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--- | |
output: | |
xaringan::moon_reader: | |
css: "ninjutsu" | |
seal: false | |
--- | |
class: split-40 | |
count: false |
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<!DOCTYPE html> | |
<html xmlns="http://www.w3.org/1999/xhtml" lang="" xml:lang=""> | |
<head> | |
<meta charset="utf-8" /> | |
<style> | |
.column1, .column2 { | |
position: absolute; | |
top:0; | |
width:50%; | |
} |
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# the party logos are required to be in the form of `plogo-XXX.png` where XXX is the party abbreviation that matches | |
# in PartyAb | |
# inspired by https://coolbutuseless.github.io/2020/04/12/racing-barplots-with-ggpattern-flagon-gganimate/ | |
library(tidyverse) | |
library(gganimate) | |
library(ggpattern) | |
dat <- read_csv("https://results.aec.gov.au/24310/Website/Downloads/HouseDopByDivisionDownload-24310.csv", skip = 1) %>% | |
mutate(PartyAb = case_when( |
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library(tidyverse) | |
income_df <- tibble(income_range = c("0-74", "75-145", "150-325", "325+"), | |
count = c(125, 170, 215, 250)) %>% | |
separate(income_range, | |
into = c("income_min", "income_max"), | |
convert = TRUE) | |
calc_median_income <- function(df) { | |
df %>% |
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as_tidymatrix <- function(x){ | |
structure(list(.value = as.vector(x), | |
.row = as.vector(row(x)), | |
.col = as.vector(col(x))), | |
row.names = seq_len(length(as.vector(x))), | |
nrow = nrow(x), # need these attribute if storing it as sparse later | |
ncol = ncol(x), | |
class = c("tidymatrix", "data.frame")) | |
} |
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x <- structure(list(x = 1), "attr" = 2) | |
y <- structure(list(y = 3), "attr" = 1) | |
l <- list(x, y) | |
out <- do.call(c, l) | |
# doesn't quite work (notice the name) | |
out2 <- lapply(seq_along(out), function(i) { | |
attributes(out[[i]]) <- attributes(l[[i]]) | |
out[[i]] | |
}) |
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library(data.table) | |
library(tidyverse) # ggplot2, tidyr, dplyr, purrr, stringr ... | |
library(scales) | |
library(grid) | |
library(RColorBrewer) | |
############################################################### | |
## MOST COMMON ACTIONS DURING FIRST TWO WEEKS | |
############################################################### | |
## IMPORT AND TIDY DATA |
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