Decoding Data Distribution – Box Plots for Insightful Qlik Sense Visualizations

A box plot, also known as a box-and-whisker plot, is a graphical representation of a set of data that shows the distribution of the data and highlights any outliers. It consists of a box with a line drawn through the middle (the median), as well as “whiskers” that extend from the box to show the range of the data.

In Qlik Sense, box plots are available as a visualization type in the chart options. To draw a box plot in Qlik Sense, follow these steps:

1. Open the Qlik Sense app and navigate to the sheet where you want to add the box plot.
2. From the toolbar, select the “New Object” button.
3. In the “Add Object” window, select the “Chart” option.
4. From the chart options, choose the “Box Plot” chart type.
5. Drag and drop the desired measure and dimension fields onto the “Measures” and “Dimensions” boxes.
6. Customize the chart by selecting the “Properties” tab and adjusting the various options available, such as the appearance of the box plot and the labels.
7. Once you have finished configuring the chart, click the “Apply and Close” button to add the chart to the sheet.

It’s also possible to create a box plot using the Qlik Sense extension library. Extensions are custom visualizations that can be added to Qlik Sense to provide additional chart types or other functionality. To use an extension to create a box plot, you will need to install the extension and then follow the extension’s specific instructions for creating and customizing the chart.

Box plots, also known as box-and-whisker diagrams, are a type of chart used to display the distribution of numerical data. In Qlik Sense, you can create box plots to help you understand the distribution of your data and identify outliers.

To create a box plot in Qlik Sense, follow these steps:

1. Load the data into Qlik Sense
2. Create a new box plot visualization
3. Drag the numerical field you want to display to the expression area
4. Optionally, add a second dimension to the chart to split the data into categories

In a box plot, the box represents the middle 50% of the data, while the whiskers represent the upper and lower quartiles. Outliers are represented by individual dots outside the whiskers.

Box plots are useful for identifying the distribution of data and understanding the spread of the data, and they are especially useful for identifying outliers and skewness in the data. When used in conjunction with other types of charts, box plots can provide a comprehensive view of the distribution of your data and help you make informed decisions.