View source: R/read_cbs_muni.R
| read_cbs_muni | R Documentation |
This function is a wrapper around readxl::read_excel(), reading a specific
municipal data file for a specific year and a specific data domain. Its added
value is in its use of row_to_names_fill() and its pre-defined parameters for
every year and its specific quirks in the Excel headers. For advanced users,
the full set of options is available with il.cbs.muni:::df_cbs_muni_params.
read_cbs_muni(
path,
year,
muni_type = c("all", "city_lc", "rc"),
data_domain = c("physical", "budget", "summary", "labor_force_survey", "social_survey"),
cols = NULL,
col_names = NULL
)
path |
A character vector of length 1, denoting the local file path to the municipal data file. A full list of available files by the CBS is at the relevant CBS page. |
year |
A numeric vector of length 1 denoting which year the data file
pointed in |
muni_type |
A character vector of length 1, one of
|
data_domain |
A character vector of length 1, one of
|
cols |
<tidy-select>
Columns to keep. The default |
col_names |
A character vector containing the new column names of the
output tibble. If |
A tibble with municipal data for a specific year, where every row is a municipality and every column is a different variable for this municipality in that year. Be advised all columns are of type character, so you need to parse the data types yourself at will. Column names are merged from the relevant headers, and only single whitespaces are kept. Rows with more than 90% empty cells (usually rows with non-data notes) are removed.
df <- read_cbs_muni(
system.file("extdata", "p_libud_2021.xlsx", package = "il.cbs.muni"),
year = 2021,
data_domain = "physical"
)
df |>
dplyr::select(1:15) |>
dplyr::glimpse()
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