USMortality

library(readr)
library(dplyr)
library(ggplot2)
library(lubridate)
library(tsibble)
library(scales)

sf <- 2
width <- 600 * sf
height <- 335 * sf

USMortality

library(dplyr)
library(ggplot2)
library(httr)
library(jsonlite)
library(lubridate)
library(tsibble)

sf <- 2
width <- 600 * sf
height <- 335 * sf

USMortality

library(dplyr)
library(ggplot2)
library(httr)
library(jsonlite)
library(lubridate)
library(tsibble)

sf <- 2
width <- 600 * sf
height <- 335 * sf

USMortality

library(tidyverse)
library(tsibble)
library(ggrepel)
library(quantmod)

sf <- 2
width <- 600 * sf
height <- 335 * sf

options(vsc.dev.args = list(width = width, height = height, res = 72 * sf))

USMortality

library(readr)
library(dplyr)
library(ggplot2)
library(tsibble)
library(lubridate)
library(fable)
library(scales)

sf <- 2
width <- 900 * sf

USMortality

# Standard Populations from SEER.gov

# Helper Functions:
## Splits an age group string by its start and end year.
split_age_group <- function(age_group) {
  ages <- strsplit(age_group, "-")
  c(as.integer(ages[[1]][1]), as.integer(ages[[1]][2]))
}

## Split weights for an age group uniformly.

USMortality

library(readr)
library(dplyr)
library(tsibble)
library(fable)
library(ggplot2)
library(scales)

sf <- 2
width <- 900 * sf
height <- 450 * sf

USMortality

#!/bin/bash

set -euo pipefail

USER="USMortality"
CHARTS_JSON="out/charts.json"
BASE_URL="https://s3.mortality.watch/charts"
ERROR_LOG="error.log"

rm -rf out && mkdir out

USMortality

library(readr)
library(dplyr)
library(ggrepel)
library(ggpubr)
library(ggpmisc)
library(scales)
library(tidyr)
library(lubridate)

sf <- 2

USMortality

#!/bin/sh

### Prerequisites: MacOS: Homebrew & NodeJS
# brew install n # Homebrew: https://brew.sh
# n install lts

npm install -g playwright
playwright install chromium

export NODE_PATH=$(npm root -g)