Visualizing your data is crucial in data science research if you want to explore and understand your findings effectively. Finding patterns and trends in your data early in the project is more accessible when displaying it in a JS chart. 

After completing the project, analyzing, and using various machine learning models, data visualization can help you effectively explain your results.

The market is flooded with new libraries and styles of charts to produce data visualizations for the web as JavaScript continues to gain prominence in the data visualization space. 

However, selecting the appropriate JS chart for the data that must be presented is challenging. Thus, this article will discuss everything you need to know to choose the correct JavaScript chart for your data.

What Is The Importance Of Data Visualization?

Visual data are used in data visualization to quickly and effectively convey information to all audiences. Companies can use this technique to determine what has to be improved, what influences client contentment and dissatisfaction, and what to do with particular items. Using visualized data, stakeholders, business owners, and decision-makers may anticipate sales volumes and future growth more accurately.

Your project’s success depends on how well your data is visualized. Your audience won’t understand your work or how to utilize these results if you spent a lot of time analyzing and modeling the data but selected the incorrect chart type to communicate your results. 

There are numerous chart types; there are so many that picking the right one can be daunting and perplexing.

How To Understand Data Better?

You must comprehend a few crucial details about the data you wish to display before you can begin to consider other chart types. You will select the ideal chart type to show your data if you can better comprehend it.

Firstly, data is a tale told in numbers. Thus, you should inquire as follows:

  • What narrative is your data attempting to tell?
  • Why and how were these data gathered?
  • Are you gathering data to look for trends?
  • Is there a distribution in your data?

Thus, selecting a chart type will be much simpler for you if you are aware of the history of your data and what it is trying to convey.

Second, it’s crucial to consider to whom you will deliver your findings. One main goal of data visualization is to increase the effectiveness of data communication. To determine the appropriate chart type to utilize when presenting your data to your audience, you must first understand who they are.

Next, the type of chart you use will depend on the size of your data. Pie charts are one example of a chart type that you shouldn’t utilize with large datasets. At the same time, scatter plots are ideal for massive data. Therefore, you must choose a chart type that best matches the magnitude of your data and conveys it simply without being cluttered.

What’s The Difference Between Various Data Types?

You should probably also pay attention to the data type. There are several different categories of data, including

  • Categorical
  • Continuous
  • Qualitative
  • Descriptive

Some chart kinds can be omitted using the type of data. For instance, if your data is continuous, a bar chart might not be ideal; you might need to use a line chart. Using a pie chart or a bar chart if your data is categorical may be a smart option. 

Given that continuous categories are impossible to have with categorical data, you probably won’t want to use a line chart. There must be a specific and finite number of categories.

Finally, you should consider how the various components of your data are related. Is the order of your data determined by some aspect, such as size, kind, or time? Doesn’t it show a ranking determined by some factor? Or a relationship between various variables?

What Are A Few Popular JS Chart Types You Can Use?

We cannot mention all charts in this post, as so many charts exist. So, let’s discuss the use cases for the top four charts today.

Bar Charts

A bar chart is employed when displaying the distribution of data points or comparing metric values across several subgroups of your data. 

A bar graph allows us to determine which groupings are most numerous or prevalent and how different groups stack up against one another. Bar charts are reasonably common because this is a fairly typical assignment.

Pie Charts

Pie charts have a specific use case, captured by their definition. A whole quantity is required to use a pie chart. 

Your main goal should be comparing their contributions to the whole. The pie chart is inappropriate if it is not met, and you should use another plot style.

For example, if we consider the market share of a company, then a pie chart would be the best option:

const dataSource = {
chart: {
caption: “Market Share of Web Servers”,
plottooltext: “<b>$percentValue</b> of web servers run on $label servers”,
showlegend: “1”,
showpercentvalues: “1”,
legendposition: “bottom”,
usedataplotcolorforlabels: “1”,
theme: “fusion”
data: [
label: “Apache”,
value: “32647479”
label: “Microsoft”,
value: “22100932”
label: “Zeus”,
value: “14376”
label: “Other”,
value: “18674221”
FusionCharts.ready(function() {
var myChart = new FusionCharts({
type: “pie2d”,
renderAt: “chart-container”,
width: “100%”,
height: “100%”,
dataFormat: “json”,

Line Charts

When you want to highlight variations in values for one variable (plotted on the vertical axis) for continuous values of a second variable, you will use a line chart (plotted on the horizontal). 

Line segments regularly going from left to right and seeing the slopes of the lines moving up or down help sell this emphasis on patterns of change.

Scatter Plots

The primary purposes of scatter plots are to examine and display correlations between two numerical variables. The patterns exhibited by the dots in a scatter plot, for example, are in addition to the values of the individual data points when the data is seen as a whole.

Which Tools Can You Use To Create JS Charts?

Developers can provide data visualizations in the form of charts on several platforms. FusionCharts is a viable choice.

You can create dashboards with the aid of your web and mobile projects.

Adding interactive and responsive charts is simpler thanks to thorough documentation, cross-browser compatibility, and a consistent API.

Creating JavaScript graphs is straightforward. It is a comprehensive JavaScript framework for dynamic and interactive charts.

You can integrate it into any online application with just a few lines of code. 

What Should You Remember About JS Charts?

With interactive visual representations of the data, data visualization positively influences an organization’s decision-making process. Businesses can now interpret data in graphical or pictorial representations to rapidly identify trends.

You must learn more about your data and the context in which you should use it. In addition, you must know your target audience/media before deciding on the type of chart to employ. When attempting to construct a visualization, go with neutral hues and fonts.

Above all, always strive to visualize things simply rather than intricately. Data visualization aims to simplify data for easy comprehension and reading. People prefer multiple straightforward graphs to a single complex one.

This post should have provided a clear and easy method for choosing the JS chart that most accurately and effectively communicates your data.

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