Data on veterans in the U.S.
Open up a new .Rmd file.
Use {r setup, include=F} in your first code chunk.
knitr::opts_chunk$set(echo = TRUE)
# Load necessary libraries
library(knitr)
library(kableExtra)
library(tidyverse)## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.4 ✔ readr 2.1.5
## ✔ forcats 1.0.0 ✔ stringr 1.5.1
## ✔ ggplot2 3.5.1 ✔ tibble 3.2.1
## ✔ lubridate 1.9.3 ✔ tidyr 1.3.1
## ✔ purrr 1.0.2
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::group_rows() masks kableExtra::group_rows()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errorslibrary(readr)
library(dplyr)
library(tidyr)
library(readxl)Accessing 2010 data on U.S. Veterans here.
If you have issues with the above link, try: https://www.va.gov/vetdata/Surveys.asp
# Load necessary libraries
library(httr)
library(readxl)
# Define the URL of the Excel file
url <- "https://www.va.gov/vetdata/docs/SurveysAndStudies/Publicdata2010.xls"
# Define a temporary file path
temp_file <- tempfile(fileext = ".xls")
# Download the file
GET(url, write_disk(temp_file, overwrite = TRUE))## Response [https://www.va.gov/vetdata/docs/SurveysAndStudies/Publicdata2010.xls]
## Date: 2024-11-18 01:49
## Status: 200
## Content-Type: application/vnd.ms-excel
## Size: 38.8 MB
## <ON DISK> /var/folders/54/02xngdrx2277pg5hxjx3z8040000gn/T//RtmplNzwFV/filed886586dc22d.xls# Read the downloaded Excel file into a data frame
df <- read_excel(temp_file)
# Optionally, remove the temporary file after reading (if desired)
unlink(temp_file)View summaries of the data
head(df)## # A tibble: 6 × 229
## ACCESWEB ACTEVER ACTLAST ACTNEW ADDRESS AGREE1 AGREE2 AGREE3 AGREE4 AGREE5
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 NA 1 1968 1965 1 2 2 1 1 2
## 2 NA 1 1963 1961 1 3 3 2 1 2
## 3 NA 1 1969 1968 2 2 2 2 2 2
## 4 NA 1 1956 1954 1 5 1 1 1 3
## 5 NA 1 1942 1941 0 2 2 1 8 8
## 6 NA 1 1963 1961 0 2 1 1 2 3
## # ℹ 219 more variables: AGREE6 <dbl>, AGREE7 <dbl>, AGREE8 <dbl>, AGREE9 <dbl>,
## # AIAN <dbl>, AIDNEED <dbl>, AIRF <dbl>, APPEAR1 <dbl>, APPEAR2 <dbl>,
## # APPLYVA <dbl>, ARMY <dbl>, ASIANI <dbl>, AWAREHL <dbl>, BENBRF <dbl>,
## # BLACK <dbl>, BUILDNG <dbl>, BUROPT1 <dbl>, BUROPT2 <dbl>, BUROPT3 <dbl>,
## # BUROPT4 <dbl>, BUROPT5 <dbl>, BUROPT6 <dbl>, BUROPT7 <dbl>, BURPREF <dbl>,
## # CGUARD <dbl>, CHINESE <dbl>, COPAY1 <dbl>, COPAY2 <dbl>, COPAY3 <dbl>,
## # COPAY4 <dbl>, COPAY5 <dbl>, COPAY6 <dbl>, COPAY7 <dbl>, COPAY8 <dbl>, …names(df)## [1] "ACCESWEB" "ACTEVER" "ACTLAST" "ACTNEW" "ADDRESS" "AGREE1"
## [7] "AGREE2" "AGREE3" "AGREE4" "AGREE5" "AGREE6" "AGREE7"
