A Beginner’s Guide to Making Infographics

MargaretDesign Tools, Visual Creation ToolsLeave a Comment

Here’s an excellent article from Rachel Banning-Lover on The Guardian, intended particularly for NGOs and relief workers,  via the Global Development Professionals Network | Guardian Professional.


How to make infographics: a beginner’s guide to data visualisation

Physicians for human rights Syria map

An interactive map of attacks on health care in Syria – the blue spots show attacks by government forces. Photograph: Physicians for Human Rights

As a growing number of international NGOs are using infographics, charts and interactive maps to share success and highlight disaster, how can organisations with less resources create high quality visualisations without having to pay to outsource them?

We’ve put together a beginner’s guide for visualising development data.

Organising your data

The first thing you need to do is have a clear idea of the data you want to visualise. Are you trying to highlight a particular disparity between money spent in one place and another? Are you trying to show a volume of activity going on in one location?

Let’s imagine I’m running a campaign calling for better sanitation worldwide. To get my message across, I want to highlight how many countries still have poor access to clean toilets and and how little access has changed in over a decade since the MDGs were set. For the purpose of this tutorial, I’ll be using a dataset from the World Bank on access to improved sanitation facilities around the world.

While I have data for over 10 years, I just want the figures for 2000 and 2012, so the first thing I need to do is remove any irrelevant columns and rows (tip: save a separate copy of the original first).


Spreadsheet uncleaned
What my spreadsheet of data first looked like when I downloaded it. Photograph: Rachel Banning-Lover


spreadsheet cleaned
I’ve now deleted the country code column and all the years, except 2000 and 2012. I also removed all non-African countries. Photograph: Rachel Banning-Lover

Once you’ve cleaned-up your data, you’re ready to visualise it. In this case before I visualised my data I also added a fourth column – the percentage difference between the 2000 and 2012 figures.

How to build a chart

Showing your data in a chart is the quickest and easiest way to visualise information. Datawrapper, Infogr.am and PiktoChart are all user friendly sites for building sleek, easy-to-customise charts that can be easily embedded on websites and are responsive to all screen sizes.

Datawrapper is perhaps the most intuitive and it’s free. A disadvantage of building charts though is that they’re not great at displaying large quantities of information, so I’m just going to display the most-improved 10 countries between 2000-2012. Here’s a quick walkthrough of how I made the chart:

  1. Create an account, then click on new chart.
  2. Copy and paste your data into the box.
  3. Check and describe your data – you can click on individual cells or columns to edit. Note how I added % to the numbers and rounded the numbers to 0 decimal places by editing a column.
  4. Now comes the fun bit – picking a chart template. I went with a simple column chart with interactive tabs, but there are a range of options to select from.
  5. The last step is to refine your chart. You can change the colours of the bars, add a title, a description, change the frame size of your chart and so on.

How to build a map

To highlight a large amount of data for different countries, using a map is a better option. Here’s a round-up of the best free tools for beginners.


Datawrapper now offers a choropleth map option which allows you to differentiate between the highest and lowest value data by colour gradient. You’d build it the same way as a Datawrapper chart.

Pros: The quickest option. It will prompt you when country names don’t correspond with country shapes. When building a map, no matter what the software, you may have to go back to your spreadsheet a couple of times to tweak country names. For the map below, I had to change Democratic Republic of Congo to Congo – Kinshasa for it to show up. Another benefit of Datawrapper is that if you hover over different parts of the legend, only the countries in that colour will appear.

Cons: Map templates are not available for visualising cities or individual countries.

Google Fusion Tables

Pros: Completely free, and particularly easy for creating point maps.

Cons: Not as intuitive as it first appears – for beginners, the choropleth map options are rather dated, although intermediate users who learned how to merge KML shapefiles with existing data tables, can create better maps. You cannot add map legends easily.


While CartoDB looks intimidating at first, it offers a number of the advanced customisable features that come with Tableau – definitely worth a look for intermediate mappers, or people who want to combine maps and charts onto one visualisation.

Pros: Easy to use and do basic-intermediate customisations; visualisations look sleek; can easily build country chloropleth maps or point maps for data with more specific locations; can add multiple layers. Works on mobile.

Cons: You have to pay if you’re anticipating using the tool to create more than 5 maps that will get more than 10,000 views a month. Layers appear on top of each other, rather than side by side. Maps are fantastic to view fullscreen, but I had to hide the legends and title box to best fit the frame size for this page.

How to build a traditional infographic

Infographics are traditionally static, a colourful page layout bursting with icons and statistics. Info.gram and Piktochart are both tools worth exploring for this purpose. Both are simple to use, with drag-and-drop features and provide the option to copy and paste data to create charts. However, templates on both are limited with a free account.

Here is a quick example using the sanitation dataset.

Further resources

This guide is not a comprehensive list of all the tools out there. In the comment threads below, do tell us below what experiences you’ve had doing data visualisations for development, and share your favourite tools and development infographics.


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