| assess_completeness {eHDPrep} | R Documentation |
Assess completeness of a dataset
Description
Assesses and visualises completeness of the input data across both rows (samples) and columns (variables).
Usage
assess_completeness(data, id_var, plot = TRUE)
Arguments
data |
A data frame, data frame extension (e.g. a tibble), or a lazy data frame (e.g. from dbplyr or dtplyr). |
id_var |
An unquoted expression which corresponds to a variable (column) in
|
plot |
Should plots be rendered when function is run? (Default: TRUE) |
Details
Returns a list of completeness assessments:
- variable_completeness
A tibble detailing completeness of variables (columns) (via
variable_completeness).- row_completeness
A tibble detailing completeness of rows (via
row_completeness).- completeness_plot
A plot of row and variable (column) completeness (via
plot_completeness).- completeness_heatmap
A clustered heatmap of cell completeness (via
completeness_heatmap).- plot_completeness_heatmap
A function which creates a clean canvas before plotting the completeness heatmap.
Value
list of completeness tibbles and plots
See Also
Other measures of completeness:
compare_completeness(),
completeness_heatmap(),
plot_completeness(),
row_completeness(),
variable_completeness()
Examples
data(example_data)
res <- assess_completeness(example_data, patient_id)
# variable completeness table
res$variable_completeness
# row completeness table
res$row_completeness
# show completeness of rows and variables as a bar plot
res$completeness_plot
# show dataset completeness in a clustered heatmap
# (this is similar to res$completeness_heatmap but ensures a blank canvas is first created)
res$plot_completeness_heatmap(res)