In power bi, we have many types of visualization techniques and the most important and extensively used one of them is charts, charts are basically used in every report or dashboard to display data to a user, we have inbuilt charts in power bi to use but we can also make combo charts or custom made charts.
Chart Visuals in Power BI
While creating Power BI dashboard chart visuals are the most eye-catching things. Charts are better suited for any dashboard with numerical data sets but knowing about the in and out of the chart is necessary to create the right kind of chart type for the data sets. It is important to know that not all the charts fit into all kinds of data sets, so you need to be choosy while building charts. In this article, we will introduce you to various types of charts in Power BI.
Top 9 Types of Charts Visualization in Power BI
When you look at the visualization gallery of Power BI you will see plenty of visual types and in this article, we will concentrate only on chart visuals.
Copy and paste the data directly to Power BI or you can copy the data to excel file and then import to Power BI as Excel file reference. So you can download the excel workbook template from the below link which is used for this example.
#1 – Clustered Bar Chart
First chart visualization you have in Power BI is Bar Chart. These are horizontal bar charts that show the graphical representation of the selected category data points. Bar charts are used to show the number of units sold, the sale value of different categories, etc…
To create a Clustered bar chart select the “Clustered bar chart” and drag the required data in the Value field as shown below.
The below Clustered bar chart shows the “Category-wise” number of units sold data.
#2 – Clustered Column Chart
This is the opposite way of the above chart, this power bi chart type shows the bars vertically whereas “Clustered Bar Charts” shows the bars horizontally.
To show a Clustered Column chart select the “Clustered Column chart” and drag the required data in the Value field as shown below.
Below chart shows quarterly Sale Value and Cost Value.
#3 – Combo Chart
The combo chart is nothing but the combination of two charts typically “Combination of Column & Line Chart” to show different data points where we can compare one data point against the other data point.
For example, if you want to compare monthly Sales Value vs Cost Value then we can use this combo chart to plot our data points.
To make a Combo chart select the “Line and Stacked Column Chart” and drag the required data in the Value field as shown below.
Below chart shows the “Category-wise Sales Value vs Cost Value”.
From this chart, we easily identify in which category cost is incurring more even though sales are on the higher side.
#4 – Area Chart
An area chart in excel is an advanced line chart where the area between each data different line items filled with color, pattern, or texture. An area chart is used to show what is the gap between one data point to another data point and make some decisions in terms of whether the sale is increased over a period of time or not.
Choose “Area Chart” from visualizations to create an area chart and drag the required data in the Value field as shown below.
The below chart shows the area between sales value, cost value, and the number of units sold for each category.
#5 – Line Chart
An area chart is filled with some color or texture between one data point to another data points but the line chart comes with no fill color or texture.
The below image shows the difference between the Area chart and Line Chart.
#6 – Pie Chart
We all know this chart in excel, in Power BI too it works similarly. Power BI Pie Chart shows the portion of each category against the overall value.
To create a Pie chart select the “Pie Chart” and drag the required data in the Value field as shown below.
The below chart shows the “Buyer-wise” total unit’s data point in Pie Chart.
By looking at this Pie Chart we can identify that “Bruce Curran, Chris Monroe, and Richard Carr” are the buyers who bought a large number of units.
#7 – Doughnut Chart
Doughnut chart is the kind of pie chart but named as “Donut” because they look like “DOUGHNUT”. Pie Chart shows the full portion where the inner circle is fully occupied but Doughnut chart inner circle will not be occupied.
Below two charts show the difference between the Pie Chart and Doughnut Chart.
However, in the doughnut chart, we can play with the inner circle radius under the format section of the chart.
#8 – Funnel Chart
This funnel chart is typically used when the data points are from largest to smallest.
To create a Funnel chart select the “Funnel Chart” and drag the required data in the Value field as shown below.
Below Funnel chart shows the sales value on buyer-wise.
As you can see above we have the highest value at the top, second highest below that and so on.
#9 – Gauge Chart
Gauge Chart one of the KPI charts to show actual performance against the set targeted value. This chart requires “Target Value” to be given to gauge the actual value against it.
Below chart shows the Actual value of 85 vs Targeted value of 100.
Formatting of Power BI Charts
Every chart will be created by default settings but we can play around with these settings under format section of each chart. Once the chart is selected we can see its field’s area to the right side next to its field’s area we can see the format option.
As you can see above we have a wide variety of formatting options for each chart. We can play with these settings and apply custom touch to the charts.
Note: Power BI dashboard file can also be downloaded from the link below and the final output can be viewed.
Things to Remember
- Apart from built-in charts, we can also download custom charts from the market place.
- You need to identify what is the best fit chart for your data set.
- Use the formatting section to play with the settings of the chart.
Guide to Power BI Charts. Here we discuss the top 9 types of chart visualization present in Power BI along with the step by step examples. You may learn more about Power BI from the following examples –