Getting started

What is overviewR?

overviewR is a small yet powerful package that helps you to get an overview – hence, the name – of your data with particular emphasis on the extent that your distinct units of observation are covered for the entire time frame of your data set.

How can you install it?

A stable version of overviewR can be directly accessed on CRAN:

install.packages("overviewR", force = TRUE)

To install the latest development version of overviewR directly from GitHub use:


Why did we build it?

If you have a (large) data set that has many different observations over a long period, it becomes increasingly difficult to identify for each unique observation its exact coverage in the data. In particular, if some observations are not included for the entire time span of the data – either because they entered later, dropped out earlier or have gaps in between – it can become difficult to spot potential problems in your data’s time and scope.

overviewR allows you to quickly get a glimpse of your data and the distribution of your observations over time. With its ability to produce both data.frame objects and LaTeX/.tex outputs, it can be used by practitioners and academics alike.

How can it be used?

overviewR can be used by everyone who works with data that have time-and-scope characteristics. That is, all data that contains different units of observation over a specific period will benefit from overviewR. To get a quick overview of which units – think of countries, companies, test persons, etc. – are present or missing during a given time span – think of years, months, days, minutes, etc. – overviewR provides an easy and intuitive insight into the set-up of your data.

Consider a data set that covers countries over the past 50 years. Not all countries existed throughout the entire period – some dissolved, others were newly founded and yet for others, data might not be available for the entire period. Before starting any analysis, it is helpful to get an overview not only of which countries are included and what the entire time span is but also to see which countries are present at which points in time. In other words, are there missing data for certain countries at different points in time?

To get a quick and intuitive overview of your data, overviewR provides currently the following basic functions:

Overview of functional add-ons

Works with data.frame objects Works with data.table Can take multiple time arguments (year, month, day)
overview_tab yes yes yes
overview_na yes yes
overview_plot yes
overview_crossplot yes
overview_crosstab yes
overview_heat yes
overview_overlap yes

There is also a CheatSheet available here that showcases the functions of overviewR.

Get involved!

Have you used overviewR in your project? Let us know! You can either e-mail us or use our pull-request template and populate/fill the following with your information:


We will feature your project below!

Projects using overviewR