Table of Contents

guest
2018-12-11
     Visualizations
       Bar Charts
       Box Plots
       Line Plots
       Pie Charts
       Scatter Plots
       Time Charts
       Column Visualizations
       Quick Charts

Visualizations


Visualizations

You can visualize, analyze and display data using a range of plotting and reporting tools.

Plot Editor

When viewing a data grid, select (Charts) > Create Chart menu to open the plot editor and create new:

Column Visualizations

To generate a quick visualization on a given column in a dataset, select an option from the column header:

Open Saved Visualizations

Once created and saved, visualizations will be re-generated by re-running their associated scripts on live data. You can access saved visualizations either through the (Reports or Charts) pulldown menu on the associated data grid, or directly by clicking on the name in the Data Views web part.

Related Topics




Bar Charts


Create a Bar Chart

  • Navigate to the data grid you want to visualize.
  • Select (Charts) > Create Chart to open the editor. Click Bar (it is selected by default).
  • The columns eligible for charting from your current grid view are listed.
  • Select the column of data to use for separating the data into bars and drag it to the X Axis Categories box.
  • Only the X Axis Categories field is required to create a basic bar chart. By default, the height of the bar shows the count of rows matching each value in the chosen category. In this case the number of participants from each country.
  • To use a different metric for bar height, select another column (here "Lymphs") and drag it to the box for the Y Axis column. Notice that you can select the aggregate method to use. By default, SUM is selected and the label reads "Sum of Lymphs". Here we change to "Mean"; the Y Axis label will update automatically.
  • Click Apply.

Bar Chart Customizations

  • To remove the large number of "blank" values from your chart:
    • Click View Data.
    • Click the Country column header, then select Filter.
    • Click the checkbox for "Blank" to deselect it.
    • Click OK in the popup.
    • Click View Chart to return to the chart which is now missing the 'blank' bar.

To make a more complex grouped bar chart, we'll add data from another column.

  • Click Chart Type to reopen the creation dialog.
  • Drag a column to the Split Categories By selection box, here "Gender".
  • Click Apply to see grouped bars. The "Split" category is now shown along the X axis with a colored bar for each value in the "X Axis Categories" selection chosen earlier.
  • Further customize your visualization using the Chart Type and Chart Layout links in the upper right.
  • Chart Type reopens the creation dialog allowing you to:
    • Change the "X Axis Categories" column (hover and click the X to delete the current election).
    • Remove or change the Y Axis metric, the "Split Categories By" column, or the aggregation method.
    • You can also drag and drop columns between selection boxes to change how each is used.
    • Note that you can also click another chart type on the left to switch how you visualize the data with the same axes when practical.
    • Click Apply to update the chart with the selected changes.

Change Layout

  • Chart Layout offers the ability to change the look and feel of your chart.

There are 3 tabs:

    • General:
      • Provide a Title to show above your chart. By default, the dataset name is used; at any time you can return to this default by clicking the (refresh) icon for the field.
      • Provide a Subtitle to print under the chart title.
      • Specify the width and height.
      • You can also customize the opacity, line width, and line color for the bars.
      • Select one of three palettes for bar fill colors: Light, Dark, or Alternate. The array of colors is shown.
    • X-Axis/Y-Axis:
      • Change the display labels for the axis (notice this does not change which column provides the data).
      • The range applied to the Y-axis can also be specified - the default is automatic. Select manual and specify the range if desired.
  • Click Apply to update the chart with the selected changes.

Save and Export Charts

  • When your chart is ready, click Save.
  • Name the chart, enter a description (optional), and choose whether to make it viewable by others. You will also see the default thumbnail which has been auto-generated, and can choose whether to use it. As with other charts, you can later attach a custom thumbnail if desired.

Once you have created a bar chart, it will appear in the Data Browser and on the (charts) menu for the source dataset. You can manage metadata about it as described in Manage Data Views.

Export Chart

Hover over the chart to reveal export option buttons in the upper right corner:

Export your completed chart by clicking an option:

  • PDF: generate a PDF file.
  • PNG: create a PNG image.
  • Script: pop up a window displaying the JavaScript for the chart which you can then copy and paste into a wiki. See Tutorial: Visualizations in JavaScript for a tutorial on this feature.

Videos

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Box Plots


Create a Box Plot

  • Navigate to the data grid you want to visualize.
  • Select (Charts) > Create Chart to open the editor. Click Box.
  • The columns eligible for charting from your current grid view are listed.
  • Select the column to use on the Y axis and drag it to the Y Axis box.

