A Pie Graph Uses _________to Represent Information
A
pie chart
(or a
circle chart) is a round statistical graphic, which is divided into slices to illustrate numerical proportion. In a pie nautical chart, the arc length of each slice (and consequently its central angle and surface area) is proportional to the quantity information technology represents. While it is named for its resemblance to a pie which has been sliced, there are variations on the way it can be presented. The primeval known pie chart is by and large credited to William Playfair’southward
Statistical Breviary
of 1801.^{[one]}
^{[2]}
Pie charts are very widely used in the business earth and the mass media.^{[3]}
Nevertheless, they have been criticized,^{[4]}
and many experts recommend avoiding them,^{[5]}
^{[halfdozen]}
^{[7]}
^{[8]}
every bit research has shown information technology is hard to compare different sections of a given pie chart, or to compare data across different pie charts. Pie charts tin be replaced in about cases past other plots such as the bar chart, box plot, dot plot, etc.
History
[edit]
The earliest known pie chart is by and large credited to William Playfair’due south
Statistical Breviary
of 1801, in which ii such graphs are used.^{[1]}
^{[ii]}
^{[nine]}
Playfair presented an illustration, which independent a series of pie charts. I of those charts depicted the proportions of the Turkish Empire located in Asia, Europe and Africa before 1789. This invention was not widely used at first.^{[1]}
Playfair idea that pie charts were in need of a third dimension to add boosted information.^{[ten]}
Florence Nightingale may not have invented the pie nautical chart, but she adapted it to arrive more readable, which fostered its wide use, still today. Indeed, Nightingale reconfigured the pie chart making the length of the wedges variable instead of their width. The graph, so, resembled a cock’southward comb.^{[11]}
She was subsequently assumed to take created it due to the obscurity and lack of practicality of Playfair’s creation.^{[12]}
Nightingale’s polar area diagram,^{[13]}
^{
: 107
}
or occasionally the
Nightingale rose diagram, equivalent to a modern circular histogram, to illustrate seasonal sources of patient mortality in the war machine field hospital she managed, was published in Notes on Matters Affecting the Health, Efficiency, and Hospital Assistants of the British Army and sent to Queen Victoria in 1858. According to the historian Hugh Pocketsize, “she may take been the first to use [pie charts] for persuading people of the need for change.”^{[11]}
The French engineer Charles Joseph Minard also used pie charts, in 1858. A map of his from 1858 used pie charts to represent the cattle sent from all around France for consumption in Paris.
Early types of pie charts in the 19th century

Pie charts from William Playfair’south “Statistical Breviary”, 1801

One of the pie charts, 1801

Minard’s map, 1858
Variants and similar charts
[edit]
3D pie chart and perspective pie cake
[edit]
A 3d pie nautical chart, or perspective pie nautical chart, is used to give the chart a 3D look. Often used for aesthetic reasons, the third dimension does not improve the reading of the data; on the contrary, these plots are difficult to interpret because of the distorted effect of perspective associated with the tertiary dimension. The use of superfluous dimensions non used to display the data of interest is discouraged for charts in general, not only for pie charts.^{[seven]}
^{[14]}
Doughnut chart
[edit]
A doughnut nautical chart (also spelled donut) is a variant of the pie chart, with a blank center allowing for additional data near the data as a whole to exist included.
^{[fifteen]}
^{[16]}
Doughnut charts are similar to pie charts in that their aim is to illustrate proportions.^{[
commendation needed
]}
This type of circular graph tin support multiple statistics at one time and information technology provides a better data intensity ratio to standard pie charts.^{[16]}
It does non have to incorporate information in the center.
Exploded pie chart
[edit]
A chart with one or more sectors separated from the rest of the disk is known equally an
exploded pie chart. This result is used to either highlight a sector, or to highlight smaller segments of the chart with small proportions.
Polar area diagram
[edit]
The polar area diagram is similar to a usual pie chart, except sectors have equal angles and differ rather in how far each sector extends from the center of the circumvolve. The polar expanse diagram is used to plot cyclic phenomena (due east.g., counts of deaths past month). For example, if the counts of deaths in each month for a year are to be plotted then there will be 12 sectors (ane per month) all with the aforementioned angle of thirty degrees each. The radius of each sector would be proportional to the square root of the decease rate for the month, and then the surface area of a sector represents the rate of deaths in a month. If the decease rate in each month is subdivided past cause of death, it is possible to brand multiple comparisons on ane diagram, as is seen in the polar area diagram famously developed past Florence Nightingale.
The starting time known employ of polar expanse diagrams was by AndréMichel Guerry, which he called
courbes circulaires
(round curves), in an 1829 newspaper showing seasonal and daily variation in current of air management over the year and births and deaths by 60 minutes of the day.^{[17]}
Léon Lalanne later used a polar diagram to show the frequency of wind directions around compass points in 1843. The wind rose is still used by meteorologists. Nightingale published her rose diagram in 1858. Although the proper name “coxcomb” has come up to be associated with this blazon of diagram, Nightingale originally used the term to refer to the publication in which this diagram first appeared—an attendinggetting book of charts and tables—rather than to this specific type of diagram.^{[eighteen]}
Ring chart, sunburst chart, and multilevel pie chart
[edit]
A band nautical chart, as well known as a sunburst chart or a multilevel pie nautical chart, is used to visualize hierarchical data, depicted past concentric circles.^{[19]}
The circumvolve in the center represents the root node, with the hierarchy moving outward from the heart. A segment of the inner circle bears a hierarchical human relationship to those segments of the outer circle which lie inside the angular sweep of the parent segment.^{[20]}
Spie nautical chart
[edit]
A variant of the polar expanse chart is the spie nautical chart, designed by Dror Feitelson.^{[21]}
The pattern superimposes a normal pie chart with a modified polar area chart to allow the comparing of 2 sets of related data. The base pie chart represents the first data prepare in the usual way, with unlike slice sizes. The 2nd fix is represented past the superimposed polar area nautical chart, using the same angles as the base, and adjusting the radii to fit the data. For example, the base pie chart could testify the distribution of age and gender groups in a population, and the overlay their representation among road casualties. Age and gender groups that are specially susceptible to existence involved in accidents and so stand up out as slices that extend across the original pie chart.
Square chart / Waffle chart
[edit]
Square charts, also chosen waffle charts, are a class of pie charts that employ squares instead of circles to correspond percentages. Similar to basic round pie charts, square pie charts take each per centum out of a total 100%. They are often 10 past 10 grids, where each cell represents 1%. Despite the name, circles, pictograms (such equally of people), and other shapes may be used instead of squares. One major benefit to square charts is that smaller percentages, difficult to see on traditional pie charts, can be easily depicted.^{[22]}
Example
[edit]
The postobit example chart is based on preliminary results of the election for the European Parliament in 2004. The table lists the number of seats allocated to each party grouping, along with the derived percentage of the total that they each make upwardly. The values in the last cavalcade, the derived central angle of each sector, Is constitute by multiplying the per centum by 360°.
Group  Seats  Percent (%)  Key angle (°) 

