``` r
library(tidyverse)

gss_clean <- gss_cat %>%
  filter(race != "Other", marital != "No answer") %>%
  mutate(relig = recode(relig, Protestant = "Protestant", .default = "Not Protestant"),
         marital = recode(marital, Married = "Married", .default = "Not married"),
         race = fct_drop(race))

gss_all_3 <- gss_clean %>%
  group_by(marital, race, relig) %>%
  nest()

gss_race_marriage <- gss_clean %>%
  group_by(marital, race) %>%
  nest()

gss_marriage <- gss_clean %>%
  group_by(marital) %>%
  nest()

bind_rows(gss_all_3, gss_race_marriage, gss_marriage) %>%
  ungroup() %>%
  arrange(marital, race, relig) %>%
  mutate(summary = data %>% map(~ summarize(., avg_age = mean(age, na.rm = TRUE),
                                            sd_age = sd(age, na.rm = TRUE),
                                            N = n()))) %>%
  unnest(summary)
#> # A tibble: 14 x 7
#>    marital     race  relig          data              avg_age sd_age     N
#>    <fct>       <fct> <fct>          <list>              <dbl>  <dbl> <int>
#>  1 Not married Black Not Protestant <tibble [672 × 6…    38.6   15.5    14
#>  2 Not married Black Protestant     <tibble [1,586 ×…    44.8   17.1    14
#>  3 Not married Black <NA>           <tibble [2,258 ×…    42.9   16.9    14
#>  4 Not married White Not Protestant <tibble [4,389 ×…    44.4   18.7    14
#>  5 Not married White Protestant     <tibble [3,677 ×…    51.7   19.8    14
#>  6 Not married White <NA>           <tibble [8,066 ×…    47.7   19.5    14
#>  7 Not married <NA>  <NA>           <tibble [10,324 …    46.7   19.1    14
#>  8 Married     Black Not Protestant <tibble [185 × 6…    42.8   11.6    14
#>  9 Married     Black Protestant     <tibble [684 × 6…    47.4   13.7    14
#> 10 Married     Black <NA>           <tibble [869 × 7…    46.4   13.4    14
#> 11 Married     White Not Protestant <tibble [3,810 ×…    47.8   14.6    14
#> 12 Married     White Protestant     <tibble [4,506 ×…    51.3   15.6    14
#> 13 Married     White <NA>           <tibble [8,316 ×…    49.7   15.2    14
#> 14 Married     <NA>  <NA>           <tibble [9,185 ×…    49.4   15.1    14
```