Only the Y Axis field is required to create a basic single-box plot, but there are additional options.

  • Select another column (here "Study: Cohort") and choose how to use this column:
    • X Axis Categories: Create a plot with multiple boxes along the x-axis, one per value in the selected column.
    • Color: Display values in the plot with a different color for each column value. Useful when displaying all points or displaying outliers as points.
    • Shape: Change the shape of points based on the value in the selected column.
  • Here we make it the X-Axis Category and click Apply to see a box plot for each cohort.
  • Click View Data to see, filter, or export the underlying data.
  • Click View Chart to return. If you applied any filters, you would see them immediately reflected in the plot.

Box Plot Customizations

  • Customize your visualization using the Chart Type and Chart Layout links in the upper right.
  • Chart Type reopens the creation dialog allowing you to:
    • Change any column selection (hover and click the X to delete the current election). You can also drag and drop columns between selection boxes to change positions.
    • Add new columns, such as to group points by color or shape. Here we've chosen "Country" and "Gender", respectively.
    • Click Apply to see your changes and switch dialogs.
  • Chart Layout offers options to change the look of your chart, including these changes to make our color and shape distinctions clearer:
    • Set Show Points to All and
    • Check Jitter Points to spread the points out horizontally.
    • Click Apply to update the chart with the selected changes.
Here we see a plot with all data shown as points, jittered to spread them out colors vary by country and points are shaped based on gender. Notice the legend in the upper right. You may also notice that the outline of the overall box plot has not changed from the basic fill version shown above. This enhanced chart is giving additional information without losing the big picture of the basic plot.

Change Layout

  • Chart Layout offers the ability to change the look and feel of your chart.
  • There are 4 tabs:
    • General:
      • Provide a Title to show above your plot. By default, the dataset name is used, and you can return to this default at an time by clicking the refresh icon.
      • Provide a Subtitle to show below the title.
      • Specify the width and height.
      • Elect whether to display single points for all data, only for outliers, or not at all.
      • Check the box to jitter points.
      • You can also customize the colors, opacity, width and fill for points or lines.
    • X-Axis/Y-Axis:
      • Change the display labels for the axes (notice this does not change which columns provide the data).
      • For the Y-axis, choose log or linear scale, and if desired, apply a Range: the default is automatic. Select manual and specify the range.
    • Developer: Only available to users that are members of the "Site Developers" permission group.
      • Provide a JavaScript function that will be called when a data point in the chart is clicked.
  • Click Apply to update the chart with the selected changes.

Save and Export Plots

  • When your chart is ready, click Save.
  • Name the plot, enter a description (optional), and choose whether to make it viewable by others. You will also see the default thumbnail which has been auto-generated. You can elect None. As with other charts, you can later attach a custom thumbnail if desired.

Once you have created a box plot, it will appear in the Data Browser and on the (charts) menu for the source dataset. You can manage metadata about it as described in Manage Data Views.

Export Chart

Hover over the chart to reveal export option buttons in the upper right corner:

Export your completed chart by clicking an option:

  • PDF: generate a PDF file.
  • PNG: create a PNG image.
  • Script: pop up a window displaying the JavaScript for the chart which you can then copy and paste into a wiki. See Tutorial: Visualizations in JavaScript for a tutorial on this feature.

Rules Used to Render the Box Plot

The following rules are used to render the box plot. Hover over a box to see a pop-up.

  • Min/Max are the highest and lowest data points still within 1.5 of the interquartile range.
  • Q1 marks the lower quartile boundary.
  • Q2 marks the median.
  • Q3 marks the upper quartile boundary.
  • Values outside of the range are considered outliers and are rendered as dots by default. The options and grouping menus offer you control of whether and how single dots are shown.

Video

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Line Plots


Create a Line Plot

  • Navigate to the data grid you want to visualize. We will use the Lab Results dataset from the example study for this walkthrough.
  • Select (Charts) > Create Chart. Click Line.
  • The columns eligible for charting from your current grid view are listed.
  • Select the X Axis column by drag and drop, here "Date".
  • Select the Y Axis column by drag and drop, here "Lymphs".
  • Only the X and Y Axes are required to create a basic line plot. Other options will be explored below.
  • Click Apply to see the basic plot.

This basic line chart plots a point for every Lymph value measured for each date, as in a scatter plot, then draws a line between them. When all values for all participants are mixed, this data isn't necessarily useful; we might want to separate by participant to see if any patterns emerge for individuals.

