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Owen Churches ofchurches

  • Adelaide, South Australia
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library(tidyverse)
library(tidygraph)
library(ggraph)
grosses <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-04-28/grosses.csv', guess_max = 40000)
# links between theatres that have put on the same show
# create the edge list
edge_list <- grosses %>%
select(show, theatre) %>%
@ofchurches
ofchurches / gist:da902a393ce8e529b33ca0a137cd5ff3
Last active April 28, 2020 00:40
tidy_tuesday_20200421
library(tidyverse)
library(tidytext)
library(wordcloud)
library(reshape2)
# Plot 1: Sentiment wordcloud.
gdpr_text <- readr::read_tsv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-04-21/gdpr_text.tsv')
#base on https://www.tidytextmining.com/sentiment.html
library(tidyverse)
library(gganimate)
library(tidygraph)
library(ggraph)
#Import the data
polls <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-04-14/polls.csv')
#Make an edge list with nodes as artists with an edge drawn each time the same critic votes for the two artists
edge_list <- polls %>%
library(tidyverse)
library(gganimate)
tdf_winners <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-04-07/tdf_winners.csv')
tdf_winningest <- tdf_winners %>%
count(winner_team) %>%
top_n(10) %>%
pull(winner_team)
library(tidyverse)
library(scales)
#First, come up with an idea in static ggplot...
beer_states <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-03-31/beer_states.csv')
top_states <- beer_states %>%
filter(state != "total") %>%
filter(type == "On Premises") %>%
library(readr)
library(tidyverse)
library(gganimate)
library(tidygraph)
library(igraph)
library(ggraph)
season_goals <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-03-03/season_goals.csv')
top_8 <- season_goals %>%