The point of the code is to isolate specific populations from a large database of enteries. Where do I go to get help with that? Sorry for the noob post
Getting there depends a lot on your source data. I'm going to illustrate with an example of a CSV (comma separated value) file, which is one of the
Save as options in Excel.
suppressPackageStartupMessages(library(tidyverse)) suppressPackageStartupMessages(library(knitr)) suppressPackageStartupMessages(library(kableExtra)) library(tidyverse) library(knitr) library(kableExtra) knitr::opts_chunk$set(echo = TRUE) converter <- read.csv("https://gist.githubusercontent.com/technocrat/93470bf9abead06ef926/raw/f652f8171374e7808455f42167f5480ea15f7f4e/state_fips_postal.csv", header = FALSE, stringsAsFactors = FALSE) converter <- rename(converter, NAME = V1, geoid = V2, id = V3) states_key <- as.tibble(converter) %>% filter(id != 'DC') kable(converter, format.args = list(big.mark = ","), caption = "State Postal Abbreviations with FIPS Codes") %>% kable_styling(bootstrap_options = "striped", full_width = F)
which will get you to:
filtered <- converter %>% filter(NAME == "Wyoming" | geoid == 23) kable(filtered, format.args = list(big.mark = ","), caption = "Selected State Postal Abbreviations with FIPS Codes") %>% kable_styling(bootstrap_options = "striped", full_width = F)
as shown here:
Illustration.pdf (49.9 KB)
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