Types of graphs

A chart is a visual representation of data, in which the data are represented by symbols such as bars in a bar chart or lines in a line chart.[1] A chart can represent tabular numeric data, functions or some kinds of qualitative structures.
Four of the most common charts are:
A histogram typically shows the quantity of points that fall within various numeric ranges (or bins).
A bar chart uses bars to show frequencies or values for different categories.


A pie chart shows percentage values as a slice of a pie.



A line chart is a two-dimensional scatterplot of ordered observations where the observations are connected following their order.


A pie chart (or a circle graph) is a circular chart divided into sectors, illustrating relative magnitudes or frequencies. In a pie chart, the arc length of each sector (and consequently its central angle and area), is proportional to the quantity it represents. Together, the sectors create a full disk. It is named for its resemblance to a pie which has been sliced.






The pie chart is perhaps the most ubiquitous statistical chart in the business world and the mass media.[1] However, it has been criticized,[2] and some recommend avoiding it[3][4], pointing out in particular that it is difficult to compare different sections of a given pie chart, or to compare data across different pie charts. Pie charts can be an effective way of displaying information in some cases, in particular if the intent is to compare the size of a slice with the whole pie, rather than comparing the slices among them.[5] Pie charts work particularly well when the slices represent 25 to 50% of the data,[6] but in general, other plots such as the bar chart or the dot plot, or non-graphical methods such as tables, may be more adapted for representing certain information.
Statisticians tend to regard pie charts as a poor method of displaying information. While pie charts are common in business and journalism, they are uncommon in scientific literature. One reason for this is that it is more difficult for comparisons to be made between the size of items in a chart when area is used instead of length

In statistics, a histogram is a graphical display of tabulated frequencies, shown as bars. It shows what proportion of cases fall into each of several categories: it is a form of data binning. The categories are usually specified as non-overlapping intervals of some variable. The categories (bars) must be adjacent. The intervals (or bands, or bins) are generally of the same size.[1]
Histograms are used to plot density of data, and often for density estimation: estimating the probability density function of the underlying variable. The total area of a histogram used for probability density is always normalized to 1. If the length of the intervals on the x-axis are all 1, then a histogram is identical to a relative frequency plot. bar chart or bar graph is a chart with rectangular bars with lengths proportional to the values that they represent. Bar charts are used for comparing two or more values that were taken over time or on different conditions, usually on small data sets. The bars can be horizontally lines or it can also be used to mass a point of view. A bar graph shows you the frequency of each element in a set of data. The height of each bar represents how many of that data element there are. Here's an example. Suppose we bought a small box of Smarties and counted how many of each colour was in the box. We might get results as shown in the table below left. We could then record the frequency of each colour in a bar graph, as shown below right.


You'll notice that we drew this graph with the bars separated by spaces. We didn't have to do this ... we could have had the bars touching, and this still would have been a bar graph.Here's another example of a bar graph, counting numerical values instead of colours. Suppose we surveyed ten elementary students and asked them to tell us their weekly allowance. We might get data like in the table at the right. Below we've organized the data into a frequency table, and then displayed it in a bar graph.
This time we made the bars touch. We still have a bar graph. Bar graphs are used to represent the frequency of discrete items. They can be things, like colours, for which there is no particular order. Or they can be numbers, like allowance amounts, where they can be put into order if you choose to.But (this is the important part) the items are not grouped, and they are not continuous. We'll show you what we meant by that last sentence, in the example below, where we show you a set of data that we will group, and display in a continuous manner on a histogram. Suppose we were surveying the masses of fish in a lake, and we caught and weighed twenty-nine fish. We recorded their masses (in kilograms). Below is the data we might have collected.


If you examine the data above closely, you'll see that there are a lot of mostly different numbers. It wouldn't make much sense to make a bar graph showing the frequency of each individual mass, since most of the bars would just be one ot two units high, and there would be a lot of bars. Instead we're going to group the data.Grouping means to count how many masses there are in different weight categories, or classes. For example, how many fish had a mass between 10 and 12 kilograms? The answer is three. They were 10, 11.4 and 11.8 kg.Note that we don't count 12 in this class of fish. 'Between 10 & 12 kilograms' means 'everything from 10 up to 12, but don't count 12' Below is our grouped frequency table. We've shown (on the left) which masses went into the count for each class. We also indicated the upper bound of each class in red, to remind you that this value isn't counted in that class.