Alternative ways to create Charts in a View

Last Updated on:
July 12, 2022

Predefined Views by your Admin can not be edited. Only Views from the My Views section can be edited. However, Predefined Views can be cloned and then edited. To clone a View, check this link.

12.1 Scatter

1. Click on the “+” sign next to the Data tab. Dropdown with various options will open. Choose Scatter”.

2. Double click on “Scatter 2” to rename the chart. Click on “Scatter” and the Chart Settings window will open. Select the data to be shown on X and Y-axis. Click on “Add Series” to put additional data on the Y-axis. Under “More Options” additional functionalities appear. 

3. When “More options” is selected, you can choose to show the Regression Line and select its type. 

4. Another additional option is to split data. Select “Split by” and from the drop down menu choose the variable by which the data will be splitted. 

5. For each series of data check “Show Regression Line”, choose shape, color and size of the data points, as well as the line type. 

6. Click on “More Options” and additional Chart Settings will be available.

7. Enter labels for X and Y axis, choose type (Linear or Logarithmic) and define minimum and maximum values.

12.2 Bar

1. Click on the “+” sign next to the Data tab. Dropdown with various options will open. Choose Bar.

2. Double click on “Bar 2” to rename the chart. Select the data to be shown on X and Y-axis. 

3. Check the “Aggregate” box to aggregate the data in the bar chart. Click on the arrow inside the Aggregation field to choose the function according to which the data will be aggregated.

4. Click on “Add Series” to put additional data on the bar chart. 

5. Series will be shown in different colors. Legend of colors is displayed below the chart. Click on the color legend to omit the specific series from the chart and click again to include it. Click on “3 dots” to remove the unwanted series of data. Click on “More Options” to open additional chart settings.

6. Click on the arrow inside the field to choose chart orientation (Horizontal or Vertical). Click on the checkbox to include bar values on the chart. For X and Y-axis manually enter the axis labels.

7. Click on the arrow inside the color field to change the color for each series of data.

8. Create a stacked bar chart to show different numeric values across multiple data categories. Each bar is divided to the sub-segments, which are stacked together, thus the total value of each category is split into parts. Click on the arrow inside the field to choose among Standard and 100% Stacking. 

12.3 Boxplot

1. Click on the “+” sign next to the Data tab. Dropdown with various options will open. Choose “Boxplot”. Boxplot shows the distribution of numerical data and skewness through displaying the data quartiles.

2. Double click on the header of the created chart to rename it. Click on the arrow to choose the data that will be displayed in Boxplot. Click on “Add Series” to add more series of data.

3. More series will be shown in another boxplot below. Click on “3 dots” next to the Series label to remove the undesired series from the plot.

4. Hover over the area to see the data distribution per quartiles (Q1, Q2, Q3, Q4).

5. Dots that are not included in the plot are representing outliers. Hover over dots to check their values.

12.4 Heatmap

1. Click on the “+” sign next to the Data tab. Dropdown with various options will open. Choose “Heatmap”. Heatmap is a two-dimensional representation of data, where rows and columns are denoting different sets of data. Heatmap is used to correlate a series of data in the View.

2. Double click on the header of the created chart to rename it. Click on the arrow inside the Data field to choose the data which will be displayed in the Heatmap for Series 1.

3. Click on “Add Series” to add data for correlation. Click on “3 dots” to remove the undesired series of data from the Heatmap.

4. Click on the arrow inside the field to choose the data for each series. When record reference field is added, select the “Transform Field” variable and the field value by which the data will be grouped.

5. The legend is placed on the right side of the Heatmap. Correlation coefficients equal to 1 indicate direct positive correlation, while -1 is indicating strong negative correlation. If there is no correlation between the variables the correlation coefficient will be 0. Empty fields indicate missing data.