Different Analytical Lines in Power BI

Hi everyone, in this blog we are going to learn about different types of Analytical lines in PowerBI. Let’s get started.  

 
We have a data which talks about Sales of Various different products. You shall see a glimpse of it down below: 

Our objective is to explore various types of Analytical lines.  

 
Step1: Add a line chart with required data on X and Y axis. 

Step2: Go to Analytical Pane present for the line visual chart. 

You shall see possibly many different options there:  
Graphical user interface, chart, application

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Step 3: Turn on the required analytical line and add value there. 
I have created 2 visuals:  
For Visual1 – I have taken Category and sales amount 
For Visual2 – I have taken Sales amount and Date(Year)  
Note: Your Analytical line options vary with your Data Points. 

Visual1 is shown below: 

For all the analytical lines – I have taken sales as my value. 

Min line – Shows Min Sales 

Max Line – Shows Max Sales 

Median Line – Shows the Sales Mid data point 

Average Line – Shows the Mean or Average Sales Value 

Percentile Line – I have taken 40 Percentile there, you can choose whatever percentile value you require. 

Visual2 is shown Below: 

Trend Line – Shows the Positive and Negative direction – Here the line in red is directed towards lower sales in comparison to initial data point.  

X Axis Constant line – It will show the constant point for data on X axis – We have Year here. As you can see the value below, it clearly has exact date. Dotted blue line is nothing but the data point on that date. 

Y Axis Constant line – It works similarly to line above the only difference is of Axis. Here it will show the Horizontal line for the data point. 

Last but not the least is Forecast line – The shaded area you see in the visual2 is the Outcome of Forecast line – Here the forecast is done for next 2 years. You can see upper and lower bound in the tooltip for the shade areas. 

Hope you have explored the following analytical lines from this article. Thank you for reading.  

Dhiraj Kala 
Data Analyst 
Addend Analytics

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