Chart

"Plotting" redirects here.
 An example of a pie chart, showing the composition of the 38th parliament of Canada.
A chart or graph is a type of information graphic or graphic organizer that represents tabular numeric data or functions. Charts often make it easier to understand and visualize large quantities of data and relationships between different parts of the data. Consequently, charts can usually be read more quickly than the raw data they come from. They are used in a wide variety of fields, and can be created by hand (often on graph paper) or by computer using a charting application.
Certain types of charts are more useful for presenting a given data set than others. For example, data that provide percentages in different groups (such as "satisfied, not satisfied, unsure") may be displayed in a pie chart or horizontal bar chart. On the other hand, data that indicate how certain numbers change over a period of time (such as "annual revenue from 1990 to 2000") might be best shown as a line chart.

Contents

1 Comparing charts with tables
2 Common charts

2.1 Example of a histogram


3 Less-common charts
4 Field-specific charts
5 Well-known (named) charts
6 See also
7 Notes
8 References
9 External links
10 Credits



The term chart is also used when referring to a map created for navigation by air or sea. This article gives an overview of charts in the sense of graphical representations.

 A line chart showing the speed of a body versus time.
Comparing charts with tables
Data gathered by an observer or researcher may be presented in the form of a table or a chart (or both). Each form is useful in its own way. A table shows the precise values of data points, but from a table it is often difficult to recognize patterns or trends underlying those values. A chart, on the other hand, quickly reveals the underlying patterns. A chart is often constructed using data organized in tabular form.

Common charts
Scatter plot, scatter graph, or scatter diagram: It is a type of display that uses Cartesian coordinates to show the relation between two quantitative variables. The data are displayed as a collection of points. For each point, the value of one variable determines the position on the horizontal axis, and the value of the other variable determines the position on the vertical axis.[1]
Line chart: A line chart is a scatter plot of ordered observations, where the observations (or points) are connected following their order. The line in a line chart depicts the best-fit trend of the scattered data.
Bar graph or bar chart: A bar graph uses rectangular bars to show frequencies or values for different categories. The bars can be horizontally or vertically oriented, and the lengths of the bars are proportional to the values they represent. Bar charts are used for comparing two or more values.
Histogram: A histogram is a graphical display showing the frequencies (or proportions) of cases that fall into each of several categories. Like a bar chart, a histogram uses rectangular bars. A histogram, however, differs from a bar chart in that the area (not the height) of the bar denotes the value, a crucial distinction when the categories are not of uniform width (Lancaster, 1974). The categories are usually specified as non-overlapping intervals of some variable.
Pie chart or circle graph: A pie chart is a circular chart divided into sectors, illustrating relative magnitudes, frequencies, or percentages. This type of chart is named for its resemblance to a pie that has been sliced. In a pie chart, the arc length of each sector (and consequently its central angle and area) is proportional to the quantity it represents.
Example of a histogram
Consider data collected by the U.S. Census Bureau on the time it takes for commuters to travel to work (2000 census, Table 5).[2] The census found that there were about 124 million people who work outside of their homes.[3]

 Histogram showing the time it took for U.S. commuters to travel to work, as of the year 2000 (US 2000 census). Area under the curve equals the total number of cases (124 million). This diagram uses Q/width from the table.

Data by absolute numbers


Interval
Width
Quantity
Quantity/width


0
5
4180
836


5
5
13687
2737


10
5
18618
3723


15
5
19634
3926


20
5
17981
3596


25
5
7190
1438


30
5
16369
3273


35
5
3212
642


40
5
4122
824


45
15
9200
613


60
30
6461
215


90
60
3435
57

This histogram shows the number of cases per unit interval so that the height of each bar is equal to the proportion of total people in the survey who fall into that category. The sum of areas under the bars represents the total number of people (124 million) who said they travel to work.

