benzipperer

realtalk R package build instructions

Requirements

• repo
• targets R package

Update frequency

monthly, upon BLS CPI release

Update instructions

benzipperer

# show all the function names in a given set of R scripts
function_definitions = function(files) {
  purrr:::map(files, function_definitions_script) |> 
    purrr::list_rbind()
}

function_definitions_script = function(file) {
  text = brio::read_lines(file) |>
    paste(collapse = "\n")
  

benzipperer

benzipperer

library(tidyverse)
library(MetricsWeighted)

# here's how to calculate multiple weighted percentiles by year 
# and reshape them so data is long in year but wide in percentiles
# below I explain this step by step

# first grab some data
cps_data <- epiextractr::load_org(1979:2022, year, orgwgt, wage) %>% 
  filter(wage > 0)

benzipperer

library(tidyverse)
library(modelsummary)
library(kableExtra)

model_am1 = mtcars %>% 
  filter(am == 1) %>% 
  lm(mpg ~ wt, data = .)

model_am0 = mtcars %>% 
  filter(am == 0) %>% 

benzipperer

/* BEGIN BZ MODIFICATIONS */
/* this do-file requires the following files from the authors
medicaidelig.dta
UKCPR_National_Welfare_Data_Update_021520.dta
*/


copy https://github.com/Economic/state_geocodes/raw/master/state_geocodes.dta state_geocodes.dta, replace
use state_geocodes, clear
rename state_census stcps

benzipperer

library(tidyverse)
library(ggridges)

# state codes
states_regions <- read_csv("https://raw.githubusercontent.com/cphalpert/census-regions/master/us%20census%20bureau%20regions%20and%20divisions.csv") %>% 
  select(state_abb = `State Code`, region = Region) 

# CMS provider info
# https://data.cms.gov/provider-data/dataset/4pq5-n9py
raw <- read_csv("NH_ProviderInfo_Jun2023.csv") %>% 

benzipperer

library(tidyverse)
library(lubridate)
library(hrbrthemes)

# K-12 shooting incident data from https://www.chds.us/ssdb/data-map/
readxl::read_excel("SSDB_Raw_Data.xlsx", sheet = "INCIDENT") %>% 
  mutate(
    year = year(ymd(Date)),
    month = month(ymd(Date)),
    month_date = ym(paste(year, month))

benzipperer

library(tidyverse)
library(lubridate)
library(haven)
library(assertr)
library(slider)
library(hrbrthemes)

# function to bin hourly wages of hourly workers
bin_hourly <- function(df, new, old) {
  df %>% 

benzipperer

proxmox stuff

pass disk/partition through to VM

https://pve.proxmox.com/wiki/Passthrough_Physical_Disk_to_Virtual_Machine_(VM)