Data Journalism Fellowship Blog.

Once data has been cleaned and uploaded to Google Fusion Tables, it is important that readers comprehend both the map and the data displayed about each geographical region when selected. A chart is one of the ways used to represent this region-by-region data for the readers. Google Charts make it possible to create interactive dynamic charts for the readers.
All that is needed is a custom template for the map information window. The custom template accepts valid HTML to design the appearance of the content displayed in the window. To include a chart that is specific to each row of data, the HTML combines data from each column into a call to the Google Chart API, which will display an image specific for that information window.
In example below, the HTML code for information window has been customized to generate a chart for a Google Fusion Map. It shows sections that need to be changed depending on the table columns and those that need not change. Text enclosed in curly braces { } is the name of columns. When the map pin is clicked, the column name is replaced with the data values for that row in the table, and the URL is called. The image that returns is the chart displayed in the info window. When the data change, the chart will update too.
There is a lot of trial and error to making this work; it all requires patience to produce great results.

This map shows County distribution rate of medical practitioners per 100,000 people for 2012. The bar chart has been used to compare the numbers of nurses, doctors and clinical officers in Kenya. The map is interactive while the charts display county-specific data.

There are many forms of charts used to present data or that can be added to the map information window. Pie charts represent data in percentage form and are used when the data adds up to 100 percent or a whole. From the example below, a pie chart has been used to show hemorrhages as the leading cause of maternal death at 25 per cent.

This same data can be presented in a bar chart. The relationship between the indicators is displayed using bars of different heights. This form of graphical display is suitable for data that does not necessary add up to 100 percent or some other whole.

Of interest however is the relationship between the pie chart and the bar chart and the map, text and images that tell big stories. The information is made easier and faster for the reader to understand, guided by the similar colour use, as the example below of Microsoft acquiring Nokia’s handset devices unit for $7.2 billion.

Combining charts with pictographs enable readers to see relationships among different sets of data in many ways. In the example below, sliced pie charts visualizes the demographic divide between Niger and Netherlands. Other than using two separate colours symbolizing the two countries, the reader is able to see the relationship among them in terms of lifetime births/woman, life expectancy at birth as well as infant mortality rate, per 1000 live births.

In this example, wealth disparities of the six continents has been visualized using doughnut charts of different colour shades, combined with pictures symbolizing the regions. The reader is able to see the percentage income of the wealthiest and poorest continents.

Interactive line charts are used to explore population trends in the US and filter different states of residence of all unauthorized immigrants. The reader is able to choose the state of interest and compare the trend from 1990 and 2012 in relation to the number of immigrants in millions. This is advance way of visualizing data enabling the users to navigate information with ease.

Great visuals communicate information at a glance even before looking at the key. It is upon the visualizer to source for accurate data to be used in the graphic. Good data visualization uses visuals to put data into context for the readers, making the information easier to understand. Simple infographics packages incorporate several charts to provide context to the news story.