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A pie chart is a graphical representation of data in the shape of a circular chart or pie, with the slices indicating the magnitude of the data. To depict data in the shape of a pie chart, a list of numerical variables as well as category categories is required. In a pie chart, the arc length of each slice, and hence the area and center angle it forms, is proportionate to the quantity it depicts.
A pie chart (sometimes known as a circle chart) is a circular statistical visual that is divided into slices to show numerical proportion. The arc length of each slice in a pie chart (and hence its center angle and area) is proportionate to the quantity it depicts. While it gets its name from its similarity to a sliced pie, there are other ways to serve it. The first known pie chart is attributed to William Playfair’s Statistical Breviary of 1801.
In the corporate sector and the media, pie charts are quite popular. They have, however, been criticized, and many experts advise against using them since research has shown that it is difficult to compare various areas of a similar pie chart, or data across numerous pie charts. In most circumstances, pie charts may be substituted with alternative plots such as the bar chart, box plot, dot plot, and so on.
There are 3 parts of a pie chart: crust, filling and topping.
Conducting exploratory research seems tricky but an effective guide can help.
The first known pie chart is widely attributed to William Playfair’s Statistical Breviary of 1801, which has two similar diagrams. Playfair displayed a graphic that included a succession of pie charts. Before 1789, one of the charts illustrated the proportions of the Turkish Empire in Asia, Europe, and Africa. Initially, this innovation was not extensively employed.
Playfair believed that pie charts needed a third dimension to give more information.
Florence Nightingale did not originate the pie chart, but she did improve on it to make it more readable, which led to its widespread use even now. Indeed, Nightingale rearranged the pie chart such that the length of the wedges varied rather than their width. As a result, the graph resembled a cock’s comb. Due to the obscurity and lack of practicality of Playfair’s idea, she was subsequently considered to have produced it. To illustrate seasonal sources of patient mortality in the military field hospital she managed, Nightingale used a polar area diagram, or occasionally a Nightingale rose diagram, equivalent to a modern circular histogram, which was published in Notes on Matters Affecting the Health, Efficiency, and Hospital Administration of the British Army and sent to Queen Victoria in 1858.Hugh Small, a historian, believes that “she may have been the first to utilize [pie charts] for persuading others of the necessity for change.”
In 1858, the French engineer Charles Joseph Minard employed pie charts as well. A map of his from 1858 depicted the cattle shipped from all around France for consumption in Paris using pie charts.
Step 1: Enter all of the data into a table and sum all of the values.
Step 2: To determine the percentage values, divide each number by the total and multiply by 100.
Mango = (45/150) × 100 = 30%
Orange = (30/150) × 100 = 20%
Plum = (15/150) × 100 = 10%
Pineapple = (30/150) × 100 = 20%
Melon = (30/150) × 100 = 20%
Step 3: To calculate the number of degrees required for each pie sector, we take a whole circle of 360° and use the formula: 360° (Frequency/Total Frequency)
(45/150) X 360
(30/150) X 360
(15/150) X 360
(30/150) X 360
(30/150) X 360
Step 4: Once all of the degrees for making a pie chart have been computed, use a protractor to create a circle (pie chart) using the calculated measurements.
Include Annotations: Outside of minor fractions like 1/2 (50 percent), 1/3 (33 percent), and 1/4, it is really exceedingly difficult to determine exact proportions from pie charts (25 percent). Furthermore, if the slice values are intended to represent quantities rather than proportions, pie charts often lack the tick marks that allow for straightforward estimate of values from slice sizes. For these reasons, annotations are a regular feature of pie charts.
Consider The Order Of Slices: A solid slice order can help a reader comprehend what the story is saying much more easily. When there are categories with relatively comparable values, a usual ordering is from the largest slice to the smallest slice, which is highly beneficial. If the category levels have a natural ordering, plotting slices in that order is typically preferable.
When deciding on a starting point, it’s best to plot slices in a cardinally-oriented direction. Typically, visualization tools will begin on the right or on the top. While beginning from the right has a mathematical grounding in terms of angle measurement norms, starting from the top seems more logical since it corresponds to how we read from top to bottom and how we think about angles.
Limit The Number Of Pie Slices: Pie charts with several slices might be difficult to read. It might be difficult to notice the smallest slices, and it can also be difficult to select enough colors to distinguish all of the slices. Recommendations vary, but if you have more than five categories, you should consider utilizing a different chart style. Another alternative is to combine little slices into a single ‘other’ slice that is colored in a neutral grey.
Avoid Distorting Effects: o read a pie chart correctly, the areas, arc lengths, and angles of the slices must all lead to an accurate depiction of the data. Avoiding 3-D effects is vital for any plot, but it is especially critical for pie charts. Squashing or expanding the circle, or adding extra depth, can easily alter the size of each slice in relation to the total.
Another source of distortion is the ‘exploded’ pie chart, in which slices are dragged out from the center for emphasis. This emphasis comes at a cost, since the gaps can make determining the part-to-whole comparison more difficult.
2D pie chart: A 2D pie chart displays the size of the items in a data series in relation to the total number of items in the series. A pie chart always displays a single data series and can be used to determine which item or items in the series is (are) the most significant.
3D Pie Chart And Perspective Pie Cake: A 3d pie chart, also known as a perspective pie chart, is used to give the chart a 3D appearance. The third dimension, which is frequently utilized for aesthetic purposes, does not help data reading; on the contrary, these plots are difficult to comprehend due to the distorted impact of perspective associated with the third dimension. The inclusion of extra dimensions that are not employed to illustrate the data of interest is discouraged for all charts, not only pie charts.
