This brief tutorial walks beginners through typical steps needed to create a data visualization. Based on one example you’ll see what needs to be done, from finding data to cleaning data to creating a chart and publish it.
Good preparation is important. Creating a visualization with Datawrapper is essentially the last step. Details matter to make it work.
1. Step: Find data
Look for data providing context related to recent events. To find relevant and interesting information, use one of the perspectives below. Whether you are working with a large or small dataset is not the decisive factor. It’s much more important to ask the right questions. Check the quality of the data. Perform simple math, by checking the sums. Aim to look at the development over a longer time period. Look for inconsistencies, strange outliers or surprising connections and dependancies.
Here are some approaches to get you there:
- Compare: Unemployment figures, education offerings in your region or costs of city services. Are they higher or lower compared to other cities or countries?
- Long time frames: Official sources tend to focus on figures from the last quarter. Often the context and perspective changes when you have data showing development for the last five, ten or even twenty years.
- Per capita: An official statement might promise millions of investment for schools. Sounds great. But have you done the math? How many students will benefit, over what period of time? How much support does each recipient actually get? Recalculating larger programs on a per capita base often clears up the picture and provides a better understanding.
- Check budgets or models: Perform simple checks of sums and totals. Ask questions how the data was gathered and what assumptions or models guided that collection. One example: How is the number of unemployment calculated in your country? Check it. Try to come up with alternative models and compare them.
2. Step: Clean the data
Before starting to visualize you need to clean and prepare the data, whether working with Datawrapper or other tools. Often you simply need to perform a clean up to find the relevant aspects. Slice up a big datatable with many different rows and columns into single views. Then get rid all formatting, special characters, links and other elements. Try to have just the raw data at the end of this process.
Example: A comparison of teacher salaries
To illustrate how this is done, here is a good example: This example compares net income of teachers in selected countries around the world. Salaries have been adjusted based on “purchasing power parity“. In here there are many aspects that are interesting and should lead to a story.
This is how the data looks on the web:
Source: World Salaries
Copy and paste the data into Excel (or a similar software)
Below you see how the copied data looks in a spreadsheet. There are some interesting aspects, but in order to create a telling visualization, we need to focus on one aspect. As a result we delete everything, just keeping “country” and “net monthly income”.
Hint: Make sure that you delete empty rows between the description and the data, too.
Below you’ll see the cleaned up data. You should use the “replace” command to get to this point, do not do it manually. The numbers are already sorted, all extra elements and mark-ups (bold, dots, currency symbols) are gone.
Step 3: Upload your data into Datawrapper
There are two options to upload data into Datawrapper: First by simply copying it in the spreadsheet and then dropping it into the field below. An alternative is to upload a .csv file (an abbreviation for “comma separated values”, think of it as lingua franca for data). If you try to upload a .csv formatting is important, otherwise it won’t work.
Step 4: Check and describe your data
Here you simply check whether the data was imported correctly. There are options to help Datawrapper getting it right:
- You can decide whether the data should be displayed in rows or columns (which has an effect on visualizations). You can go back to this step at any time and change this setting.
- Mark first rows or columns as labels
- Credit and link to the source
Step 5: Visualize
Datawrapper can display data in a number of basic, but versatile variations:
- Lines: Best used to show changes over time and trends. To reduce the number of labels on the axis there is a trick: In Excel or another spreadsheet software simply shorten the years from something like “2001” to “o1”. Another option, especially when you work with many data points is to display only the most important years and leave the others blank. (“1900”, “1910”, “1920”,…).
- Columns: When the values of each year or period have no direct relation to each other or when it is important to display the growth of the values use a column chart instead of a line chart. Datawrapper can display several columns with different values side by side.
- Bars: This variation is useful if you have a lot of labels you need to display. Here this information is on the left side of your visualizations, leaving much more room and making it easier to read.
- Pie: Use this if you want to display parts of a total – like all the smartphones sold in a country. But try to limit the number of pies to a maximum of five, if you have more use a bar or column chart instead.
- Donut: A variation of the pie, with a hole in the middle. You can display the total in the middle by selecting this option in Datawrapper.
Tipp: A handy and often used feature of Datawrapper is “transpose”. With one click you are changing the order of the data, the x- and y-values are switched around. Just experiment with this and use it when your chart does not display as intended. Again, you can jump back and forth between the steps, all your changes will be kept.
Step 6: Publish and embed
Done. In the last step you see your chart and get an embed code. Copy that and drop it into any web editor for publishing.
Hint: For a proper display the width of your visualization is important. If your webpage has a very narrow layout try to reduce the number of values on your x-axis or choose a bar chart.
In some newsrooms editors don’t have permission to use HTML editors. In such cases there should be one user with usage rights allowing this for embedding and publishing.
That’s it. Hope you have fun working with Datawrapper.