Package: vvauditor 0.7.0

vvauditor: Creates Assertion Tests

Offers a comprehensive set of assertion tests to help users validate the integrity of their data. These tests can be used to check for specific conditions or properties within a dataset and help ensure that data is accurate and reliable. The package is designed to make it easy to add quality control checks to data analysis workflows and to aid in identifying and correcting any errors or inconsistencies in data.

Authors:Tomer Iwan [aut, cre, cph], Hajo Bons [aut, cph]

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vvauditor.pdf |vvauditor.html✨
vvauditor/json (API)

# Install 'vvauditor' in R:
install.packages('vvauditor', repos = c('https://tin900.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.00 score 7 scripts 164 downloads 55 exports 45 dependencies

Last updated 8 days agofrom:56c9c19f1f. Checks:8 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 10 2025
R-4.5-winOKFeb 10 2025
R-4.5-macOKFeb 10 2025
R-4.5-linuxOKFeb 10 2025
R-4.4-winOKFeb 10 2025
R-4.4-macOKFeb 10 2025
R-4.3-winOKFeb 10 2025
R-4.3-macOKFeb 10 2025

Exports:assert_date_namedassert_field_consistencyassert_field_distinctnessassert_field_existenceassert_logical_namedassert_missing_valuesassert_no_duplicates_in_groupassert_range_validationassert_type_consistencyassertion_messagecalculate_category_percentagescheck_double_columnscheck_duplicatescheck_na_columnscheck_no_duplicate_rowscheck_no_duplicates_in_groupcheck_non_zero_rowscheck_numeric_or_integer_typecheck_posixct_typecheck_rowscheck_zero_columnscount_more_than_1create_categorical_detailscreate_data_typescreate_dataset_summary_tablecreate_field_infocreate_numeric_detailscreate_subset_fieldsdrop_na_column_namesduplicates_in_columnfind_common_columnsfind_maximum_valuefind_minimum_valuefind_pattern_rget_distribution_statisticsget_first_element_classget_valuesidentify_join_pairsidentify_outliersis_unique_columnmd_complete_casesregex_content_parameterregex_timeregex_year_dateremove_duplicates_and_naretrieve_function_callsretrieve_functions_and_packagesretrieve_package_usageretrieve_sourced_scriptsretrieve_string_assignmentsreturn_assertions_messagerun_all_assertionsstr_detect_in_filetest_all_equalunique_id

Dependencies:askpassbackportsbitbit64checkmateclicliprcpp11crayoncurldplyrfansifindRgenericsgluehmsjanitorkitlifecyclelubridatemagrittrpdftoolspillarpkgconfigprettyunitsprogresspurrrqpdfR6Rcppreadrrlangsnakecasestringistringrsystibbletidyrtidyselecttimechangetzdbutf8vctrsvroomwithr

Creating Dataset Summary Tables

Rendered fromdataset-summary.Rmdusingknitr::rmarkdownon Feb 10 2025.

Last update: 2025-02-10
Started: 2024-02-27

Readme and manuals

Help Manual

Help pageTopics
Assert Date Value in Columnassert_date_named
Check if the fieldnames of the dataset are the sameassert_field_consistency
Assert Field Uniqueness Consistency Between Data and Metadataassert_field_distinctness
Assert Field Existence in New Dataassert_field_existence
Assert Logical Value in Columnassert_logical_named
Assert Consistency of Missing Values in Dataassert_missing_values
Assert No Duplicates in Groupassert_no_duplicates_in_group
Assert Range Validation for Data Fieldsassert_range_validation
Assert Type Consistency Between Data and Metadataassert_type_consistency
Assert Message Based on Typeassertion_message
Calculate the percentage of categories in a data vectorcalculate_category_percentages
check double columnscheck_double_columns
Check for Duplicate Rows in Selected Columnscheck_duplicates
Check for columns with only NA valuescheck_na_columns
Check for No Duplicate Rowscheck_no_duplicate_rows
Check for No Duplicates in Groupcheck_no_duplicates_in_group
Check for Non-Zero Rowscheck_non_zero_rows
Check for Numeric or Integer Typecheck_numeric_or_integer_type
Check for POSIXct Typecheck_posixct_type
Check rowscheck_rows
Check for Columns with Only 0scheck_zero_columns
Count more than 1count_more_than_1
Create categorical details csvcreate_categorical_details
Create data types tibblecreate_data_types
Create dataset summary statistics tablecreate_dataset_summary_table
Create field infocreate_field_info
Create numeric details csvcreate_numeric_details
Create subset fieldscreate_subset_fields
Drop NA column namesdrop_na_column_names
Duplicates in columnduplicates_in_column
Find Common Columns Between Data Framesfind_common_columns
Find the maximum numeric value in a vector, ignoring non-numeric valuesfind_maximum_value
Find the minimum numeric value in a vector, ignoring non-numeric valuesfind_minimum_value
Find pattern in R scriptsfind_pattern_r
Compute distribution statistics for a numeric vectorget_distribution_statistics
Retrieve the class of the first element of a vectorget_first_element_class
Get values of columnget_values
Identify Possible Join Pairs Between Data Framesidentify_join_pairs
Identify Outliers in a Data Frame Columnidentify_outliers
Check if a column in a dataframe has unique valuesis_unique_column
MD complete casesmd_complete_cases
Construct Regex for Matching Function Parameter Contentregex_content_parameter
Generate regular expression of a time.regex_time
Generate regular expression of a year date.regex_year_date
Remove Duplicates and NA Values from Inputremove_duplicates_and_na
retrieve_function_callsretrieve_function_calls
Retrieve functions and packagesretrieve_functions_and_packages
Retrieve packages that are loaded in a scriptretrieve_package_usage
retrieve_sourced_scriptsretrieve_sourced_scripts
retrieve_string_assignmentsretrieve_string_assignments
Return Assertion Messagesreturn_assertions_message
Read and return the mtcars testfilereturn_mtcars_testfile
Run All Data Validation Assertionsrun_all_assertions
Detect string in filestr_detect_in_file
Test all equaltest_all_equal
unique idunique_id