Less-common charts
A box plot (or box-and-whiskers plot) shows information about the distribution (such as minimum, maximum, mean average) along a single axis.
A bubble chart is a two-dimensional scatter plot in which a third variable is represented by the size of the points.
A Tonnetz (doughnut chart), a conceptual lattice diagram invented by Leonhard Euler in 1739, shows a two-dimensional tonal pitch space created by the network of relationships between musical pitches in just intonation.
A Polar area diagram (developed by Florence Nightingale) is an enhanced form of pie chart.
A radar chart (or "spider chart") is a two-dimensional chart of three or more quantitative variables represented on axes starting from the same point.
A ternary plot is a barycentric plot on three variables that add up to a constant.
A waterfall chart, also known as a "Walk" chart, is a special type of floating-column chart.
Field-specific charts
Some types of charts have specific uses in certain fields.

Stock market prices are often depicted with a open-high-low-close chart with a traditional bar chart of volume at the bottom.
Candlestick charts are another type of bar chart used to describe price movements of an equity over time.
A Kagi chart is a time-independent stock tracking chart that attempts to minimise noise.
Alternatively, where less detail is required and chart size is paramount, a Sparkline may be used.
Interest rates, temperatures, etc., at the close of the period are plotted with a line chart.
Scatter charts plot readings of two variables simultaneously as dots between the X-axis and the Y-axis, such as for price and earnings.
Marketers use a lift chart to highlight performance.
Project planners use a Gantt chart to show the timing of tasks as they occur over time.
A phase diagram denotes the equilibrium conditions between thermodynamically-distinct phases.
Well-known (named) charts
Some specific charts have become well known by effectively explaining a phenomenon or idea.

An Allele chart is a chart originating from the study of genetics to show the interaction of two data points in a grid.
Bode plots are used in Control Theory.
The Dalitz plot is a scatterplot which represents the relative frequency of manners in which the products of certain three-body decays may move apart.
A Gantt chart helps in scheduling complex projects.
A Lineweaver-Burk plot is used to represent and determine enzyme kinetics.
Nichols plots are used in Control Theory.
The Nolan chart is a libertarian political chart.
Nyquist plots are used in Control Theory.
A PERT chart is often used in project management.
The Pournelle chart is a political chart to categorize state and rational ideologies.
The Smith chart serves in radio electronics.
See also
Flowchart
Information graphics
Notes

↑ Jessica M. Utts, Seeing Through Statistics, 3rd ed. (Belmont, CA: Thomson, Brooks/Cole, 2005, ISBN 0534394027), 166-167.

↑  US Census Brief

↑ This numerical rounding is commonly done when collecting data from people.


ReferencesISBN links support NWE through referral fees
Bluttman, Ken. 2005. Excel Charts for Dummies.—For dummies. Hoboken, NJ: Wiley. ISBN 978-0764584732
Cleveland, William S. 1985. The Elements of Graphing Data. Monterey, CA: Wadsworth Advanced Books and Software. ISBN 0534037305
Jones, Gerald E. 2007. How to Lie with Charts. Santa Monica, CA: LaPuerta. ISBN 978-1419651434
Lancaster, H.O. 1974. An Introduction to Medical Statistics. Wiley Series in Probability and Mathematical Statistics. New York: Wiley. ISBN 0471512508
Tufte, Edward R. 2001. The Visual Display of Quantitative Information. Cheshire, CT: Graphics Press. ISBN 0961392142
Van Belle, Gerald. 2002. Statistical Rules of Thumb. Wiley Series in Probability and Statistics. New York: Wiley-Interscience. ISBN 0471402273
Wilkinson, Leland. 2005. The Grammar of Graphics. Statistics and Computing. New York: Springer. ISBN 0387245448
Zelazny, Gene. 2007. The Say It with Charts Complete Toolkit. New York: McGraw-Hill. ISBN 978-0071474702.
External links
All links retrieved February 7, 2017.

Create A Graph NCES Kids' Zone. (Free online graph creation tool.)
BARCHART Generator (Free online bar chart generator.)
Understanding Histograms The Luminous Landscape. (For digital photography.)
Histograms: Construction, Analysis and Understanding

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