4.2 Data Visualization

It is the process of creating graphical representation of data and information. It involves various visual elements like charts, graphs, and maps. This graphical representation is useful to make decisions in the field of science, arts and in daily life. It is a powerful tool that transforms raw data into meaningful and insightful information.

Data visualization through charts, graphs and plots, makes complex information simple to understand and helps in making meaningful decisions. Some interactive data visualization techniques are helpful to get optimal results from the available data. Data visualization have variety of techniques and types that helps to get meaningful information from data and use it for the improvement of business and services.

4.2.1 Methods of Data Visualization

Methods and types of data visualization are interrelated terms. However, methods of data visualization are the techniques to prepare data for visualization. These methods are explained briefly as follows:

Bar Chart: This method of data visualization is used to show comparison among discrete values. For example, we can use Bar Chart to visualize marks of students in various subjects or sales data of various products in a company.

Line Chart: It is used to display trends of data over short or long period of time. For example, gold prices over the last five or ten years can be displayed by using a Line Chart. Similarly, stock prices, or change in temperature over a year can be presented by using a Line Chart.

Pie Chart: It is used to represent proportions of various categories of data in a whole. For example, market shares of various companies.

Scatter Plot: It is used to display the relationship between numerical variables. For example, correlation between height and weight of a group of people or correlation between head volume and head circumference of male and female students of certain grades.

Histogram: It is used to show the distribution of a single numerical value. For example, distribution of score in a class.

Box Plot (Box-and-Whisker Plot): It is used to summarize the distribution of data with the help of minimum, first quartile, median, third quartile and maximum data. For example, analysis of salaries of various employees in a company.

Heatmap: It is used to represent data in matrix form. Data values are shown by using color intensity. For example, images received from the space to analyze weather forecast. Another example is of climate change, or measurement of different parts of flowers.

Bubble Chart: It is similar to scatter plot, but it has a third variable which is represented by the size of bubble. For example, points in a 2D space where area of each point is proportional to the third variable.

4.2.2 Types of Data Visualization

Thera are different ways to represent data graphically to make it easier to understand. Son common types of data visualization are as follows:

Quantitative Visualization

Quantitative visualization is used to represent numerical data. It focuses on quantities or numbers to show measurable data. It is used to display data that can be measured or counted. For example, a bar chart showing sales figures of a company over several months effectively communicates quantitative information.

Categorical Visualization

Categorical visualization is used to represent data that falls into distinct categories. It helps to show proportions or parts of a whole. This type is ideal for displaying nominal or ordinal data. For example, a pie chart showing the market share of different companies in a specific industry.

Temporal Visualization

Temporal visualization is used to display data that changes over time. It is used for time- series data. Line graphs are usually used to represent temporal data. For example, a line graph.

Spatial Visualization

Spatial visualization is used to represent data related to physical locations or spaces, visualizing geographic or spatial data. For example, a heatmap showing population density across different regions.

Multivariate Visualization