Visual representation of data is best used for graphs and charts. Here’s how you can effectively present data in graphs.
In the age of data overload, it’s easy to get lost in the information of it all. Every day, we are processing data — whether it’s on autopilot or conscious action. Autopilot data processing is a no-brainer. It’s just for our own personal use and does not need to be conveyed to a third party for the information to have value. On the other hand, data that needs to be presented to an audience needs to be converted from raw data to digestible content. Visual representations of raw data come in different formats. Which one to use depends on the data that needs to be presented and how the user wants the content conveyed.
One of the most commonly used types of visual data representation is through graphs. Data is plotted in a diagram along with a pair of axes — using a graph maker — which shows the relationship between a set of variables. It’s a much more understandable format to show what could be pages or mountains of raw data into a graphical one. Trends are effortlessly detected, and relationships are easily identified when using this specific type of visual presentation.
There are several different types of graphs. This article will cover the three most commonly used and how to present data in graphs.
Types of Graphs
The most commonly used graph of all is the line graph. Used in academic and business settings, it’s an efficient way to display trends, especially changes that happen over a long time. Each variable is presented in each axis X and Y. The X-axis holds the independent variable, which means values in that axis do not change. In contrast, the Y-axis contains the dependent variable, which are values that can and do change.
In business, a line graph is an excellent representation of data accumulated in sales or revenue. This allows a quick analyzation of when sales are low and when it peaks. For example, you can use a line graph to show the sales trend over one year. The twelve months in a year reflect along the X-axis, as months’ value does not change. On the other hand, sales or revenue is displayed along the Y-axis. These data values tend to vary, depending on the time of the year. So it’s easy to reflect its increase or decrease along the vertical axis.
Best used for displaying categorical data, a bar graph showcases trends over time. Each block in a bar graph represents a group of categories, and the trend is illustrated by the rise or fall of the block’s height. Categories are displayed on the horizontal axis, while the quantity or amount is on the vertical axis.
For example, in identifying the most popular takeout restaurants in the area, the horizontal axis can represent cuisine categories. It can be Indian, Chinese, Subway, or a diner. Along the vertical axis is the quantity of orders. You can narrow the parameters on the vertical axis to a single day of the week or an entire weekend. It depends on what specific analysis you want to capture from the graph.
Scatter plots are used to outline two different variables’ correlation or relationship. For example, to show a correlation between temperature (Variable A) and crime rates (Variable B), each variables’ data is plotted along its corresponding axis as dots — horizontal for Variable A, vertical for Variable B. The result of the scatter plot reveals if there’s a correlation between the variables: a) if temperature affects crime rates and b) how much each variable affects the other.
If there is a correlation or relationship between the two variables, the dots will appear directly near each other, which will form a line. If there’s no significant correlation, the dots will appear randomly scattered on the graph’s diagram.
Best Way To Present Data in Graphs
Now that we’ve covered the most common types of graphs and how best to use them, here’s how to conveniently present your data in graphs:
1. Identify the type of data on hand
It’s essential to identify if the data you have on hand is qualitative or quantitative. Quantitative data are also known as objective data. This means the data set is typically in numbers and is measurable. Qualitative data, on the other hand, usually is subjective; observed but cannot be measured.
A person’s height is quantitative when the data is 6’3″. However, if the data is “tall, ” qualitative. Identifying the type of data on hand enables you to decide which graph type is more suitable.
2. Input data into a worksheet
Once you have your data, input it into the worksheet. You cannot create a graph without a data series. A data series is a column or row of data values (numbers or text) encoded into a worksheet to create a graph. Be sure that the data entered is correct to avoid generating incorrect trends onto your graph.
3. Choose a graph type and import data
If using Excel to create data, highlight the data series you wish to reflect on your graph. Next, click on the ‘Insert’ tab, and choose the graph you want to use. Once your graph is generated, you can customize the colors, labels, and other elements. Then, just right-click on the graph for options.
There is no one best way to present data in graphs, but there is an easier way to create and present one. Free design solutions, like Venngage, not only makes it convenient to create graphs, but its premade templates ensure stunning visual designs. Data input is tricky already, so work smart by making use of premade templates and customizable designs.