Doughnut Chart: A doughnut chart (sometimes written donut) is a pie chart variation with a blank center that allows for more information about the data as a whole to be included. Doughnut charts are similar to pie charts in that they are used to show proportions. [Citation required] This style of circular graph may display numerous statistics at the same time and has a higher data intensity ratio than traditional pie charts. It is not required to have information in the middle.
Exploded Pie Chart: An exploding pie chart is one that has one or more sectors isolated from the rest of the disc. This effect can be used to emphasize a sector or smaller pieces of the chart with modest proportions.
Polar Area Diagram: The polar area diagram is similar to a traditional pie chart, except that the sectors have equal angles and differ primarily in how far each sector extends from the circle’s center. Cycles are depicted using the polar area diagram (e.g., counts of deaths by month). For example, if the monthly death counts for a year are plotted, there will be 12 sectors (one for each month), all with the same angle of 30 degrees. The radius of each sector would be proportionate to the square root of the month’s death count, thus the area of a sector would indicate the number of deaths.If the mortality count in each month is segmented by cause of death, many comparisons may be made on a single figure, as shown in Florence Nightingale’s renowned polar area diagram.
André-Michel Guerry used polar area diagrams, which he named courbes circulaires (circular curves), in an 1829 work to demonstrate seasonal and daily fluctuation in wind direction across the year, as well as births and deaths by hour of the day. In 1843, Léon Lalanne created a polar diagram to depict the frequency of wind directions around compass points. Meteorologists still utilise the wind rose. In 1858, Nightingale released her rose diagram.Although the term “coxcomb” has become synonymous with this sort of diagram, Nightingale initially intended it to refer to the publication in which this design first appeared—an attention-grabbing book of charts and tables—rather than to this particular form of diagram.
Ring Chart: A ring chart, also known as a sunburst chart or a multilayer pie chart, is used to show hierarchical data as concentric rings. The root node is represented by the circle in the middle, with the hierarchy expanding outward from it. A segment of the inner circle has a hierarchical connection to the outer circle segments that are inside the angular sweep of the parent segment.
Spie Chart: The spie chart, invented by Dror Feitelson, is a variation on the polar area chart. To allow for the comparison of two sets of related data, the design superimposes a standard pie chart with a modified polar area chart. The first data set is represented by the basic pie chart in the normal fashion, with varying slice sizes. The second set is represented by the overlay polar area chart, which uses the same angles as the base but with the radii adjusted to match the data. For example, the base pie chart may depict the distribution of age and gender groupings in a population, with their representation among road casualties overlayed.Age and gender groupings that are more likely to be engaged in accidents stand out as slices that expand beyond the initial pie chart.
Square Chart: Square charts, sometimes known as waffle charts, are a type of pie chart in which squares instead of circles are used to depict percentages. Square pie charts, like simple circular pie charts, take each percentage out of a total of 100 percent.They are usually 10 by 10 grids, with each cell representing 1%. Despite the name, circles, pictograms (such as people’s faces), and other forms may be used in place of squares. One significant advantage of square charts is that lower percentages, which are difficult to discern on typical pie charts, may be easily displayed.
Bar Of Pie: Another easy technique to indicate additional categories on a pie chart while avoiding congestion on the pie chart is to use a bar of pie. Unlike the pie of pie, the extension developed from the current pie chart is a bar graph, despite the fact that they perform identical functions.
It takes values from the primary pie chart and merges them into stacked bars.
Pie Of Pie: Pie of pie is a simple approach to express more categories on a pie chart without creating a cluttered, difficult-to-read graph. A pie of pie, as the name indicates, is a pie chart derived from an existing pie chart.
It takes certain values from the primary pie and combines them to create a new pie.
Fitting A Pie To Incompatible Data: One of the most common pie chart blunders is fitting it to data that does not reflect a parts-to-whole comparison. This is particularly common when the data to be plotted are percentages or proportions but do not form a full whole. The sample below demonstrates how frequently participants questioned used each of four programs, but because many users used numerous apps, the numbers add up to far more than 100%.
Another problematic example is when the data for each group are a summary statistic rather than a total. The graph below was created using the average transaction amount for various transaction categories. However, because it disregards how frequently each transaction type was utilized, it distorts the amount of income generated by each kind. While checks have the highest average, they may also be used seldom. A bar chart is an ideal chart style to use in both scenarios.
Using Pie To Compare Groups: If you wish to compare groupings rather than compare each group to the entire, you need use a different chart type. Even when sorted by size, it might be difficult to identify how different two slices are, especially as they move further from the start / end point. In the example below, you could think that the second slice is larger than the third because of the sequence, however the matching bar chart reveals the reverse. The essential thing to take away from the pie chart is that both slices have roughly the same percentage of the total.
Comparing Across Multiple Pie Charts: There may be times when you wish to compare numerous pies against one another, such as when examining user demographic dispersion across time. However, this has the same problem as the preceding part in that you want to compare groups to one another. Worse, because it’s a comparison of pies, you can’t rely on the arrangement of slices as readily. When this type of group-to-group comparison is sought, it is frequently preferable to express the data using a different plot, such as a stacked bar chart, grouped bar chart, or line chart. Pie charts, like genuine pies, are best taken one at a time.
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