Table of Contents
A. Get familiar with a variety of chart typesSometimes all you need is a chart, one that visualizes your information and makes a point. But which chart should you choose? Creating the right chart can be difficult, especially when the choices involve so many different chart types. Well, in this section, you’ll get familiar with a variety of chart types.
- Column and bar charts
- Line and area charts
- Pie and doughnut charts
- Stacked charts
- Combination charts
- Bubble and scatter (XY) charts
- Market share charts
- Pareto charts
1. Column and bar chartsColumn charts are used to compare data from similar categories. For example, sales by month or sales by region. They compare this data over time. Each column in the chart represents a specific category. The category’s value is represented by the length of a column, and the columns all begin at the same value. This way, users can easily see differences in values among categories or differences in value over time. Bar charts convey information to help you compare the values of different categories. These charts use bars of equal width with lengths proportional to the values they represent. This makes comparing across categories easier. One axis plots categories and the other axis represents the value scale.
2. Line and area chartsA line chart is a form of charting where you use a line to connect points that correspond to data values. Line charts often illustrate trends or changes over time. They are the most common type of chart for illustrating changes in data over time. Next, an area chart is like a line chart in that it shows changes in data over time. An area chart, however, uses bars instead of lines to connect the data points with the x-axis values. In addition, each bar includes color as well as filled space. This can give a visual representation of overall change within a time frame.
3. Pie and donut chartsAfter that, a pie chart is a circular graph divided into segments. Pie charts compare parts to the whole. The number and size of similar values in a data set determine each segment’s size. The length of a slice’s arc on the graph’s perimeter represents the percentage value of the variable. Radial lines connect the arcs to the circle’s center. Then, a doughnut chart is a graphical representation of data. It uses a pie chart, but instead of a circle in the middle, it has an empty space. The space generally shows important information about the chart. You can highlight information by “slicing out” different portions of the doughnut.
4. Stacked chartsThere is also the stacked graph. It visualizes data like expenditures or profits. Stacked charts combine different layers into one chart. This is useful because it is easier to compare changes across multiple categories when you see the values on the same chart. Stacked graphs are often used in bar charts and line charts. Sometimes you need to see the big picture, and that’s when a stacked bar graph comes in handy. They combine groups of values into one simple bar graph so you can quickly grasp the total amount of change over time across several products or services.
5. Combination chartsCombination charts, like multi-series charts, allow you to plot multiple categories. They also let you show different representations of your data. This can help you better analyze and understand the information shown on your chart. They’re also for displaying and comparing multiple categories within a single view.
6. Bubble and scatter (XY) chartsNext, the bubble chart visualizes three variables. Two values locate the point on the x- and y-axis, and the third variable is represented by the size of the bubble. A common way to use it is to compare and depict relationships among variables by means of positioning and proportions. It can be used to analyze patterns and trends in data. A scatter chart shows two numerical parameters and how they are related. Scatter charts use a Cartesian coordinate system to display the value of one parameter on one axis and the value of another parameter on another. If both parameters are numeric, this chart type shows how one parameter impacts the other. For example, you might use a scatter chart to plot the relationship between income and expenditure or temperature and sales.
7. Market share chartsA Marimekko chart (also called a mekko or market share chart) is a two-dimensional chart that shows the relationship between categories of data and their segments in terms of percentages as well as varying column widths to represent the data. The x-axis represents the relationship between sums of values within categories and the y-axis represents the percentage scale. This visualization is primarily for sales data and marketing analysis.
8. Pareto chartsA Pareto chart shows the frequency of problems or causes in a process. Pareto charts focus on problems or causes. They help you determine which ones are most significant. A Pareto chart can also show the components of a problem, as well as how it affects related processes. They are useful when communicating with others about your data. The Pareto chart is a graph that shows frequencies or costs by arranging the bars of different lengths. The bars are arranged from the highest frequency (or cost) on the left to the lowest on the right. The chart is used to demonstrate which situations are more significant.
B. Integrate ready-made charts for faster and better resultsAs a data scientist, the last thing you want to worry about is how to make the pretty visualizations you need for your project’s deliverables. You would rather focus all of your energy on the results. That’s where FusionCharts comes in handy. FusionCharts provides charting solutions for businesses across all industries, from health care and education to finance and energy. It simplifies the creation of highly interactive data visualizations for business and technical users. It is a great option for a data science project. FusionCharts is an awesome visualization library. It provides a selection of charts and graphs you can use on your project and tons of customization capabilities. It also has a ready-made open-source integration with most popular tech stacks. This includes back-end integration (e.g., ASP.NET, Java, PHP) as well as front-end integrations (e.g., Vue.js, Angular, or React), all ready to help you ship your projects faster.
Let’s see how you can get these charts installed on your server and customized to your liking.If you’ve ever tried installing an open-source charting library of your own, you know how challenging it can be. It’s not always obvious what types of charts are available and how to get them up and running on your project. FusionCharts makes creating charts easy by providing premade charts with the code ready to copy and paste into your data science projects. These are high-quality charting libraries that have been battle-tested by being used in companies like Facebook, Apple, Google, Oracle, IBM, Intel, Adobe, and more!
Create over 150 charts and more with the Django plugin for FusionCharts
- Quick demo: Django Module for FusionCharts
- Here’s a step-by-step documentation guide to creating charts using the Django Python framework.