# 统计代写|数据可视化代写Data visualization代考|STAT1100

## 统计代写|数据可视化代写Data visualization代考|Three-Dimensional Plots

Contour maps and contour plots were certainly useful, but they were still images on a two-dimensional surface, using shading or level curves to show a third dimension. There is a huge difference between trying to navigate a driving route or a hike from a 2D map that shows elevation with isolines versus a 3D relief map that shows elevation in context, using perspective, realistic lighting (“raytracing”), color (“terrain colors”), texture mapping, and other techniques to generate beautiful and more useful 3D topographic maps. ${ }^{10}$

The technique of rendering 3D views in depth and perspective on a flat surface was known to artists for centuries, but early landscapes lacked realism. The first exemplar to get perspective approximately right was the painting View of the Arno Valley by Leonardo da Vinci in 1473, his first known drawing; but that is just an artist’s view. For data graphics, the precise technical details of drawing a 3D surface of a response variable $z$ over a plane defined by $(x, y)$ coordinates did not develop until the late 1800 s. By 1869, in the course of work on thermodynamics, the German physicist Gustav Zeuner [1828-1907] worked out the mathematics of what has come to be called the axonometric projection: a way of drawing a 3D coordinate system so that the coordinate axes looked to be at right angles, and parallel slices or curves had the proper appearance. Zeuner took Descartes to 3D.

An example is shown in Figure 8.6. The coordinate axes, $X, Y, Z$ are shown with the origin in the back. Two parallel curves are drawn, and the goal of this diagram is to explain how the rectangular region can be seen in terms of its projected shadows (shaded) as rectangles on the bottom and left planes.
The first known use of a 3D data graphic using these ideas was designed by Luigi Perozzo [1856-1916], an Italian mathematician, statistician, and,ultimately, a hero of demography, largely for this contribution to the study of the distribution of age over time.

A graphic innovation on this topic appeared in the U.S. Census atlas of 1870, where Francis Walker pioneered the idea of an “age-sex pyramid” showing the age distribution of the population by sex. It was called a pyramid because it compared the populations of men and women in back-to-back histograms by age, in a way that resembled a pyramid. In a number of plates, these data were broken down by state and other factors, in such a way that insurance agencies could begin to set age-, sex-, and region-specific rates for an annuity or life insurance policy. To demographers, this method gave a way to characterize fertility, life expectancy, and other questions regarding population variation. But these were still 2D graphs.

## 统计代写|数据可视化代写Data visualization代考|Contour Maps

Maps start with a two-dimensional surface defined by latitude and longitude. After geographic features such as rivers, cities, and towns had been inscribed, it was natural for cartographers to want to show features of elevation, and landforms such as mountains and plateaus, in what came to be called topographic maps. This idea was a natural initial impetus for 3D thinking and visual depiction.

The first large-scale topographic map of an entire country was the Carte géométrique de la France, by the French astronomer and surveyor CésarFrançis Cassini de Thury [1714-1784], ${ }^2$ completed in 1789. But well before these precise determinations of altitude were made, map makers began to try to show topographical features using contour lines of equal elevation on their maps. These were useful for finding the way through a mountain range as well as for military defense.

Beyond wayfinding and route navigation, thematic maps use the features of geography to show something more: how some quantity of interest varies from place to place. Figure $3.3$ by Balbi and Guerry is a nice example of the use of shaded (choropleth) maps of France to display the geographic distribution of crimes and compare this with the distribution of literacy. But this and similar maps treat geographic regions as discrete, and simply shade the entire arca in rclation to a variable of interest.

The language and symbolism of maps expanded to display more abstract quantitative phenomena that varied systematically over geographical space. This was technically a small step from topographic maps that showed elevation of terrain using either color shading or iso-curves (lines of equal magnitude), but the impact was profound in scientific investigation. It was essentially what Galton had done in mapping the contours of equal barometric pressure across Europe (see Plate 12).

This idea, of drawing level curves or contours on a map to show a data variable, began much earlier. Perhaps the first complete example ${ }^3$ is the 1701 map by Edmund Halley, showing lines of equal magnetic declination (isogons) for the world, shown here in Figure 8.2. It was titled, in a style that tried to tell the whole story on the frontispiece, The Description and Uses of a New, and Correct Sea-Chart of the Whole World, Shewing Variations of the Compass.

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## 统计代写|数据可视化代写数据可视化代考|等高线地图

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