Types of Graphs: How to Create Stunning Visualizations with Your Data
Table of Contents
Definition of Graphs
The word ‘Graph’ comes from the Latin word, “graphus” which is an instrument for making or transmitting records or images.
A graph is a relationship between two or more items that are frequently represented by the points on a graph. The purpose of the graph is to organize numerical data visually so that it can be quickly, simply, and clearly understood.
Importance of Graphs in Data Visualization
When spoken material is accompanied with a visual graph, you may recall it more easily than when it is not. Therefore, if the data is effectively communicated, decision-makers can act quickly based on data insights, increasing both decision-making and business success.
Graphs assist you focus on the information being displayed and aid in remembering it for future reference.
Graphs can also be a powerful technique to convey information to huge crowds of people, where some people might find written information difficult to read.
Benefits of Using Graphs in Data Visualization
1. Relationship Correlations
Finding the correlations between independent variables might be difficult without data visualization. We can improve our business decisions if we can make sense of those independent variables.
2. Saving Time Through Data Visualization
Compared to simply examining a chart with numbers displayed in no specific manner, data visualization through graphs makes it faster to get certain insights from the data.
3. Trends Over Time
Without the required knowledge from the past and present, forecasts cannot be made. Trends over time help us understand our past and potential future.
4. Risk and Reward
Analyzing value and risk measures needs skill since, in the absence of data visualization, we must decipher challenging spreadsheets and figures. When data is visualized, we may then identify regions that could or might not need action.
5. Reacting to the Market
Being able to quickly and easily access information with data shown in a clear manner on a useful dashboard enables firms to act fast in response to findings and helps them avoid making mistakes.
Types of Graphs: Overview
When working with numbers and statistics, it is imperative to incorporate data visualization into your initiatives. Having pictures to represent your facts can immensely aid your audience in understanding whatever it is you are generating.
But how can you tell which graphs and charts will work best for your information and industry?
Every type of graph is a graphic representation of data plotted on a diagram (such as a bar, pie, or line chart) that demonstrates various trends and relationships in the data. We’ve compiled a list of 5 different sorts of graphs to assist you in selecting the finest ones for your information.
1. Bar Graphs
Bar graphs are visual depictions of groups of data that are made up of vertical or horizontal rectangular bars with lengths that are equal to the data’s measure. One of the most widely used graph and chart forms, they are frequently used to compare data from several categories.
Rectangular bars are used to depict categorical data. The comparison categories are shown on the bar chart’s one axis. A measured value can be seen on the other axis.
Example: The bar chart below shows the number of children enrolling themselves in different types of activities at their homes; the x-axis represents the different types of activities and the y-axis represents the number of children.
2. Line Graphs
Graphically displaying data that is continuously changing over time is a line chart. Each line graph is made up of points that link data to demonstrate a trend (continuous change). X and Y axes are present in line graphs. Time is often distributed along the horizontal axis.
Example: The line graphs below show the number of online food deliveries of various companies such as zomato, swiggy, and KFC during a span of five months; the x-axis represents the delivery over a span of five months, March-July, and y-axis represents the number of online food deliveries in thousand.
3. Pie Charts
One sort of graph that illustrates the information in the circular graph is a pie chart. Pie charts emphasize numerical proportion while presenting facts and statistics in an understandable, “pie-slice” format.
Each pie slice is proportional to how big a given category in a specific group is overall. The pie chart divides a group into smaller portions, to put it another way. A list of numerical and category variables is required to create a pie chart.
Example: The pie chart below shows the amount of water used in activities such as using restrooms, showering, faucets, washing clothes, leaks and others in our household on a daily basis.
4. Scatter Plots
The scatter diagram displays the relationship between pairs of numerical data by graphing them with one variable on each axis. The goal is to demonstrate how significantly one variable influences another. Typically, the first variable is referred to as independent and the second variable is referred to as dependent because its values depend on the first variable.
