William Playfair
 
The base concept of using complex graphical representations for displaying data is not new.  Mapmakers, or cartographers, were probably the first data visualization practitioners.  The use of color, shapes, position, hue, fill patterns, shading, text,
charts, icons — anything that communicates information was used to layer data elements into two-dimensional images.  
Fundamentally, each element is based on solid mathematics.
 
The use of pie charts and line graphs dates back to 1801 in a book by William Playfair, The Statistical Breviary.  Playfair utilized pie charts, line graphs, colors, relative size, shape and textual information to depict the land mass of European empires after the 1801 Luneville Peace Treaty between France and Austria. These visual representations depicted the proportion of the land mass of each empire on the continents (pie charts), their relative population (graphs), their relative revenues (graphs), whether or not they are maritime powers (color), and the relative tax burden on their population (graphs).

Without requiring the details, one can immediately interpret many items. The relative size of the circles, the color, the relative size of the pie slices, and the relative lengths of the lines all allow one to quickly understand the relationships between the data.  In this case one would recognize the strongest military threats, the size of the empires, and the financial strength of the governments.

Charles Minard

In 1861, Charles Minard, a French civil engineer and a pioneer using graphics to present statistics, published this famous drawing describing Napoleon‘s 1812 march on Russia.

Six types of information are displayed on this 2-dimensional chart: geography, time, temperature, the course and direction of the army's movement, and the troop strength. The two bands (grey and black) represent the size of the force; one millimeter equates to 10,000 men for both bands. The width of the grey band shows the relative size of the outbound army; the black band represents retreating soldier counts over the same time frame. Troop counts are associated with specific battles, as well as the distance traveled toward Moscow from the Polish border.  Soldier count is therefore tied to events, time, distance and temperature (which is depicted in the third line at the bottom of the chart).

Clearly, one sees that many men died.  (Specifically, Napoleon‘s army left Poland with a force of 422,000; only 100,000
reached Moscow; and only 10,000 returned.)  With minimal effort, one can determine what the circumstances and
contributing factors were at each step of the way by examining the details.
 
On this single chart, not only are a myriad of facts shown, but also the relationships between the key influencing factors can be quickly grasped and analyzed.  This is the eloquence of data visualization.
 
The Playfair and Minard examples indicate the synthesis of complex data (probably hundreds of manual calculations) with a full understanding of the data and 20/20 hindsight. One would imagine the effort to create these charts took many months, and required not only statistical prowess, but artistic facility as well.