Package 'data.validator'

Add validation results to the Report object

Description

This function adds results to validator object with aggregating summary of success, error and warning checks. Moreover it parses assertr results attributes and stores them inside usable table.

Usage

add_results(data, report)

Arguments

data	Data that was validated.
report	Report object to store validation results.

---

Create new validator object

Description

The object returns R6 class environment responsible for storing validation results.

Usage

data_validation_report()

---

Get validation results

Description

The response is a list containing information about successful, failed, warning assertions and the table stores important information about validation results. Those are:

• table_name - name of validated table

• assertion.id - id used for each assertion

• description - assertion description

• num.violations - number of violations (assertion and column specific)

• call - assertion call

• message - assertion result message for specific column

• type - error, warning or success

• error_df - nested table storing details about error or warning result (like violated indexes and values)

Usage

get_results(report, unnest = FALSE)

Arguments

report	Report object that stores validation results. See add_results.
unnest	If TRUE, error_df table is unnested. Results with remaining columns duplicated in table.

---

Render simple version of report

Description

Renders content of simple report version that prints validation_results table.

Usage

render_raw_report_ui(
  validation_results,
  success = TRUE,
  warning = TRUE,
  error = TRUE
)

Arguments

validation_results	Validation results table (see get_results).
success	Should success results be presented?
warning	Should warning results be presented?
error	Should error results be presented?

---

Render semantic version of report

Description

Renders content of semantic report version.

Usage

render_semantic_report_ui(
  validation_results,
  success = TRUE,
  warning = TRUE,
  error = TRUE,
  df_error_head_n = 6L
)

Arguments

validation_results	Validation results table (see get_results).
success	Should success results be presented?
warning	Should warning results be presented?
error	Should error results be presented?
df_error_head_n	Number of rows to display in error table. Works in the same way as head function.

---

Saving results as a HTML report

Description

Saving results as a HTML report

Usage

save_report(
  report,
  output_file = "validation_report.html",
  output_dir = getwd(),
  ui_constructor = render_semantic_report_ui,
  template = system.file("rmarkdown/templates/standard/skeleton/skeleton.Rmd", package =
    "data.validator"),
  ...
)

Arguments

report	Report object that stores validation results.
output_file	Html file name to write report to.
output_dir	Target report directory.
ui_constructor	Function of validation_results and optional parameters that generates HTML code or HTML widget that should be used to generate report content. See custom_report example.
template	Path to Rmd template in which ui_constructor is rendered. See data.validator rmarkdown template to see basic construction - the one is used as a default template.
...	Additional parameters passed to ui_constructor. For example: df_error_head_n

---

Saving results table to external file

Description

Saving results table to external file

Usage

save_results(report, file_name = "results.csv", method = utils::write.csv, ...)

Arguments

report	Report object that stores validation results. See get_results.
file_name	Name of the resulting file (including extension).
method	Function that should be used to save results table (write.csv default) The function passed to method should have 'x' and 'file' arguments. Functions with different arguments can be passed by creating a wrapper function for it. See example save_results_methods.
...	Remaining parameters passed to method.

---

Save simple validation summary in text file

Description

Saves print(validator) output inside text file.

Usage

save_summary(
  report,
  file_name = "validation_log.txt",
  success = TRUE,
  warning = TRUE,
  error = TRUE
)

Arguments

report	Report object that stores validation results.
file_name	Name of the resulting file (including extension).
success	Should success results be presented?
warning	Should warning results be presented?
error	Should error results be presented?

---

Prepare data for validation chain

Description

Prepare data for validation and generating report. The function prepares data for chain validation and ensures all the validation results are gathered correctly. The function also attaches additional information to the data (name and description) that is then displayed in validation report.

Usage

validate(data, name, description = NULL)

Arguments

data	data.frame or tibble to test
name	name of validation object (will be displayed in the report)
description	description of validation object (will be displayed in the report)

---

Validation on columns

Description

Validation on columns

Usage

validate_cols(
  data,
  predicate,
  ...,
  obligatory = FALSE,
  description = NA,
  skip_chain_opts = FALSE,
  success_fun = assertr::success_append,
  error_fun = assertr::error_append,
  defect_fun = assertr::defect_append
)

Arguments

data	A data.frame or tibble to test
predicate	Predicate function or predicate generator such as in_set or within_n_sds
...	Columns selection that predicate should be called on. All tidyselect language methods are supported. If not provided, all everything will be used.
obligatory	If TRUE and assertion failed the data is marked as defective. For defective data, all the following rules are handled by defect_fun function
description	A character string with description of assertion. The description is then displayed in the validation report
skip_chain_opts	While wrapping data with validate function, success_fun and error_fun parameters are rewritten with success_append and error_append respectively. In order to use parameters assigned to the function directly set skip_chain_opts to TRUE
success_fun	Function that is called when the validation pass
error_fun	Function that is called when the validation fails
defect_fun	Function that is called when the data is marked as defective

See Also

validate_if validate_rows

---

Verify if expression regarding data is TRUE

Description

The function checks whether all the logical values returned by the expression are TRUE. The function is meant for handling all the cases that cannot be reached by using validate_cols and validate_rows functions.

Usage

validate_if(
  data,
  expr,
  description = NA,
  obligatory = FALSE,
  skip_chain_opts = FALSE,
  success_fun = assertr::success_append,
  error_fun = assertr::error_append,
  defect_fun = assertr::defect_append
)

Arguments

data	A data.frame or tibble to test
expr	A Logical expression to test for, e.g. var_name > 0
description	A character string with description of assertion. The description is then displayed in the validation report
obligatory	If TRUE and assertion failed the data is marked as defective. For defective data, all the following rules are handled by defect_fun function
skip_chain_opts	While wrapping data with validate function, success_fun and error_fun parameters are rewritten with success_append and error_append respectively. In order to use parameters assigned to the function directly set skip_chain_opts to TRUE
success_fun	Function that is called when the validation pass
error_fun	Function that is called when the validation fails
defect_fun	Function that is called when the data is marked as defective

See Also

validate_cols validate_rows

---

Validation on rows

Description

Validation on rows

Usage

validate_rows(
  data,
  row_reduction_fn,
  predicate,
  ...,
  obligatory = FALSE,
  description = NA,
  skip_chain_opts = FALSE,
  success_fun = assertr::success_append,
  error_fun = assertr::error_append,
  defect_fun = assertr::defect_append
)

Arguments

data	A data.frame or tibble to test
row_reduction_fn	Function that should reduce rows into a single column that is passed to validation e.g. num_row_NAs
predicate	Predicate function or predicate generator such as in_set or within_n_sds
...	Columns selection that row_reduction_fn should be called on. All tidyselect language methods are supported. If not provided, all everything will be used.
obligatory	If TRUE and assertion failed the data is marked as defective. For defective data, all the following rules are handled by defect_fun function
description	A character string with description of assertion. The description is then displayed in the validation report
skip_chain_opts	While wrapping data with validate function, success_fun and error_fun parameters are rewritten with success_append and error_append respectively. In order to use parameters assigned to the function directly set skip_chain_opts to TRUE.
success_fun	Function that is called when the validation pass
error_fun	Function that is called when the validation fails
defect_fun	Function that is called when the data is marked as defective

See Also

validate_cols validate_if

---