Line Plot Customizations

Customize your visualization using the Chart Type and Chart Layout links in the upper right.

  • Chart Type reopens the creation dialog allowing you to:
    • Change the X or Y Axis column (hover and click the X to delete the current selection).
    • Select a Series column (optional). The series measure is used to split the data into one line per distinct value in the column.
    • Note that you can also click another chart type on the left to switch how you visualize the data with the same axes when practical.
  • For this walkthrough, drag "Participant ID" to the Series box.
  • Click Apply.

Now the plot draws series' lines between values for the same subject, but is unusably dense. Let's filter to a subset of interest.

  • Click View Data to see and filter the underlying data.
  • Click the ParticipantID column header and select Filter.
    • Click the "All" checkbox in the popup to unselect all values. Then, check the boxes for the first 6 participants, 101-606.
    • Click OK.
  • Click View Chart to return. Now there are 6 lines showing values for the 6 participants, clearly divided into upward and downward trending values.

This is a fairly small set of example data, but we can use the line plot tool to check a hypothesis about cohort correlation.

  • Click Chart Type to reopen the editor.
  • Drag "Study: Cohort" to the Series box. Notice it replaces the prior selection.
  • Click Apply.

Now the line plot shows a line series of all points for the participants in each cohort. Remember that this is a filtered subset of (fictional) participants, but in this case it appears there is a correlation. You could check against the broader dataset by returning to view the data and removing the filter.

Add a Second Y Axis

To plot more data, you can add a second Y axis and display it on the right.

  • Click Chart Type to reopen the editor.
  • Drag the "CD4+" column to the Y Axis box. Notice it becomes a second panel and does not replace the prior selection (Lymphs).
  • Click the (circle arrow) to set the Y Axis Side for this measure to be on the right.
  • Click Apply.
  • You can see the trend line for each measure for each cohort in a single plot.

Change Chart Layout

The Chart Layout button offers the ability to change the look and feel of your chart.

There are four tabs:

  • General:
    • Provide a title to display on the plot. The default is the name of the source data grid.
    • Provide a subtitle to display under the title.
    • Specify a width and height.
    • Control the point size and opacity, as well as choose the default color, if no "Series" column is set.
    • Control the line width.
    • Hide Data Points: Check this box to display a simple line instead of showing shaped points for each value.
    • Number of Charts: Select whether to show a single chart, or a chart per measure, when multiple measures are defined.
  • X-Axis/Y-Axis:
    • Change the display labels for the axis (notice this does not change which column provides the data).
    • Specify a manual range if desired.
  • Developer: Only available to users that are members of the "Site Developers" permission group.
    • Provide a JavaScript function that will be called when a data point in the chart is clicked.

Save and Export Plots

  • When your plot is finished, click Save.
  • Name the chart, enter a description (optional), and choose whether to make it viewable by others. You will also see the default thumbnail which has been auto-generated, and can choose whether to use it. As with other charts, you can later attach a custom thumbnail if desired.

Once you have saved a line plot, it will appear in the Data Browser and on the (charts) menu for the source dataset. You can manage metadata about it as described in Manage Data Views.

Export Chart

Hover over the chart to reveal export option buttons in the upper right corner:

Export your completed chart by clicking an option:

  • PDF: generate a PDF file.
  • PNG: create a PNG image.
  • Script: pop up a window displaying the JavaScript for the chart which you can then copy and paste into a wiki. See Tutorial: Visualizations in JavaScript for a tutorial on this feature.

Related Topics




Pie Charts


Create a Pie Chart

  • Navigate to the data grid you want to visualize.
  • Select (Charts) > Create Chart to open the editor. Click Pie.
  • The columns eligible for charting from your current grid view are listed.
  • Select the column to visualize and drag it to the Categories box.
  • Click Apply. The size of the pie wedges will reflect the count of rows for each unique value in the column selected.
  • Click View Data to see, filter, or export the underlying data.
  • Click View Chart to return. If you applied any filters, you would see them immediately reflected in the chart.

Pie Chart Customizations

  • Customize your visualization using the Chart Type and Chart Layout links in the upper right.
  • Chart Type reopens the creation dialog allowing you to:
    • Change the Categories column selection.
    • Note that you can also click another chart type on the left to switch how you visualize the data using the same selected columns when practical.
    • Click Apply to update the chart with the selected changes.