Example: The scatter plot below shows the relationship between the height and age of a new-born baby. In this the height is the dependent variable and age is the independent variable.
5. Area Graphs
To illustrate how the numerical values of one or more groups vary over the course of a second variable, usually time, an area chart combines the line chart and bar chart. By including shading between the lines and a baseline, similar to a bar chart, an area chart can be distinguished from a line chart.
Example: The area graph below shows the active users of an ed-tech company for their trial, basic and premium courses during a span of sixteen months. The time span from Nov 2019 to Feb 2021 is shown on x-axis, whereas active users are shown on the y-axis.
How to Choose the Right Type of Graph for Your Data Analysis
Asking yourself these five important questions regarding your data is necessary before you look at different chart types. You can choose the ideal type of chart to display your data by answering these questions, which will help you better comprehend your data.
- What message is your data attempting to convey?
- To whom will you present your findings?
- How much data do you have?
- What data type do you have?
- How are the various components of your data related to one another?
Bar Graphs
When to Use:
- To compare data among different categories.
- Bar charts can also show large data changes over time.
- Bar charts are ideal for visualizing the distribution of data when we have more than three categories.
When to Avoid:
- If you have numerous data points.
- If your categories are numerous, there shouldn’t be more than 10 bars in your graph.
Line Graphs
When to Use:
- Line graphs are useful for displaying trends, that is the continuous dataset you are using is dynamic.
- When you need to forecast something based on a history of data across time.
- When contrasting two or more distinct factors of data during a specific time period.
When to Avoid:
- When you have smaller datasets.
Pie Charts
When to Use:
- When you want to produce and depict the composition of something.
- It is excellent for showing nominal or ordinal data groupings.
- To display proportional or percentage data.
- Pie charts are most effective when showing data for three to seven categories.
When to Avoid:
- If your dataset is large.
- If you wish to compare two values in an exact or absolute manner.
Scatter Plots
When to Use Scatter Plot:
- When attempting to determine whether there is a relationship between two variables.
- Based on the measurement of the independent variable, forecast the behavior of the dependent variable.
- When there are paired numerical data.
When to Avoid:
- If your dataset is small.
- If your dataset’s values do not exhibit any correlation.
Area Chart
When to Use Area Chart:
- To convey trends rather than precise data.
- In order to demonstrate part-to-whole linkages.
- If you want to show the size of your data rather than just how it relates to time.
When to Avoid:
- Discrete data cannot be used with it.
- To compare a limited number of types.
Uses of Graphs in Different Fields
1. Social Media
Graphs depict who is connected to whom, how they interact and influence one another, as well as other relationships within the social structure. These can be used to determine how ideas propagate, what subjects become popular, how communities develop, and even who could be a good match for that particular person.
2. Epidemiology
In today’s world, disease propagation is prevalent. Understanding and limiting the spread of illnesses now depend heavily on the analysis of such graphs.
3. Traffic Management
In public transportation networks, vertices represent stops, and edges represent the connections between them. Such networks are used by several map services, including Google Maps, Bing Maps, and Apple iOS maps, to find the best routes between locations.
4. Solving Crimes
Investigations involving crime often employ graph methodology. It can help you identify the perpetrator of a significant crime by representing events as vertices on a graph and potential relationships as edges.
5. Web Page Research
Each edge indicates a connection between two sites, and each vertex represents a separate web page. To assist with the connecting procedure, algorithms are used. The graph connects websites and webpages, aiding in page ranking and allowing Google to show the best page.
Why Graphs are Important in Data Analysis?
In the workplace, data gathering, analysis, and charting are crucial. Employees at all levels should be familiar with and confident in utilizing a range of charts. Statistical knowledge is crucial for problem-solving and making decisions. Thus, adults can make better decisions by comprehending the deluge of statistical data.
Children may study graphs in a fun and engaging way with the help of {igebra.ai}. Enabling the opportunity to view numbers in various contexts. Young children who are introduced to graphs are better able to count fast, organize, compare, and discuss data.