EUL  39  5.3  19.ii 
PES  200  27.3  98.iv 
EFA  42  5.7  20.7 
EDD  15  2.0  vii.iv 
ELDR  67  nine.2  33.0 
EPP  276  37.seven  135.7 
UEN  27  3.7  xiii.3 
Other  66  nine.0  32.5 
Full  732  99.9*  360.two* 
*Because of rounding, these totals practise not add together up to 100 and 360.
The size of each central angle is proportional to the size of the corresponding quantity, here the number of seats. Since the sum of the central angles has to be 360°, the central angle for a quantity that is a fraction
Q
of the full is 360Q
degrees. In the example, the central bending for the largest grouping (European People’south Party (EPP)) is 135.seven° because 0.377 times 360, rounded to 1 decimal place, equals 135.7.
Use and effectiveness
[edit]
A flaw exhibited past pie charts is that they cannot show more than a few values without separating the visual encoding (the “slices”) from the data they represent (typically percentages). When slices go too small, pie charts have to rely on colors, textures or arrows and so the reader can understand them. This makes them unsuitable for use with larger amounts of data. Pie charts also take up a larger amount of space on the folio compared to the more flexible bar charts, which do non need to have divide legends, and can brandish other values such as averages or targets at the aforementioned fourth dimension.^{[7]}
Statisticians by and large regard pie charts as a poor method of displaying information, and they are uncommon in scientific literature. One reason is that it is more difficult for comparisons to be made between the size of items in a chart when surface area is used instead of length and when different items are shown every bit different shapes.^{[23]}
Further, in research performed at AT&T Bell Laboratories, it was shown that comparison past angle was less accurate than comparison by length. Most subjects have difficulty ordering the slices in the pie chart past size; when an equivalent bar chart is used the comparing is much easier.^{[24]}
Similarly, comparisons between data sets are easier using the bar chart. Even so, if the goal is to compare a given category (a slice of the pie) with the total (the whole pie) in a single nautical chart and the multiple is close to 25 or 50 pct, then a pie chart can oftentimes be more effective than a bar graph.^{[25]}
^{[26]}
In a pie nautical chart with many section, several values may be represented with the same or similar colors, making estimation difficult.
Several studies presented at the
European Visualization Briefing
analyzed the relative accuracy of several pie chart formats,^{[27]}
^{[28]}
^{[22]}
reaching the determination that pie charts and doughnut charts produce similar error levels when reading them, and square pie charts provide the most authentic reading.^{[29]}
References
[edit]

^
^{ a }
^{ b }
^{ c }
Spence (2005) 
^
^{ a }
^{ b }
Tufte, p. 44 
^
Cleveland, p. 262 
^
Wilkinson, p. 23. 
^
Tufte, p. 178. 
^
van Belle, p. 160–162. 
^
^{ a }
^{ b }
^{ c }
Stephen Few. “Save the Pies for Dessert”, August 2007, Retrieved 20100202 
^
Steve Fenton “Pie Charts Are Bad” 
^
“Milestones in the History of Thematic Cartography, Statistical Graphics, and Data Visualization”.
world wide web.datavis.ca.

