ateucher

library(duckdb)
#> Loading required package: DBI
library(glue)

url <- "http://www.env.gov.bc.ca/wsd/data_searches/water/Discharge.csv"

conn <- DBI::dbConnect(duckdb(), ":memory:")

# Install and load duckdb extensions to read from http

ateucher

library(arrow)
#> 
#> Attaching package: 'arrow'
#> The following object is masked from 'package:utils':
#> 
#>     timestamp
library(duckdb)
#> Loading required package: DBI
library(dplyr)

ateucher

These are instructions for setting up git to authenticate with GitHub when you have 2-factor authentication set up. This authentication should be inherited by any GUI client you are using. These are intentionally brief instructions, with links to more detail in the appropriate places.

1. Download and install the git command-line client (if required).

2. Open the git bash window and introduce yourself to git (if required):

   git config --global user.name 'Firstname Lastname'
   git config --global user.email 'firstname.lastname@gov.bc.ca'
   

ateucher

extract_pptx_notes <- function(pp_file, format = c("md", "docx")) {
  if (!requireNamespace("officer", quietly = TRUE))
    stop("pacakge 'officer' required.")
  if (!requireNamespace("xml2", quietly = TRUE))
    stop("pacakge 'xml2' required.")
  if (!requireNamespace("rmarkdown", quietly = TRUE))
    stop("pacakge 'rmarkdown' required.")
  if (!requireNamespace("glue", quietly = TRUE))
    stop("pacakge 'glue' required.")

ateucher

R: if vs ifelse

Inspired by a question about when to use if vs ifelse

First we'll make a simple function that determines whether or not someone is awesome:

is_awesome <- function(name) {

ateucher

author	date	output	title
ateucher	2021-06-08	reprex::reprex_document	ash-crane_reprex.R

library(osmdata)
#> Data (c) OpenStreetMap contributors, ODbL 1.0. https://www.openstreetmap.org/copyright

ateucher

library(sf)
library(jsonlite)
library(purrr)
library(mapview)

f <- read_json("https://www.bchydro.com/power-outages/app/outages-map-data.json")

polys <- lapply(f, function(x) {
  mat <- matrix(unlist(x$polygon), ncol = 2, byrow = TRUE)
  st_polygon(list(rbind(mat, mat[1,])))

ateucher

library(tidyverse)
library(gghighlight)
library(ggrepel)
library(scales)

data <- read_csv("https://github.com/CSSEGISandData/COVID-19/raw/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv")

data_long <- pivot_longer(data, `1/22/20`:last_col(), names_to = "date", values_to = "cases") %>%
  mutate(date = as.Date(date, format = "%m/%d/%y")) %>%
  filter(!is.na(cases),

ateucher

library(ggplot2)

iris$is_pretty <- sample(c(TRUE, FALSE), nrow(iris), replace = TRUE)

# dodge < width
ggplot(iris, aes(y = is_pretty, x = Petal.Length, fill = Species)) + 
  geom_bar(stat = "identity", position = position_dodge(0.5), width = 0.85)

ateucher

require(ggplot2)

set.seed(42)

df <- data.frame(x=1:50, y=rnorm(50, 10, 2), int=rbinom(50,1,0.3))

ggplot(df, aes(x=x, y=y)) +
  geom_ribbon(aes(ymin=0, ymax=y, fill='#1E90FF'), alpha=0.3) +
  geom_abline(intercept=10, slope=-0.1
              , aes(colour='Linear')) +