Map

When to use a map

The maps on Many Eyes let you overlay data values on geographic regions. You should use a map if you want to see spatial patterns in the data.

How the map works

The map displays data associated with geographic regions using either colors or bubbles.

For example, you may want to compare the ratio of exports to GDP of different countries. If you choose the color mode, each region will be colored according to its export ratio. In the image above, regions colored dark brown have the highest amount of exports and countries in pale colors have low amounts of exports. (If data is missing for a region, such as for the United States in the above example, it will appear as an empty "hole" in the map.) Mousing over a country will display the exact value.

The map can also show categorical values (e.g., language spoken). It will interpret text columns as categories, and will fill countries with a different color for each category.

Colors vs. Bubbles

Colored maps are not always the best way to display values, since large regions are emphasized much more than small ones. To address this issue, the map provides an alternate "bubble" mode in which values are represented by circles. The area of each circle corresponds to the absolute value of the data, with blue circles indicating negative numbers.

To switch the map between color and bubble modes, click the mode buttons (highlighted below) in the map toolbar.

Selecting regions

Clicking on a region will highlight it, which is often helpful when making comments. Clicking on a range in the legend will select all regions on the map whose values fall within that range. In the example below, clicking on the highest value range for exports helps us to find the interesting outliers in this dataset: Luxembourg and Malaysia.

Zooming

Zoom in and out on the map using mousewheel or the buttons on the left side of the toolbar. Once you have zoomed in, you can move your viewpoint using the arrow icons or dragging the mouse.

Comparing maps

To directly compare multiple columns in your dataset, you can create multiple views in the map and show them side-by-side. Using the buttons labeled "# of Maps" in the toolbar, you can compare two data columns side-by-side, or show one small map for each column. This "small multiples" mode is often an effective way to show regional changes over time or to correlate geographic trends.

When the map is set to show multiple views, it's important to consider the numeric or categorical scale used by each view. By default, each view has its own separate scale. If the columns shown by the views are comparable (e.g. each column shows the value from a single year), then the scales should be aligned. Aligning the scales will make sure that each view shows the same color for the same value.

If the scales aren't aligned, then the map can become confusing. In the example below, the views compare mobile phone users vs Internet users per 1,000 people in Europe. In the default view, your first impression might be that Internet users are only slightly less numerous than mobile phone users. However, by clicking the "Align Map Scales" box in the toolbar, we can ensure that each view uses the same colors to show the same values. This reveals that in fact there are far fewer Internet users than mobile phone users in most European countries.

Data requirements

The map uses a string column for region names, and any number of numerical or text columns for values. Region names can be long names (France, Brazil), standard abbreviations (FR, BR), or ISO codes (FRA, 76).

An example data set suitable for the world map is:

Dealing with mismatches

Unfortunately, region names are not standardized. Where one data set has "The Bahamas," another may say, "Bahamas, The" and a third may simply have "Bahamas." The Many Eyes map has a built in facility for handling this fact of life, but you may need to give it some guidance.

When you first create a map, you may see a dialog like the one below:

You can use this dialog to help the map understand how it should associate data with countries. The data value that the map doesn't understand is displayed in bold text. Below the data value is a dropdown box with a list of guesses for the standardized name of the region. At the top of the list will be the country that the map thinks is the most likely candidate. You can choose a country from the dropdown box and select "OK" to associate the data value with the selected country, "Ignore this data value" to omit the data from the map, or "Ignore all unknown data values" to dismiss the dialogue.