To create a map, one has to style the GIS data and present it in a form that is visually informative. There are a large number of options available in QGIS to apply different types of symbology to the underlying data. In this tutorial, we will explore some basics of styling. The data we will use is from Center for Sustainability and the Global Environment (SAGE) at the University of Wisconsin-Madison. To keep things simple, let’s use the Quantile method. Click Classify at the bottom and you will see 3 classes show up with their corresponding values. Click OK. To create a map, one has to style the GIS data and present it in a form that is visually informative. There are a large number of options available in QGIS to apply different types of symbology to the underlying data. In this tutorial, we will explore some basics of styling. that would represent the map we are trying to create. Since we want to create a layer represting life expectancy, i.e. the average age till a person lives in a country, the field tab of the Properties dialog. Clicking on the drop-down button inthe Style dialiog, you will see there are five options available – . This option allows you to choose a single style that will be applied to all the features in the layer. Since this is a polygon dataset, you have two basic choices. You can You will see that this Single Symbol style isn’t useful in communicating the life expectancy data we are trying to map. Let us explore another styling option. Right-click the layer again and choose tab. Categorized means the features in the layer will be shown in different shades of a color based on unique values in an attribute field. Choose You will see different countries appearing in shades of blue. Lighter shades meaning lower life expectancy and darker shades meaning higher life expectancy. This representation of the data is more useful and clearly show how life expectancy in developed countries vs. developing countries. This would be the type of style we set out to create. and choose a different style for each of the classes. We can think of classifying our life expectancy data into 3 classes, Equal Interval: As the name suggests, this method will will create classes which are at the same size. If our data ranges from 0-100 and we want 10 classes, this method would create a class from 0-10, 10-20, 20-30 and so on , keeping each class the same size of 10 units. Quantile – This method will decide the classes such that number of values in each class are the same. If there are 100 values and we want 4 classes, quantile method will decide the classes such that each class will have 25 values. Natural Breaks (Jenks) – This algorithm tries to find natural groupings of data to create classes. The resulting classes will be such that there will be maximum variance between individual classes and least variance within each class. Standard Deviation – This method will calculate the mean of the data, and create classes based on standard deviation from the mean. style, it must be a numeric field. Integer and Real values are fine, but if the attribute field type is String, it cannot be used with this styling option. . There are some more styling options available. You can click on the Symbol for each of the classes and choose a different style. We will choose Red, Yellow and Green fill colors to indicate low, medium and high life expectancy. This style definitely conveys a lot more useful map than the previous two attempts. There are clearly marked class names and colors to represent our interpretation of the life expectancy values. Source.