Get a list of measures (a codebook) that are included in a data collection project.
Usage
dcf_variables(project = ".", exclude = c("geography", "time", "age"), ...)Arguments
- project
Path to a local project, or the GitHub account and repository name (
"{account_name}/{repo_name}") of a remote project. Or a report as returned fromdcf_report.- exclude
A character vector of variable names to exclude from the list (usually ID columns).
- ...
Additional arguments passed to
dcf_report.
Value
A tibble containing variables:
name | Name of the variable, as it appears in the data file. |
type | The value's storage type. |
n | Number of non-missing observations within the file. |
duplicates | Number of duplicated values within the file. |
missing | Number of missing values within the file. |
project_type | The project type, between source and bundle. |
data_format | The orientation of the data, between wide and tall. |
file | The file containing the variable; a path relative to the project root. |
short_name | Short name, if included in measure info. |
long_name | Long name, if included in measure info. |
short_decription | Short description, if included in measure info. |
long_description | Long description, if included in measure info. |
measure_type | Higher-level description of type than storage type
(e.g., count versus integer), if included in measure info. |
unit | How a single value should be interpreted
(e.g., per 100k people for a rate per 100k people), if included in measure info. |
time_resolution | The measure's collection frequency, if included in measure info. |
category | The measure's category, if included in measure info. |
subcategory | The measure's subcategory, if included in measure info. |
See also
Other data user interface functions:
dcf_data(),
dcf_report()
Examples
dcf_variables("dissc-yale/pophive_demo")
#> # A tibble: 49 × 17
#> name type n duplicates missing project_type data_format file
#> <chr> <chr> <int> <int> <int> <chr> <chr> <chr>
#> 1 epic_all_encou… inte… 7074 23297 22149 bundle wide data…
#> 2 epic_covid inte… 7074 27988 22149 bundle wide data…
#> 3 epic_flu inte… 7074 27977 22149 bundle wide data…
#> 4 epic_rsv inte… 6943 28695 22280 bundle wide data…
#> 5 gtrends_rsv_va… float 17576 22167 11647 bundle wide data…
#> 6 gtrends_naloxo… float 17576 19924 11647 bundle wide data…
#> 7 gtrends_overdo… float 17524 12684 11699 bundle wide data…
#> 8 gtrends_rsv float 17576 14629 11647 bundle wide data…
#> 9 wastewater_cov… float 10976 18676 18247 bundle wide data…
#> 10 wastewater_flua float 8561 25265 20662 bundle wide data…
#> # ℹ 39 more rows
#> # ℹ 9 more variables: short_name <chr>, long_name <chr>,
#> # short_description <chr>, long_description <chr>, measure_type <chr>,
#> # unit <chr>, time_resolution <chr>, category <chr>, subcategory <chr>