In today's era, data is playing a major role in various sectors of business, healthcare, education, technology, and science. It is driving decision making, innovation, and strategic planning processes. Data has become one of the major drivers of economic growth, technological advancement, and societal development, transforming the way we work, learn, and interact. Despite its crucial role, many have yet to recognise the importance of data. One of the main reasons for this oversight is the complexity of data representation, which is often difficult for most people to understand. Therefore, the representation of data is really important. In this topic, we will learn about data visualization.
Visualization of data
Data can be referred to as raw facts or figures, which do not provide much context or meaning without processing, organizing, structuring, and interpreting. However, once interpreted, these facts and figures become useful information that aids in decision-making and provides valuable insights.
Data visualization is the practice of converting processed and interpreted data into a visual context, such as graphs, maps, etc., to make complex data more understandable, accessible, and usable. It is not always necessary to use interpreted data; sometimes, even raw data can provide insight and help with visualization as well. Data visualization plays a major role in different fields today because it helps people understand complex data, identify patterns, and ultimately make data-driven decisions.
Introduction to basic charts
In the realm of data visualization, basic charts are essential tools used to represent and interpret data. These tools help the user in better understanding complex data. Let us learn about some types of these basic charts.
Pie chart: A pie chart is a circular graph divided into several arc slices, each representing various aspects of data. Named for its resemblance to a pie cut into slices, each slice of the pie chart corresponds to a category of data. The size of the slice represents the proportion or percentage of that category within the whole dataset. This means pie charts are good at showing how different parts compare to the whole. They help us see what share each category contributes to the total.
For example, consider a classroom full of students. Let's utilize a pie chart to visualize the gender distribution among these students, illustrating the respective percentage of students who identify as male, female, or other.
Suppose there are 30 students:
Female: 15
Male: 12
Other: 3
From the Pie chart above, we can see that the number of female students surpasses that of any other gender, and that individuals who identify as neither male nor female are in the minority.
Bar chart: A bar chart is a diagram that uses either horizontal or vertical bars to show comparisons among different categories of data. Each bar represents a category, and its length or height represents the quantity or amount for that category. Bar charts are good at showing comparisons among categories, allowing us to see which category has the larger quantity or frequency. One of their key advantages is their capacity to display differences between groups effectively, making it easier to see which category prevails, be it in size or frequency.
Let us suppose there are various items in a shop. We could represent the sales of these items in a bar graph.
From the chart above, we can see that the best-selling items are chocolates and drinks, respectively, while noodles are not selling that well. Implementing this data, the vendor can get insights into the most and least popular products. This allows the vendor to adjust their inventory investment accordingly.
Line chart: A line chart, also known as a line plot or line graph, is a type of chart that displays information as a series of points connected by straight line segments. This chart is often used to visualize trends in data over time periods. Typically, the horizontal line in a line chart represents the time intervals, while the vertical line usually indicates the amount or quantity of an item. Each point on the line stands for a piece of data from our information. The direction and steepness of the line, whether it moves up or down, shows what's happening with our data over time, symbolizing whether the data is increasing or decreasing. Therefore, line charts are effective for illustrating changes over time and predicting future trends.
The line chart demonstrates the sales of chocolate over a specific period. It shows a gradual increase in sales from Sunday to Monday, followed by a sudden drop on Tuesday, and a spike on Wednesday.
Choosing proper chart
There are numerous types of charts that accurately represent data, each having its own significance. Choosing appropriate charts for data visualization is crucial. Let's examine what situations the above charts are mostly suited for.
Proportion of whole
The term "proportion of whole" refers to how much a particular piece or segment represents from the total amount. For example, if a chocolate bar is divided into 4 pieces and you eat 1 of them, it can be represented as 1/4 of the chocolate bar.
These kinds of situations can be represented by the following charts:
Pie chart
In the aforementioned scenario, one piece out of a whole chocolate has been consumed, so it can be represented as follows:
Bar chart
We can also represent the above data using a bar graph:
Trends and changes over time
Trends and changes over time are often represented in data visualizations to show how a certain variable has changed during a specified period. The most commonly used type of chart to represent these trends and changes over time is a line chart.
For example, let us see the amount of pizza consumed by a person in a month during the year 2023:
Conclusion
Data visualization refers to the practice of converting data into a visual context, such as graphs, maps, etc., to make complex data more understandable, accessible, and usable. It helps identify patterns and make data-driven decisions.
Pie charts are circular diagrams divided into slices, or arcs, that represent different categories of data. The size of each slice shows the proportion of that category within the whole dataset, which makes them effective for showing how different parts compare to the whole.
Bar charts use horizontal or vertical bars to show comparisons among different categories. Each bar represents a category, and the length or height of the bar represents the quantity for that category. They are excellent for showing comparisons and differences between groups.
Line charts, also known as line plots or line graphs, display information as a series of points connected by straight line segments. They are often used to visualize a trend in data over intervals of time, making them effective for showing changes over time and predicting future trends.
The appropriate chart type depends on the nature of the data and the message you want to convey. Pie charts effectively display proportions of a whole, bar charts are good for comparing quantities across categories, and line charts excel in showing trends over time.
Remember, effective data visualization is not just about choosing the right chart, but also about presenting the data in a manner that is clear, accurate, and meaningful to your audience.