R/07-data_summarize.R
summary_variables_numeric.Rd
Summarizes (in a data frame) the columns of type 'numeric' in a dataset and its data dictionary (if any). The summary provides information about quality, type, composition, and descriptive statistics of variables. Statistics are generated by valueType.
summary_variables_numeric(dataset_preprocess, dataset = NULL, data_dict = NULL)
A data frame which provides summary of the variables (for internal processes and programming).
A dataset object.
A list of data frame(s) representing metadata of the input dataset. Automatically generated if not provided.
A data frame providing statistical description of 'numerical' variables present in a dataset.
A data dictionary contains the list of variables in a dataset and metadata
about the variables and can be associated with a dataset. A data dictionary
object is a list of data frame(s) named 'Variables' (required) and
'Categories' (if any). To be usable in any function, the data frame
'Variables' must contain at least the name
column, with all unique and
non-missing entries, and the data frame 'Categories' must contain at least
the variable
and name
columns, with unique combination of
variable
and name
.
A dataset is a data table containing variables. A dataset object is a data frame and can be associated with a data dictionary. If no data dictionary is provided with a dataset, a minimum workable data dictionary will be generated as needed within relevant functions. Identifier variable(s) for indexing can be specified by the user. The id values must be non-missing and will be used in functions that require it. If no identifier variable is specified, indexing is handled automatically by the function.
{
# use madshapR_examples provided by the package
dataset <- madshapR_examples$`dataset_example`
dataset_preprocess <- dataset_preprocess(dataset)
summary_prep <- summary_variables_numeric(
dataset_preprocess = dataset_preprocess[[1]])
head(summary_prep)
}
#> # A tibble: 6 × 8
#> `Variable name` Minimum `1st quartile` Median `3rd quartile` Maximum Mean
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 gndr -77 1 1 2 2 -6.34
#> 2 height 149 164. 171 181 197 173.
#> 3 weight_ms -88 52 59 66 95 50.9
#> 4 weight_dc 45 60.5 75 84.5 142 75.1
#> 5 prg_ever -7 -7 -7 1 9 -2.44
#> 6 empty NA NA NA NA NA NA
#> # ℹ 1 more variable: `Standard deviation` <dbl>