(rank,
             group = species,
             fill = as.factor(species),
             color = as.factor(species))) +
  geom_tile(aes(y = how_many_counted/2,
                height = how_many_counted,
                width = 0.9),
            alpha = 0.8,
            color = NA) +
  geom_text(aes(y = 0,
                label = paste(species, " ")),
            vjust = 0.2,
            hjust = 1) +
  coord_flip(clip = "off",
             expand = FALSE) +
  scale_y_continuous(labels = scales::comma) +
  scale_x_reverse() +
  guides(color = FALSE,
         fill = FALSE) +
  labs(title = '{closest_state}',
       subtitle = "Which are the 5 most common birds over years? Birds seen in the Hamilton area of Ontario during Christmas since 1921",
       caption = "Based on data from @BirdsCanada",
       x = "",
       y = "Sights per year") +
  theme(plot.title = element_text(hjust = 0, size = 22),
        axis.ticks.y = element_blank(),
        axis.text.y = element_blank(),
        plot.margin = margin(1,1,1,4,"cm")) +
  transition_states(year, transition_length = 4, state_length = 1) +
  ease_aes('cubic-in-out') -> p

p %>%
  animate(fps = 5,
          nframes = 200,
          duration = 30,
          width = 800,
          height = 600,
          renderer = gifski_renderer("../data/christmas_bird_counts/most_common.gif"))