Charlie Joey Hadley charliejhadley

## bechdel-chart.R
library("tidyverse")
library("fivethirtyeight")

library("ggrepel")
library("hrbrthemes")
library("ggtext")

bechdel_complete <- bechdel %>%
  drop_na() %>%
  mutate(profitable = budget_2013 <= domgross_2013)

## starwars-graph.R
library(tidyverse)
library(ggraph)
library(tidygraph)


nodes_characters <- starwars %>%
  mutate(character_id = row_number(), .before = 0) %>%
  mutate(across(where(is.list), ~lengths(.x), .names = "n_{.col}"))

edges_reoccuring_co_stars <- nodes_characters %>%

## births-deaths.csv
tibble::tribble(
     ~country, ~year,     ~month,    ~name, ~value,
  "Australia", 2011L,  "January", "births", 24550L,
  "Australia", 2011L,  "January", "deaths", 11483L,
  "Australia", 2011L, "February", "births", 23209L,
  "Australia", 2011L, "February", "deaths", 10522L
  )

## server.R


function(input, output, session){

  output$curve_plot <- renderPlot({

    print(input$exponent)

    curve(x^as.integer(input$exponent), from = -5, to = 5)


## get_docs_rdocsanalysis.R
devtools::install_github("charliejhadley/rdocsanalysis")

library(tidyverse)
dplyr_docs <- rdocsanalysis::process_pkg_docs("dplyr", version_number = "1.0.0")

## funky-data.csv

          
            date_quote
            date_purchase
            flag

            
              2020-08-15
              2020-09-28
              TRUE

            
              2020-07-27
              2020-09-09
              FALSE

            
              2020-07-22
              2020/09/04
              FALSE

            
              2020-08-22
              2020-10-05
              TRUE

            
              2020-04-14
              2020-05-28
              TRUE

            
              2020-05-27
              2020/07/10
              TRUE

            
              2020-03-20
              2020-05-03
              FALSE

            
              2020-03-15
              2020/04/28
              FALSE

            
              2020-01-12
              2020/02/25
              FALSE

## fixed-leaflet.R
library(tigris)
library(sf)
library(rmapshaper)
library(readxl)
library(janitor)
library(leaflet)
library(tidyverse)

# ==== Streaming Data ====
# Data obtained from https://kiss951.com/2021/05/20/national-streaming-day-list-of-the-most-popular-streaming-services-in-each-state/

## waterfall-chart.R
library(tidyverse)

data_waterfall_raw <- read_csv("waterfall.csv")

data_waterfall_clean <- data_waterfall_raw %>%
  mutate(order = row_number()) %>%
  mutate(event = str_wrap(event, 12)) %>%
  mutate(event = fct_reorder(event, order)) %>%
  mutate(
    end = cumsum(change),

## mortgate-rate.R
library(tidyverse)
library(lubridate)
library(bbplot)
library(ggtext)

# values for five-year mortgages are inaccurately read from the original graphic by BBC
# https://twitter.com/charliejhadley/status/1576992785638772736?s=20&t=DTM3oBSGAsSOQ2SIrvUB-A

mortgage_rates <- tribble(
  ~date, ~rate, ~deal,

## quarto.qmd
---
title: "Quarto"
format: html
echo: false
message: false
warning: false
---

```{r load-packages}
library(tidyverse)
	library("tidyverse")
	library("fivethirtyeight")

	library("ggrepel")
	library("hrbrthemes")
	library("ggtext")

	bechdel_complete <- bechdel %>%
	drop_na() %>%
	mutate(profitable = budget_2013 <= domgross_2013)
	library(tidyverse)
	library(ggraph)
	library(tidygraph)


	nodes_characters <- starwars %>%
	mutate(character_id = row_number(), .before = 0) %>%
	mutate(across(where(is.list), ~lengths(.x), .names = "n_{.col}"))

	edges_reoccuring_co_stars <- nodes_characters %>%
	tibble::tribble(
	~country, ~year, ~month, ~name, ~value,
	"Australia", 2011L, "January", "births", 24550L,
	"Australia", 2011L, "January", "deaths", 11483L,
	"Australia", 2011L, "February", "births", 23209L,
	"Australia", 2011L, "February", "deaths", 10522L
	)


	function(input, output, session){

	output$curve_plot <- renderPlot({

	print(input$exponent)

	curve(x^as.integer(input$exponent), from = -5, to = 5)
	devtools::install_github("charliejhadley/rdocsanalysis")

	library(tidyverse)
	dplyr_docs <- rdocsanalysis::process_pkg_docs("dplyr", version_number = "1.0.0")
date_quote	date_purchase	flag
2020-08-15	2020-09-28	TRUE
2020-07-27	2020-09-09	FALSE
2020-07-22	2020/09/04	FALSE
2020-08-22	2020-10-05	TRUE
2020-04-14	2020-05-28	TRUE
2020-05-27	2020/07/10	TRUE
2020-03-20	2020-05-03	FALSE
2020-03-15	2020/04/28	FALSE
2020-01-12	2020/02/25	FALSE
	library(tigris)
	library(sf)
	library(rmapshaper)
	library(readxl)
	library(janitor)
	library(leaflet)
	library(tidyverse)

	# ==== Streaming Data ====
	# Data obtained from https://kiss951.com/2021/05/20/national-streaming-day-list-of-the-most-popular-streaming-services-in-each-state/
	library(tidyverse)

	data_waterfall_raw <- read_csv("waterfall.csv")

	data_waterfall_clean <- data_waterfall_raw %>%
	mutate(order = row_number()) %>%
	mutate(event = str_wrap(event, 12)) %>%
	mutate(event = fct_reorder(event, order)) %>%
	mutate(
	end = cumsum(change),
	library(tidyverse)
	library(lubridate)
	library(bbplot)
	library(ggtext)

	# values for five-year mortgages are inaccurately read from the original graphic by BBC
	# https://twitter.com/charliejhadley/status/1576992785638772736?s=20&t=DTM3oBSGAsSOQ2SIrvUB-A

	mortgage_rates <- tribble(
	~date, ~rate, ~deal,
	---
	title: "Quarto"
	format: html
	echo: false
	message: false
	warning: false
	---

	```{r load-packages}
	library(tidyverse)