https://pve.proxmox.com/wiki/Passthrough_Physical_Disk_to_Virtual_Machine_(VM)
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year | cpi_u_rs_extended | |
---|---|---|
1937 | 24.3 | |
1938 | 23.8 | |
1939 | 23.5 | |
1940 | 23.6 | |
1941 | 24.9 | |
1942 | 27.6 | |
1943 | 29.2 | |
1944 | 29.7 | |
1945 | 30.4 |
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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) |
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library(tidyverse) | |
library(modelsummary) | |
library(kableExtra) | |
model_am1 = mtcars %>% | |
filter(am == 1) %>% | |
lm(mpg ~ wt, data = .) | |
model_am0 = mtcars %>% | |
filter(am == 0) %>% |
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/* 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 |
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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") %>% |
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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)) |
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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 %>% |
Find the new physical volume using fdisk -l
. Let's say it is /dev/sda
.
Then partition using fdisk /dev/sda
. Type n
to create primary partition, default partition 1, default sectors.
Then type t
to change partition type to 8e
(Linux LVM). Then type w
to write the partition table.
pvcreate /dev/sda1
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clear all | |
set more off | |
* download CES data, if new | |
!wget -N https://download.bls.gov/pub/time.series/ce/ce.data.0.AllCESSeries | |
!wget -N https://download.bls.gov/pub/time.series/ce/ce.series | |
!wget -N https://download.bls.gov/pub/time.series/ce/ce.industry | |
* identify 3-digit industries | |
insheet using ce.industry, clear tab |
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