# Types of Graphs

## Different Types of Graphs

Graphs are a common way to visually represent data relationships. A graph aims to present data that are too numerous or complicated to be adequately represented in text and a limited amount of space. However, graphs should not be used for small quantities of data that could be expressed in a single sentence. Reiterate the data in the text as well, as this defeats the purpose of using a graph. A graph can be used if the data shows clear patterns or indicates relationships between variables. A graph is not the best figure to use if the data does not indicate any clear trend in the evidence.

Despite the fact that a graph can be produced using a variety of computer programmes, we must stick to certain basic principles. A graph must be transparent and readable as a minimum requirement. This is influenced not only by the font size and symbols but also by the graph's form. For each graph, it's important to have a simple and descriptive legend.

Graphs Can be Divided into Several Sections Depending on Their Format:

• A Figure Number,

• A Caption (not a Title),

• A Data Field,

• Axes and Scales,

• Symbols,

• Legends, And

• A Credit or Source Line.

A caption, axes and sizes, symbols, and a data field should always be included in graphs. Plotting symbols must be distinct, legible, and provide sufficient contrast between the foreground and background figures. The comparison between open and closed circles is superior to the combination of open circles and open squares. Each legend, like the title of the paper, should express as much information as possible about what the graph tells the reader, but not a description or explanation of the findings or experimental data. Restating the axis names, such as "temperature vs. time," is not a good idea. It's critical to choose the right graph type for the data you'll be presenting. Use line diagrams or scattergrams if both the independent and dependent variables are numeric; use bar graphs if only the dependent variable is numeric; and use bar graphs or pie charts for proportions.

### Different Types of Graphs and Different Types of Charts

In data analysis, there are several different types of graphs and charts. However, in this article, we'll go through types of graphs and charts:

### Bar Chart/Graph

A bar chart is a graph in which the data points in a collection of data are depicted by spaced rectangular bars. Discrete and categorical data are normally plotted with it. The chart's horizontal axis represents categorical data, while the vertical axis represents individual data. While rectangular bars in a bar chart are typically arranged vertically, they may also be arranged horizontally.

#### Types of Bar Graph

1. Grouped Bar Chart

When there are subgroups in a dataset that needs to be visualised on a graph, grouped bar charts are used. Each subgroup is normally distinguished from the others by using different colours to shade them.

1. Stacked Bar Chart

In a dataset, stacked bar graphs are often used to display subgroups. The rectangular bars that define each category, however, are stacked on top of one another in this case.

1. Segmented Bar Chart

This is a form of a stacked bar chart in which each stacked bar represents a percentage of the total value of its discrete value. The overall percentage is 100%.

### Pie Graph/Chart

A Pie Graph/Chart is a circular graph that shows numerical proportions inside a dataset. Typically, this graph is divided into sectors, with each sector representing the proportion of a specific numerical element in the set.

Each sector in a pie chart represents the proportion of an element in the dataset, similar to how a pizza is divided into different slices. The proportion is determined by the sector's degree and its percentage area in relation to the circle's area.

#### Types of Pie Chart

1. Simple Pie Chart

This is the simplest form of a pie chart and is also known as a pie chart.

1. Exploded Pie Chart

One of the circle's sectors is removed (or exploded) from the pie map in an exploded pie chart. It's used to refer to data about a specific aspect of the data collection.

1. Pie of Pie

A pie of pie, as the name implies, is a chart that produces a completely new (usually small) pie chart from an existing one. It can be used to minimise chaos and focus attention on a specific set of elements.

1. Bar of Pie

This is similar to the pie of pie, with the key difference being that instead of a pie chart, a bar chart is created in this case.

1. 3D Pie Chart

In this type, a pie chart is represented in a 3-D space.

### Line Graph or Chart

A line graph is made up of a set of data points connected by a straight line. Each of these data points on the graph represents the relationship between the horizontal and vertical axes.

Depending on the type of data being visualised, the graph can ascend, descend, or do both. It goes down when studying the relationship between price and supply, and it goes up when studying the relationship between price and demand.  You can choose whether or not to include data points when creating a line map.

#### Types of Line Graph

1. Simple Line Graph

Only one line is plotted on the graph in a simple line graph. The independent variables are on one axis, while the dependent variables are on the other.

