Basic data is mainly 2-dimensional with a focus on raw data represented through lines, curves, etc. Charts, on the other hand, is a representation of datasets with the intent of making the user understand the information in a better manner.
Graphs are a good example of charts used for data visualization. There are various types of graphs and charts used in data visualization. However, in this article, we'll be covering the top 11 types that are used to visualize business data. A bar chart is a graph represented by spaced rectangular bars that describe the data points in a set of data.
It is usually used to plot discrete and categorical data. The horizontal axis of the chart represents categorical data while the vertical axis of the chart defines discrete data. Although the rectangular bars in a bar chart are mostly placed vertically, they can also be horizontal.
For horizontally placed rectangular bars, the categorical data is defined on the vertical axis while the horizontal axis defines the discrete data. Grouped bar charts are used when the datasets have subgroups that need to be visualized on the graph. Each subgroup is usually differentiated from the other by shading them with distinct colors.
The stacked bar graphs are also used to show subgroups in a dataset. But in this case, the rectangular bars defining each group are stacked on top of each other.
This is the type of stacked bar chart where each stacked bar shows the percentage of its discrete value from the total value. A pie chart is a circular graph used to illustrate numerical proportions in a dataset. This graph is usually divided into various sectors, where each sector represents the proportion of a particular numerical element in the set. Just like a pizza is divided into different slices, each sector in a pie chart represents the proportion of an element in the dataset.
The proportion is defined by the degree of the sector and the percentage area with respect to the area of the circle. In an exploded pie chart, one of the sectors of the circle is separated or exploded from the chart. It is used to lay emphasis on a particular element in the data set. As the name suggests, a pie of pie is a chart that generates an entirely new usually small pie chart from the existing one.
It can be used to reduce clutteredness and lay emphasis on a particular group of elements. This is similar to the pie of pie, with the main difference being that a bar chart is what is generated in this case rather than a pie chart.
Line graphs are represented by a group of data points joined together by a straight line. Each of these data points describes the relationship between the horizontal and the vertical axis on the graph. The graph may ascend, descend, or do both depending on what kind of data is being visualized. When studying the relationship between price and supply, it goes down and for peace and demand, it goes up.
In a simple line graph, only one line is plotted on the graph. One of the axes defines the independent variables while the other axis contains dependent variables. Multiple line graphs contain two or more lines representing more than one variable in a dataset. They are best used for comparison, composition, or relationship analysis when there are only few variables and data points.
It would not make much sense to create a chart if the data can be easily interpreted from the table. For example, if you want to show the rate of change , like sudden drop of temperature, it is best to use a chart that shows the slope of a line because rate of change is not easily grasped from a table.
The column chart is probably the most used chart type. This chart is best used to compare different values when specific values are important, and it is expected that users will look up and compare individual values between each column.
With column charts you could compare values for different categories or compare value changes over a period of time for a single category. Histogram is a common variation of column charts used to present distribution and relationships of a single variable over a set of categories. A good example of a histogram would be a distribution of grades on a school exam or the sizes of pumpkins, divided by size group, in a pumpkin festival.
Use stacked column charts to show a composition. Do not use too many composition items not more than three or four and make sure the composing parts are relatively similar in size. It can get messy very quickly. Before moving to the next chart type, I wanted to show you a good example of how to improve the effectiveness of your column chart by simplifying it.
Credit: Joey Cherdarchuk. If you have long category names, it is best to use bar charts because they give more space for long text.
You should also use bar charts, instead of column charts, when the number of categories is greater than seven but not more than fifteen or for displaying a set with negative numbers. Stacked bars are not good for comparison or relationship analysis. The only common baseline is along the left axis of the chart, so you can only reliably compare values in the first series and for the sum of all series.
Line charts are among the most frequently used chart types. Use lines when you have a continuous data set. These are best suited for trend-based visualizations of data over a period of time, when the number of data points is very high more than With line charts, the emphasis is on the continuation or the flow of the values a trend , but there is still some support for single value comparisons, using data markers only with less than 20 data points.
How do you visualize and analyze the data so you can extract insights and actionable information? M ore importantly, how can you make reporting more efficient when you're busy working on multiple projects at once? One of the struggles that slows down my own reporting and analysis is understanding what types of graphs to use -- and why. That's because choosing the wrong visual aid or simply defaulting to the most common type of data visualization could cause confusion with the viewer or lead to mistaken data interpretation.
To create charts that clarify and provide the right canvas for analysis, you should first understand the reasons why you might need a chart.
In this post, I'll cover five questions to ask yourself when choosing a chart for your data. Charts are perfect for comparing one or many value sets, and they can easily show the low and high values in the data sets. To create a comparison chart, use these types of graphs:. Use this type of chart to show how individual parts make up the whole of something, such as the device type used for mobile visitors to your website or total sales broken down by sales rep.
Distribution charts help you to understand outliers, the normal tendency, and the range of information in your values. If you want to know more information about how a data set performed during a specific time period, there are specific chart types that do extremely well.
Relationship charts are suited to showing how one variable relates to one or numerous different variables. You could use this to show how something positively effects, has no effect, or negatively effects another variable. Download this free data visualization guide to learn which graphs to use in your marketing, presentations, or project -- and how to use them effectively. To better understand each chart and how they can be used, here's an overview of each type of chart.
A column chart is used to show a comparison among different items, or it can show a comparison of items over time. You could use this format to see the revenue per landing page or customers by close date.
A bar graph, basically a horizontal column chart, should be used to avoid clutter when one data label is long or if you have more than 10 items to compare. This type of visualization can also be used to display negative numbers. A line graph reveals trends or progress over time and can be used to show many different categories of data. You should use it when you chart a continuous data set. A dual axis chart allows you to plot data using two y-axes and a shared x-axis.
Pie charts are best to use when you are trying to compare parts of a whole. They do not show changes over time. Bar graphs are used to compare things between different groups or to track changes over time. However, when trying to measure change over time, bar graphs are best when the changes are larger.
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