^
Palsky, p. 144–145 
^
^{ a }
^{ b }
Greenbaum, Hilary; Rubinstein, Dana (20 April 2012). “Who Made That Pie Chart?”.
The New York Times.

^
Dave article on this information on QI 
^
Cohen, I. Bernard (March 1984). “Florence Nightingale”.
Scientific American.
250
(3): 128–137. Bibcode:1984SciAm.250c.128C. doi:x.1038/scientificamerican0384128. PMID 6367033.
(alternative pagination depending on country of sale: 98–107, bibliography on p. 114) online article – see documents link at left 
^
Good and Hardin, chapter 8. 
^
Harris, Robert L. (1999).
Information graphics : a comprehensive illustrated reference
([Nachdr.] ed.). Oxford: Oxford Academy Printing. p. 143. ISBN9780195135329.

^
^{ a }
^{ b }
Information Design by Juergen KaiUwe Brock on iBooks.
iBooks
. Retrieved
201706ten
.

^
Friendly, p. 509 
^
“Florence Nightingale’s Statistical Diagrams”. Retrieved
20101122
.

^
“Multilevel Pie Charts”.
www.neoformix.com.

^
Webber Richard, Herbert Ric, Jiangbc Wel. “Infinitefilling Techniques in Visualizing Output from Computer Based Economical Models” 
^
“Feitelson, Dror (2003) Comparing Partitions With Spie Charts”
(PDF). 2003. Retrieved
20100831
.

^
^{ a }
^{ b }
Kosara, Robert; Skau, Drew (2016). “Judgment Error in Pie Nautical chart Variations”.
EuroVis.

^
Krygier, John (28 Baronial 2007). “Perceptual Scaling of Map Symbols”.
makingmaps.internet
. Retrieved
3 May
2015.

^
Cleveland, p. 86–87 
^
Simkin, D., & Hastie, R. (1987). An InformationProcessing Analysis of Graph Perception. Journal of the American Statistical Association, 82(398), 454. doi:10.2307/2289447.
Kosara, Robert (13 Apr 2011). “In Defense of Pie Charts”. Retrieved
April 13,
2011.

^
Spence, Ian; Lewandowsky, Stephan (1 Jan 1991). “Displaying proportions and percentages”.
Practical Cognitive Psychology.
5
(1): 61–77. doi:10.1002/acp.2350050106.

^
“An Illustrated Tour of the Pie Chart Study Results”.
eagereyes. 20160628. Retrieved
20161128
.

^
Skau, Drew; Kosara, Robert (2016). “Arcs, Angles, or Areas: Individual Data Encodings in Pie and Donut Charts”.
EuroVis.

^
“A Reanalysis of A Report Wellnigh (Foursquare) Pie Charts from 2009”.
eagereyes. 20160711. Retrieved
20161128
.
Farther reading
[edit]

Cleveland, William S. (1985).
The Elements of Graphing Data. Pacific Grove, CA: Wadsworth & Advanced Volume Program. ISBN0534037305.
 Friendly, Michael. “The Golden Historic period of Statistical Graphics,”
Statistical Science,
Book 23, Number 4 (2008), 502535  Good, Phillip I. and Hardin, James Due west.
Common Errors in Statistics (and How to Avoid Them). Wiley. 2003. ISBN 0471460680.  Guerry, A.Grand. (1829). Tableau des variations météorologique comparées aux phénomènes physiologiques, d’aprés les observations faites à fifty’obervatoire imperial, et les recherches statistique les plus récentes.
Annales d’Hygiène Publique et de Médecine Légale, 1 :228. 
Harris, Robert L. (1999).
Information Graphics: A comprehensive Illustrated Reference. Oxford University Press. ISBN0nineteen513532six.
 Lima, Manuel. “Why humans dearest pie charts: an historical and evolutionary perspective,”
Noteworthy, July 23, 2018  Palsky Gilles.
Des chiffres et des cartes: la cartographie quantitative au XIXè siècle. Paris: Comité des travaux historiques et scientifiques, 1996. ISBN 273550336four.  Playfair, William,
Commercial and Political Atlas and Statistical Breviary, Cambridge Academy Printing (2005) ISBN 0521855543.  Spence, Ian. No Humble Pie: The Origins and Usage of a statistical Chart.
Journal of Educational and Behavioral Statistics. Wintertime 2005, 30 (iv), 353–368.  Tufte, Edward.
The Visual Brandish of Quantitative Information. Graphics Printing, 2001. ISBN 096139214ii.  Van Belle, Gerald.
Statistical Rules of Pollex. Wiley, 2002. ISBN 047140227iii.  Wilkinson, Leland.
The Grammar of Graphics, 2nd edition. Springer, 2005. ISBN 0387245448.
External links
[edit]
Wikimedia Commons has media related to
Pie charts.
A Pie Graph Uses _________to Represent Information
Source: https://en.wikipedia.org/wiki/Pie_chart