dataquieR’s workflow uses data and metadata for data quality reporting:

The main function for reporting is dq_report2, and this tutorial shows how to use it.

Installation

The first step is to install dataquieR:

install.packages("dataquieR")

Afterwards, we load it to use its functions:

library(dataquieR)

Loading data and metadata

We can the load data using:

sd1 <- prep_get_data_frame("ship")

This data set has 2154 observations and 33 variables:

View(sd1)
id exdate age sex obs_bp obs_soma obs_int dev_bp dev_length dev_weight
3861 1998-09-22 65 1 9 9 11 18 11 11
6506 1998-01-21 70 1 4 4 3 9 3 1
6096 1999-04-07 43 2 4 4 2 10 3 1
6674 2000-10-06 55 2 3 5 2 22 4 1
6490 1998-11-17 69 2 7 7 12 18 11 11
5366 1997-11-27 65 1 5 5 1 10 3 1
5735 1999-09-01 40 2 7 7 23 15 11 11
4031 1999-08-12 51 2 9 9 12 20 11 11
3578 2000-02-26 25 1 9 9 22 15 11 11
4807 2000-07-13 80 2 3 3 2 18 4 1


Next, we load the corresponding metadata using:

prep_load_workbook_like_file("ship_meta_v2")

The metadata is a workbook containing several sheets or tables that can be called individually if needed.

For more information on the example data and metadata, see the example data description and the metadata tutorial.

Generating a report

We can create a default report using dq_report2(), which requires only the data and metadata previously loaded:

my_dq_report <- dq_report2(study_data = sd1) # metadata will be found, if prep_load_workbook_like_file run before.
print(my_dq_report)

Minimal workflow example

The animation below shows a quick workflow for reporting data quality with dataquieR:

The report is a mini web page (HTML format) that can be viewed in any browser. You can see the example report generated by dq_report2() here.

Example code

The code shown in the animation to produce a report is given here:

# Quick data quality reporting with dataquieR

# Installation
install.packages("dataquieR")

# For further information and to install the development version  
# please see our website: https://dataquality.ship-med.uni-greifswald.de/DownloadR.html

# Load the package
library(dataquieR)

# Load the data (Study of Health in Pomerania example data)
sd1 <- prep_get_data_frame("ship")

# View the data
View(sd1)

# Load the metadata
prep_load_workbook_like_file("ship_meta_v2")

# Compute a report
my_dq_report <- dq_report2(study_data = sd1,
                           meta_data_v2  = "ship_meta_v2",
                           label_col  = LABEL)

# View the results
print(my_dq_report)

The function dq_report2() and print() can manage further arguments and settings. However, this sparse version is a good start to gaining insight into the data and may serve as the base to tailor more specific reports.