1. Multiple Line Graph

Two or more lines in a multiple line graph represent more than one variable in a dataset. This graph can be used to evaluate two or more variables over the same time period.

1. Compound Line Graph

When working with various groups of data from a larger dataset, a compound line graph is an extension of the simple line graph. In a compound line graph, each line is shaded downwards toward the x-axis. Each group of data represented by a simple line graph is stacked on top of one another in a compound line graph.

### Histogram Chart

The frequency of discrete and continuous data in a dataset is visualised using joined rectangular bars in a histogram chart. Each rectangular bar represents the number of elements that fall within a given class interval.

### Types of Histogram Chart

The histogram chart is divided into sections based on the distribution of the data.

1. Normal Distribution

A bell-shaped histogram map is typical of a normally distributed histogram. This distribution is regular, as the name implies, and it is the standard method for how a normal histogram chart should appear.

1. Bimodal Distribution

We have two classes of normal distribution histogram charts in a bimodally distributed histogram map. It is created when two processes in a dataset are combined.

1. Skewed Distribution

This is an asymmetric graph with an off-centre pick that normally points to the graph's end. Depending on which way the apex appears to point, a histogram chart is said to be right or left distorted.

1. Random Distribution

There is no typical pattern in this sort of histogram map. It's also known as a multimodal distribution because it generates several peaks.

1. Edge Peak Distribution

The composition of this distribution is identical to that of a regular distribution, with the exception of a large peak at one of its edges.

1. Comb Distribution

The rectangular bars in the comb distribution vary between tall and short, giving it a comb-like structure.

### Area Chart

Area charts are used to colour the area between the line segment and the x-axis to collectively calculate data patterns over time. In simple terms, an area chart is a line chart that has been expanded.

### Types of Area Chart

1. Simple Area Chart

The coloured segments in a simple area map overlap each other in the chart area. They're put on top of each other, intersecting.

1. Stacked Area Chart

The coloured segments in a stacked region chart are stacked on top of one another so that they do not collide.

1. 100% Stacked Area Chart

This is a type of stacked area chart in which the amount of space occupied by each group of data on the chart is expressed as a percentage of the total data. Normally, the vertical axis totals a hundred percent.

1. 3-D Area Chart

This is the kind of area map that is measured in three dimensions.

### Dot Graph or Plot

A dot plot is a graph in which data points are represented vertically by dot-like markers. Since the height of the aggregation of a group of dot-like markers is equal to the frequency of the elements in a specific class interval, it is said to be similar to the histogram chart and bar chart.

### Types of Dot Plot

1. The Wilkinson Dot Plot

To keep the dots on the plot from overlapping, this form of dot plot employs local displacement. Leland Wilkinson designed this dot lot.

1. Cleveland Dot Plot

This is a scatterplot-like chart that shows data in one dimension vertically. William Cleaveland was the one who came up with the idea.

A radar chart is a two-dimensional graphical tool for presenting multivariate data in the form of three or more quantitative variables depicted on axes starting from the same point. The spider graph is another name for it.

This is the most basic form of the radar chart, and it is the same as a standard radar chart. It is made up of a series of radii that are all taken from the same point and then joined together.

Each data point on the spider graph is labelled on radar charts with markers.

The empty space between the lines and the middle of the spider web is coloured in the filled radar charts.

### Column Chart

A column chart is a form of data visualisation in which each group is represented by a rectangle whose height is proportional to the values plotted. Vertical bar charts are another name for column charts.

### Conclusion

In analytical geometry, graphs and charts are used to map out the functions of two or more variables in a cartesian coordinate. They're also used to figure out how a statistical dataset's correlation and regression function. Data analysis primarily uses charts and graphs to make sense of a dataset. The charts simplify the data analysis process by summarising the details in a dataset. In data visualisation, there are several different types of charts, each of which is used in a different scenario. The situation in which these graphs are used is largely determined by the advantages and disadvantages of each form.

As a result, we like to use bar charts in some situations and radar charts in others. Choosing the form of chart to use is up to the data analyst's discretion, but it is affected by factors such as the strengths, disadvantages, audience, and so on.