Download Data Dictionary (CSV)
Code
data_dictionary <- read.csv(file = here("data/final_codebook.csv"))
Categorical, Dates, and Factors:
Code
data_dictionary %>% filter(class != "integer") %>%
kbl(
align = "cclcc",
col.names =
c("Variable Name", "Class/Type", "Definition",
"Unique Values", "Example Format")
) %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed", "bordered")
) %>%
row_spec(0,
bold = TRUE,
background = "#0f172a",
extra_css = "font-size: 16px!important;color:#ffffff;"
)
| end_date |
Date |
last date of Epi week |
31 |
format: 2023-06-03 |
| start_date |
Date |
first date of Epi week |
31 |
format: 2023-05-28 |
| county |
character |
county of residence of cases |
58 |
Alameda |
| health_officer_region |
character |
California Health Officer Region |
6 |
Bay Area |
| race_coded |
character |
race category codes |
7 |
1, 2, 3, 4, 5, 6, 7 |
| race_long |
character |
race category full text |
7 |
Black, Non-Hispanic |
| race_short |
character |
race category abbreviated text |
7 |
Black NH |
| sex |
character |
sex categorization |
2 |
FEMALE, MALE |
| age_cat |
factor |
age category |
4 |
0-17, 18-49, 50-64, 65+ |
| mmwr_week |
factor |
epi week 40 in 2022 to epi week 23 in 2023 |
31 |
22:52 |
| mmwr_year |
factor |
year |
1 |
2023 |
Numeric:
Code
data_dictionary %>%
filter(class == "integer") %>%
select(-unique_n) %>%
kbl(
align = "cclc",
col.names =
c("Variable Name", "Class/Type", "Definition",
"Range of Values")
) %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed", "bordered")
) %>%
row_spec(0,
bold = TRUE,
background = "#0f172a",
extra_css = "font-size: 16px!important;color:#ffffff;"
)
| cumulative_infected |
integer |
total number of diagnosed individuals |
0 - 137804 |
| cumulative_severe |
integer |
total number infected requiring hospitalization |
0 - 4060 |
| cumulative_unrecovered |
integer |
total number unrecovered after a week of diagnosis |
0 - 16920 |
| new_infections |
integer |
newly diagnosed individuals |
0 - 12110 |
| new_severe |
integer |
newly identified cases requiring hospitalization |
0 - 352 |
| new_unrecovered |
integer |
newly reported as unrecovered |
0 - 1436 |
| pop |
integer |
estimated population by age group, race, and sex by county for year 2023 |
0 - 980387 |
| total_cnty_pop |
integer |
total population estimate by county |
1165 - 9825708 |
| total_race_pop |
integer |
total county population by race/ethnicity |
0 - 4089110 |
| total_age_pop |
integer |
total county population by age category |
182 - 1492414 |
| total_sex_pop |
integer |
total county pouplation by sex |
548 - 5049625 |
| total_HOR_pop |
integer |
total population by Health Officer Region |
683715 - 12802429 |