Code snippet for demo and graphic in Probability-Proportional-To-Size-Sampling blogpost

weighted_sampling_scratch.R

#' ---
#' title: Code snippet for demo and graphic in Probability-Proportional-To-Size-Sampling blogpost
#' author: nathancday--at-Github--
#' date: 2022-10-24
#' ---


# Libs --------------------------------------------------------------------
library(cowplot)
library(tidyverse)


# Helpers -----------------------------------------------------------------

sample_and_plot = function(x, weight = FALSE) {
  if (!weight) {
    sample_dat = sample_n(dat, 50)
    plt_title = paste0("SRS #", x)
  } else {
    # this is the magic ... weight=frewg
    sample_dat = sample_n(dat, 50, weight = freq)
    plt_title = paste0("PPTSS #", x)
  }
  
  sample_pct_lbl = scales::percent(sum(sample_dat$freq) / sum(dat$freq))
  
  ggplot(dat, aes(query, freq)) +
    geom_col(fill = "white") +
    geom_col(data = sample_dat) +
    annotate("text", x = 400, y = 7000, label = paste0("Sample covers: ", sample_pct_lbl)) +
    scale_x_discrete(labels = NULL) +
    labs(title = plt_title,
         y = NULL, x = NULL)
}


# Ingest -----------------------------------------------------------------

# CSV data from AI Powered Search by Grainger. Turnbull, Irwin
# https://github.com/o19s/visualizing-signals#step-by-step-setup
dat = read_csv("weighted_sampling/signals.csv") %>% 
  filter(type == "query") %>% 
  mutate(query = tolower(target)) %>% 
  count(query, sort = TRUE, name = "freq") %>% 
  slice_head(n = 500) %>% 
  mutate(query = fct_inorder(query))


# Viz ---------------------------------------------------------------------

ylab = "Traffic frequency"
xlab = "Individual queries\nMost frequent  ---> Least frequent"

p_all = ggplot(dat, aes(query, freq)) +
  geom_col() +
  scale_x_discrete(labels = NULL) +
  labs(title = "All queries sorted by traffic frequency",
       y = ylab, x = xlab)

p_uni_li = map(1:5, ~ sample_and_plot(.x))

p_uni = cowplot::plot_grid(plotlist = p_uni_li, ncol = 1)

p_wt_li = map(1:5, ~ sample_and_plot(.x, weight = TRUE))

p_wt = cowplot::plot_grid(plotlist = p_wt_li, ncol = 1)

p_samples = cowplot::plot_grid(p_uni, p_wt, nrow = 1)

cowplot::plot_grid(p_all, p_samples, ncol = 1, rel_heights = c(0.33, .66))


# Output ------------------------------------------------------------------

ggsave("sampling.png", height = 7, width = 8) # saves last plot by default