Calculating median age for a group of US census blocks?

Josiah, thanks for your reply.

Regarding my objective, I'm trying to compile census statistics for the
blocks that make up the neighborhood where I live. It consists of ten
census blocks, of which I selected three for simplicity in my example.
The census block-group which contains these ten blocks also contains
some blocks which are outside of my neighborhood and shouldn't be
counted or included.

Since I won't be able to calculate the median age from the age and count
data, and since the individual data doesn't seem to be available, is it
your thought that I can't produce a valid median age for a group of
census blocks?

Thanks so much for your advice.

-Kevin

On 8/7/23 14:38, Josiah Parry wrote:

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 at r-project.org <mailto:r-sig-geo at 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