Graphic representation is an important branch of data science that is increasingly relevant in our society. In a world where technology is so important in our lives, the ability to measure data and its subsequent representation is fundamental. To that end, in this post we will see the most common types of graphs we find, what they are for, and how we can create them.
Let’s start at the beginning… What are graphs?
Graphs are the visual representation of a related set of data that are usually numerical. Not only do they serve as a visual aid, but through them we can obtain trends or relationships between the variables with which we are working.
Graphs have many applications and, depending on our objective, it will be more appropriate to use one type or another, but their main uses include:
- Representation of research results
- Presentation of data for a sales or social media report
- In demography, data representation is used to display population distribution using histograms or glyphs.
- Data comparison
- As a visual aid for a presentation and/or infographic
Interactive Graphics: Have you created yours yet?
For a few years now, interactive content has been much more integrated into our lives. Thanks to tools like Genially it is possible to bring our content, and in this case, graphs to life.
Interactive graphs create a better experience for the reader, increasing their attention and understanding of the content we’re showing them.
Excel and other data processing software may have certain advantages, but they are less visual, lack interactivity, and may cause our audience to stop paying attention. If you want to make attractive graphs online and share them with others or integrate them into web pages like our friends at Maldita did, Genially is a perfect tool.
Next, we’ll look at the most prominent types of graphs and how to easily generate them.
Types of Graphs
Now let’s discuss what types of graphs exist, what we can use each of them for, and how we can make them in a simple and easy way.
Column Chart: Simple, grouped, or stacked
This type is one of the most used in tools like Excel in which a lot of data is organized and represented very simply as columns.
We can generate another type of columns which are stacked or grouped with a different data organization than the previous type. Stacked columns are used to divide a category into smaller categories and to know what their relationship to the main category is.
Uses: Any kind of graphical representation of a dataset that we can organize into different categories. It is also used to visualize how the data changes over time. A company’s total sales divided by country is an example of a good dataset to represent as a stacked column chart.
The bar graph is a representation of variables in which the height of each bar is the “frequency” of each value. We can find these graphs in a vertical or horizontal format.
The difference between the column chart and the bar graph is that the bar graph serves qualitative variables, although they are sometimes used interchangeably, so the uses we can find for both are very similar.
The pie chart is a widely used representation in statistics where the “pie” represents 100% and each slice represents its value in proportion to the whole.
Uses: Uses can vary widely, although in most cases they will represent a “percentage of.” In education we may use the pie chart to view a student’s attendance rate or the percentage of students who achieve each possible grade on a test or in a class. Other uses may be to view the percentage of traffic from your social networks to your website or to find out the percentage of the population that voted in an election compared to the percentage that did not.
We usually use the line graph to represent large amounts of data over time. It is normal to see a second line in these graphs that represents the average of the data we are representing, or a comparison line for another metric that we want to compare with.
Uses: The uses can be quite varied. Some ideas include: The evolution of a company’s total sales over a period, the increase in people registering on your elearning platform, or the evolution of life expectancy throughout the 21st century.
Very similar to the line graph but the area from the value to the X axis is filled with a color or texture.
Uses: Similar to a line graph, although it is true that we see them most frequently used to represent cumulative totals. For example, to compare the purchases of two of your best customers throughout the year.
These graphs are very similar to the pie charts we saw before; both of them show us the data as a percentage of the total. However, this type of graph is more visual because it can fit more data due to its design.
They are ideal as a performance indicator. There are two types of progress charts: bar or speedometer. You can use whichever you like best!
Uses: It’s very common to see them on dashboards or control panels to see the performance of a team, the advancement in the didactic programming of an elearning system, etc.
Scatter plots are a perfect tool for studying data relationships based on two variables: X and Y. This graph shows each value as points in a “data cloud” that moves along the axes based on their relationship.
- Relationship to X: If a point on the chart is further right, it represents a higher value or quantity of X.
- Relationship to Y: If a point is high on the graph, it represents a higher value or quantity of Y.
In short, if we see a point far up to the right, it means that it has a strong relationship with both X and Y. If we see it right at the beginning of the graph, at the bottom left, it means it is not very related.
Uses: These graphs are very common in the corporate sector and we can see them in graphs that compare a company to the competition based on two factors: when the objective is to find correlations between the data and studying trends (we often draw a line so we see the increasing or decreasing trend clearly)
Gantt charts are a representation of the set of activities or tasks in a project. To make one we need:
- A list of activities to be carried out in the project, and a relationship with the established start and end dates.
- A list of tasks within each activity, or number of sprints, to measure the progress of each activity and the project in general.
This template will help you organize your projects, as in the example below:
Uses: Gantt charts are widely used in managing large projects or tasks involving a set of work teams, making them a must-have tool for any Project Manager.
Radar or Web Chart
Radar charts are designed to represent the comparison of multiple variables. They can tell us which variables are most relevant to our objective and which are less relevant. It’s important that we find a balance because each variable adds one more aspect to the graph and this can be a problem for interpreting data.
Other graphs and charts
There are many other types of charts/graphs that we can highlight such as:
- Funnel Charts
- Pyramid Graphs
How to make a graph in Genially
With Genially, it’s possible to generate online graphics just by copying and pasting the data you want, so making a graph or chart is quick and easy.
To do this, we will follow these steps:
Step 1: Prepare the data
It’s recommended to have all the data already organized and ready to paste in Genially. You just need to paste the data and you will have generated the type of chart that you selected.
Step 2: Where are you going to put the graph or chart?
Once we have the data we want to manipulate ready, we open the Genially where we will insert the graph or chart. It can be in a dashboard or report template to which we want to add a blank graphic or a blank genially if, for example, we want to insert it into some website or blog (as we have done in this article).
In this case, we created a performance report of a website where we needed to represent the trend we’re having on a monthly basis. That’s why we opened the report in Genially and created a canvas on which to insert the graph.
Step 3: Where the magic happens
This is where it all comes together. In the panel we click on “Resource,” go to the Graphics section, and select the one that best suits what we need. We already know all the types of graphs and charts, and the differences between them, so we should not have any problem choosing.
In this case, we selected a series line graph because it’s the one that best adapts to represent data over time and compare it with earlier data. Here’s the interactive performance report created with Genially. Click to see the result:
Templates to speed up your work
In addition, there are different dashboard templates in Genially to save you time in presenting data. It’s as simple as dumping the information into the corresponding chart and you’re ready to go!
And just like that we’ve created a chart or graph online and forgotten about Excel. Furthermore, with Genially, any graphic is easier to share and integrate onto other platforms. To end, we’ll look at some tips if you’re not used to working with data.
- Set the goals of your study before collecting data. Decide the questions you’d like to answer and break down what information you need to answer them.
- If you are representing data that is not your own, verify the source correctly. This is a collection of websites from public sources where you can download data (very useful for journalists, researchers, or content generators)
- Represent your data in the simplest way. It’s important to know the target audience that will read your study, infographic… Offering more data does not mean you are creating better research. Be clear and concise.
- Add titles to each of the data representations you make. Be descriptive.
- Add captions and tooltips. With tooltips, Genially makes adding captions easy. Whenever you or the viewer hovers over them, a tooltip will appear indicating the data you are viewing.
- Leave a final section for conclusions. In an infographic it’s common to put the data as high up as possible and leave the end for conclusions or advice you want to give.
If you’ve created any of these types of charts or graphs with Genially, share the link in the comments 😊📈