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Generate data visualizations

Generate data visualizations

 


The Phenotypic Data Manager can also generate data visualizations per collected trait of an occurrence. To differentiate these diagrams, here are their definitions:

  • Box plots - displays the spread of each plot trait data, showing the minimum, the first quartile, the median, the third quartile, and the maximum values

  • Histogram - displays the frequency distribution of each plot trait data, showing the range of values

  • Scatter plots - display the relationship between two trait data

  • Heatmap - displays the color-coded relationship of trait data on all plots

Traits whose data are all or have a mix of questionable, suppressed, bad, and missing will not appear in the trait list options.

Let’s start!

 

Generate box plots

  1. From the data browser, click the Box Plot tab.

image-20240423-065819.png

 

  1. Click the trait(s) that you want to use for generating box plot(s). After that, click Generate. Your box plots are now displayed in your browser.

Boxplot generate.gif

 

  1. You may also view the box plot information by hovering your cursor on the box plot points.

Boxplot hovering.gif

 

  1. To clear all the generated box plots, click Clear.

image-20240423-065713.png

 

Suppress box plot values

You can also suppress the trait data values in your box plots by inputting range values.

  1. Select the trait to be suppressed from the lower left corner under the Traits dropdown,

image-20240716-010501.png

 

  1. Write down the trait upper bound and the trait lower bound at the provided text area. Possible outliers greater than or equal to the Trait Upper Bond will be suppressed. On the other hand, outliers less than or equal to the Trait Lower Bond will be suppressed.

image-20240716-010628.png

 

  1. After that, from the bottom left click Suppress button.

image-20240716-011008.png

 

  1. A pop-up window will appear with the number of outliers suppressed. The box plot will be regenerated with the outliers removed.

image-20240716-011047.png

 

The suppressed data values from the box plots will also be reflected in the trait table.

image-20240716-012607.png

 

Generate histogram

  1. From the data browser, click the Histogram tab.

image-20240423-065352.png

 

  1. Click the trait(s) that you want to use for generating histogram(s). After that, click Generate. Your histograms are now displayed in your browser.

Generate histogram.gif

 

  1. You may also adjust the display of your histograms by navigating the tools above. Click on the dropdown menu for the list of tools.

Download plot as a PNG - saves the histogram to the device in a PNG format

Download histogram.gif

 

Zoom - zooms into a specific area of the histogram. Drag-select the area to zoom in; double-click to zoom out

zoom in to histogram.gif

 

Pan - moves the histogram by dragging the area

Pan on histogram.gif

 

Box select - draws a box selection on an area of the histogram and selects it

Boxselect.gif

 

Lasso select - draws a polygonal selection on an area of the histogram and selects it

Lasso effect.gif

 

Zoom in - increases the scale of the histogram.

Zoom in.gif

 

Zoom out - decreases the scale of the box plot

Zoom out.gif

 

Autoscale - sets to the histogram’s default size

autoscale histogram.gif

 

Reset axes - resets the histogram back to its original place

Reset grid histogram.gif

 

  1. To clear all the generated histograms, click Clear.

image-20240423-065503.png

 

Generate scatter plots

  1. From the data browser, click the Scatter Plot tab.

image-20240423-064534.png

 

  1. Click two or more traits that you want to use for generating scatter plot(s). After that, click Generate. Your scatter plots are now displayed in your browser.

 

  1. You may also adjust the display of your scatter plots by navigating the tools above. Click on the dropdown menu for the list of tools.

Download plot as a PNG - saves the scatter plots to the device in a PNG format

scatter plot.gif

 

Zoom - zooms into a specific area of the scatter plot. Drag-select the area to zoom in; double-click to zoom out

Pan - moves the scatter plot by dragging the area

Pan scatter.gif

 

Box select - draws a box selection on an area of the scatter plot and selects it

Box select scatter.gif

 

Zoom in - increases the scale of the scatter plot

Zoom scatter.gif

 

Zoom out - decreases the scale of the scatter plot

Zoom out scatter.gif

 

Autoscale - sets to the scatter plot’s default size

Autoscale scatter.gif

 

Reset axes - resets the scatter plot back to its original place

Reset axes scatter.gif

 

  1. To clear all the generated scatter plots, click Clear.

image-20240423-064715.png

 

Generate heatmaps

  1. From the data browser, click the Heatmap tab.

image-20240423-082238.png

 

  1. Select the data type that you want to use for viewing heat map(s). You may choose between trait, block, rep, entry, and entry type. The heatmap will automatically generate.

Heatmap colour by entry.gif

The block option will not appear in the dropdown menu if the occurrence has no block number.

 

  1. If you choose trait, the dropdown menu will list the trait(s) you can select. After that, click Generate.

Missing, bad, or suppressed values are highlighted in gray.

heatmaps by traits.gif

 

  1. You may also adjust the display of your heatmap by navigating the tools above. Click on the dropdown menu for the list of tools.

Download plot as a PNG - saves the heatmap to the device in a PNG format

heatmap download.gif

 

Zoom - zooms into a specific area of the heatmap. Drag-select the area to zoom in; double-click to zoom out

Zoom in to heatmap.gif

 

Pan - moves the heatmap by dragging the area

pan heatmap.gif

 

Zoom in - increases the scale of the heatmap

Zoom in scale heatmap.gif

 

Zoom out - decreases the scale of the heatmap

Zoom out scale.gif

 

Autoscale - sets to the heatmap’s default size

Autoscale heatmap.gif

 

Reset axes - resets the heatmap back to its original place

Reset grid heatmap.gif

 

  1. To clear all the generated heatmaps, click Clear.

image-20240429-060618.png

Great job! You have generated data visualizations for your collected plot trait data. Once done checking the data, you may send them for analysis in the Analysis Request Manager tool.