## [13] "AGREE8" "AGREE9" "AIAN" "AIDNEED" "AIRF" "APPEAR1"
## [19] "APPEAR2" "APPLYVA" "ARMY" "ASIANI" "AWAREHL" "BENBRF"
## [25] "BLACK" "BUILDNG" "BUROPT1" "BUROPT2" "BUROPT3" "BUROPT4"
## [31] "BUROPT5" "BUROPT6" "BUROPT7" "BURPREF" "CGUARD" "CHINESE"
## [37] "COPAY1" "COPAY2" "COPAY3" "COPAY4" "COPAY5" "COPAY6"
## [43] "COPAY7" "COPAY8" "COPAY9" "COPAY10" "COPAY11" "COPAY12"
## [49] "COPAY13" "COVPROS" "COVPROV1" "COVPROV2" "COVPROV3" "COVPROV4"
## [55] "COVPROV5" "COVPROV6" "COVPROV7" "CTREMAIL" "CTRWEB" "CURHINOS"
## [61] "CURHINS1" "CURHINS2" "CURHINS3" "CURHINS4" "CURHINS5" "CURHINS6"
## [67] "CURHINS7" "CURHINS8" "CURHINS9" "CURSCD" "DEGREE" "DENTAL6"
## [73] "DEPEND1" "DEPEND2" "DOBYYYY" "EDUACT1" "EDUACT2" "EDUACT3"
## [79] "EDUACT4" "EDUCOS" "EDUCREC" "EDUCTYP" "EDUCVA" "EDUCVA1"
## [85] "EDUCVA2" "EDUCVA3" "EDUCVA4" "EDUCVA5" "EDUCVA6" "EDUCVA7"
## [91] "EDUCVA8" "EDUCVAOS" "EDUGOAL" "ELSEMAIL" "EMAIL" "EMERG6"
## [97] "EQUIP6" "EVDIS" "EVENT" "EVERUSHL" "EVEXP" "EVHZRD"
## [103] "EVOCR1" "EVOCR2" "EVOCR3" "EVOCR4" "EVOCR5" "EVOCR6"
## [109] "EVOCR7" "EVOCROS" "EVPRIS" "EVSCD" "EVSMOK" "EVVOC"
## [115] "EYE6" "FILIPINO" "FINALWGT" "FRONT" "FUTURHC" "GENDER"
## [121] "GENDER1" "GETNEWS" "GOODSERV" "GROUND" "GUAMCHAM" "HBOUND"
## [127] "HEARD1" "HEARD2" "HEARD3" "HEARD4" "HEARD5" "HEARD6"
## [133] "HEARD7" "HISPANIC" "HISPANOS" "HLTH1" "HLTH2" "HLTHWEB"
## [139] "HOMEMAIL" "HOMEWEB" "HOWHL" "ID" "IMPDIS" "IMPVOC"
## [145] "INCOM1" "INCOM2" "INHC" "INHOM6" "INTERNET" "JOBEMAIL"
## [151] "JOBH1" "JOBH2" "JOBH3" "JOBH4" "JOBH5" "JOBH6"
## [157] "JOBHOS" "JOBMATCH" "JOBPREP" "LENDER" "LIBEMAIL" "LIBWEB"
## [163] "LIVARRAG" "LKBUR" "LKCP" "LKEDU" "LKHC" "LKHCF"
## [169] "LKHL" "LKLI" "LKPRES" "LKSURV" "LKTRAN" "LKVOCR"
## [175] "MARINE" "MARKER" "MARRY" "MCARECO1" "MCARECO2" "MCARECO3"
## [181] "MEDICADV" "MEDICD1" "MEDICD2" "MEDICD3" "MEDICD4" "MEDICD5"
## [187] "MEDICD6" "MEDICD7" "MEDICD8" "MEDICD9" "MEDICD10" "MEDICD11"
## [193] "MEDICD12" "MEDICD13" "MEDICR1" "MEDICR2" "MEDICR3" "MEDICR4"
## [199] "MEDICR5" "MEDICR6" "MEDICR7" "MEDICR8" "MEDICR9" "MEDICR10"
## [205] "MEDICR11" "MEDICR12" "MEDICR13" "MEDICSUP" "MILTIME" "MPAYR"
## [211] "NATHAWAI" "NAVY" "NEEDA1" "NEEDA2" "NEEDA3" "NEEDA4"
## [217] "NEEDA5" "NEEDA6" "NEEDA7" "NEEDA8" "NEEDA9" "NEEDA10"
## [223] "NEEDA11" "NEVHC1" "NEVHC2" "NEVHC3" "NEVHC4" "NEVHC5"
## [229] "NEVHC6"There are also public-use files on veterans located on the web.
For example, one set of public-use data can be accessed here.