Yes, I see what you mean: > median(c(60, 50, 40, 20, 20, 20)) [1] 30 > median(c(50, 50, 50, 20, 20, 20)) [1] 35 >
Thanks so much for that clear example. -Kevin On 8/7/23 14:45, Sean Trende wrote: > This is correct on the second question, at least for more recent censuses. > On the first question, imagine a block where the ages of three individuals > are 60, 50, and 40, and another one where the ages are 20, 20, and 20. Using > your approach you would have 50 * 3 = 150 for the first block, and 20*3 = 60 > for the second block. The median of 60 and 150 is 105. Even dividing that > by three you get 35, which is not the correct median age (30). > > -----Original Message----- > From: R-sig-Geo <r-sig-geo-boun...@r-project.org> On Behalf Of Josiah Parry > Sent: Monday, August 7, 2023 2:38 PM > To: Kevin Zembower <ke...@zembower.org> > Cc: r-sig-geo@r-project.org > Subject: Re: [R-sig-Geo] Calculating median age for a group of US census > blocks? > > Hey Kevin, I don't think you're going to be able to get individual level data > from the US Census Bureau. The closest you may be able to get is the current > population survey (CPS) which I believe is also available via tidycensus. > Regarding your first question, I'm not sure I follow what your objective is > with it. I would use a geography of census block groups as the measure of > median for census block groups. Otherwise it is unclear how you are defining > what a "group of blocks" is. > > On Mon, Aug 7, 2023 at 2:34 PM Kevin Zembower via R-sig-Geo < > r-sig-geo@r-project.org> wrote: > >> Hello, all, >> >> I'd like to obtain the median age for a population in a specific group >> of US Decennial census blocks. Here's an example of the problem: >> >> ## Example of calculating median age of population in census blocks. >> library(tidyverse) >> library(tidycensus) >> >> counts <- get_decennial( >> geography = "block", >> state = "MD", >> county = "Baltimore city", >> table = "P1", >> year = 2020, >> sumfile = "dhc") %>% >> mutate(NAME = NULL) %>% >> filter(substr(GEOID, 6, 11) == "271101" & >> substr(GEOID, 12, 15) %in% c(3000, 3001, 3002) >> ) >> >> ages <- get_decennial( >> geography = "block", >> state = "MD", >> county = "Baltimore city", >> table = "P13", >> year = 2020, >> sumfile = "dhc") %>% >> mutate(NAME = NULL) %>% >> filter(substr(GEOID, 6, 11) == "271101" & >> substr(GEOID, 12, 15) %in% c(3000, 3001, 3002) >> ) >> >> I have two questions: >> >> 1. Is it mathematically valid to multiply the population of a block by >> the median age of that block (in other words, assign the median age to >> each member of a block), then calculate the median of those numbers >> for a group of blocks? >> >> 2. Is raw data on the ages of individuals available anywhere else in >> the census data? I can find tables such as P12, that breaks down the >> population by age ranges or bins, but can't find specific data of >> counts per age in years. >> >> Thanks for your advice and help. >> >> -Kevin >> >> _______________________________________________ >> R-sig-Geo mailing list >> R-sig-Geo@r-project.org >> https://stat.ethz.ch/mailman/listinfo/r-sig-geo >> > > [[alternative HTML version deleted]] > > _______________________________________________ > R-sig-Geo mailing list > R-sig-Geo@r-project.org > https://stat.ethz.ch/mailman/listinfo/r-sig-geo _______________________________________________ R-sig-Geo mailing list R-sig-Geo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo
