Run all of the checks from the package against the data and metadata objects.
Arguments
- data
data.frame, for the data table, more efficient if supplied as a lazy duckplyr data.frame
- meta
data.frame, for the metadata table
- verbose
logical, if TRUE prints feedback messages to console for every test, if FALSE run silently
- stop_on_error
logical, if TRUE will stop with an error if the result is "FAIL", and will throw genuine warning if result is "WARNING"
Examples
screen_dfs(example_data, example_meta)
#> check result
#> 1 col_req_meta PASS
#> 2 col_invalid_meta PASS
#> 3 col_req_data PASS
#> 4 col_to_rows PASS
#> 5 meta_col_type PASS
#> 6 meta_ob_unit PASS
#> 7 meta_col_name PASS
#> 8 meta_col_name PASS
#> 9 time_id_valid PASS
#> 10 check_api_char_limit_column-name PASS
#> message
#> 1 All of the required columns are present in the metadata file.
#> 2 There are no invalid columns in the metadata file.
#> 3 All of the required columns are present in the data file.
#> 4 There are an equal number of rows in the metadata file (3) and non-mandatory columns in the data file (3).
#> 5 col_type is always 'Filter' or 'Indicator'.
#> 6 No observational units have been included in the metadata file.
#> 7 The col_name column is completed for every row in the metadata.
#> 8 The indicator_dp column is completed for all indicators.
#> 9 The time_identifier values are all valid.
#> 10 All filter / indicator names are less than or equal to the character limit of 50.
#> guidance_url stage
#> 1 NA Precheck columns
#> 2 NA Precheck columns
#> 3 NA Precheck columns
#> 4 NA Precheck columns
#> 5 NA Precheck meta
#> 6 NA Precheck meta
#> 7 NA Precheck meta
#> 8 NA Check meta
#> 9 NA Precheck time
#> 10 NA Check API