Change Layout

  • Chart Layout offers the ability to change the look and feel of your chart.
  • Customize any or all of the following options:
    • Provide a Title to show above your chart. By default, the dataset name is used.
    • Provide a Subtitle. By default, the categories column name is used. Note that changing this label does not change which column is used for wedge categories.
    • Specify the width and height.
    • Select a color palette. Options include Light, Dark, and Alternate. Mini squares showing the selected palette are displayed.
    • Customizing the radii of the pie chart allows you to size the graph and if desired, include a hollow center space.
    • Elect whether to show percentages within the wedges, the display color for them, and whether to hide those annotations when wedges are narrow. The default is to hide percentages when they are under 5%.
    • Use the Gradient % slider and color to create a shaded look.
  • Click Apply to update the chart with the selected changes.

Save and Export Charts

  • When your chart is ready, click Save.
  • Name the chart, enter a description (optional), and choose whether to make it viewable by others. You will also see the default thumbnail which has been auto-generated, and can choose whether to use it. As with other charts, you can later attach a custom thumbnail if desired.

Once you have created a pie chart, it will appear in the Data Browser and on the (charts) menu for the source dataset. You can manage metadata about it as described in Manage Data Views.

Export Chart

Hover over the chart to reveal export option buttons in the upper right corner:

Export your completed chart by clicking an option:

  • PDF: generate a PDF file.
  • PNG: create a PNG image.
  • Script: pop up a window displaying the JavaScript for the chart which you can then copy and paste into a wiki. See Tutorial: Visualizations in JavaScript for a tutorial on this feature.

Videos

Related Topics




Scatter Plots


Create a Scatter Plot

  • Navigate to the data grid you want to visualize.
  • Select (Charts) > Create Chart. Click Scatter.
  • The columns eligible for charting from your current grid view are listed.
  • Select the X Axis column by drag and drop.
  • Select the Y Axis column by drag and drop.
  • Only the X and Y Axes are required to create a basic scatter plot. Other options will be explored below.
  • Click Apply to see the basic plot.
  • Click View Data to see, filter, or export the underlying data.
  • Click View Chart to return. If you applied any filters, you would see them immediately reflected in the plot.
  • Customize your visualization using the Chart Type and Chart Layout links in the upper right.
  • Chart Type reopens the creation dialog allowing you to:
    • Change the X or Y Axis column (hover and click the X to delete the current selection).
    • Add a second Y Axis column (see below) to show more data.
    • Optionally select columns for grouping of points by color or shape.
    • Note that you can also click another chart type on the left to switch how you visualize the data with the same axes and color/shape groupings when practical.
    • Click Apply to update the chart with the selected changes.
  • Here we see the same scatter plot data, with colors varying by cohort and points shaped based on gender. Notice the key in the upper right.

Change Layout

The Chart Layout button offers the ability to change the look and feel of your chart.

There are four tabs:

  • General:
    • Provide a title to display on the plot. The default is the name of the source data grid.
    • Provide a subtitle to display under the title.
    • Specify a width and height.
    • Choose whether to jitter points.
    • Control the point size and opacity, as well as choose the default color palette. Options: Light (default), Dark, and Alternate. The array of colors is shown under the selection.
    • Number of Charts: Select either "One Chart" or "One Per Measure".
    • Group By Density: Select either "Always" or "When number of data points exceeds 10,000."
    • Grouped Data Shape: Choose either hexagons or squares.
    • Density Color Palette: Options are blue & white, heat (yellow/orange/red), or select a single color from the dropdown to show in graded levels. These palettes override the default color palette and other point options in the left column.
  • X-Axis/Y-Axis:
    • Change the display labels for the axis (notice this does not change which column provides the data).
    • Choose log or linear scale for the Y-axis, and specify a range if desired.
  • Developer: Only available to users that are members of the "Site Developers" permission group.
    • Provide a JavaScript function that will be called when a data point in the chart is clicked.

Add Second Y Axis

You can add more data to a scatter plot by selecting a second Y axis column. Reopen a chart for editing, click Chart Type, then drag another column to the Y Axis field. The two selected fields will both have panels. On each you can select the side for the Y Axis using the arrow icons.

For this example, we've removed the color and shape columns to make it easier to see the two axes in the plot. Click Apply.

If you use the Chart View > Number of Charts > One Per Measure, you will see two separate charts, still respecting the Y Axis sides you set.

Example: Heat Map

Displaying a scatter plot as a heatmap is done by changing the layout of a chart. Very large datasets are easier to interpret as heatmaps, grouped by density (also known as point binning).

  • Click Chart Layout and change Group By Density to "Always".
  • Select Heat as the Density Color Palette and leave the default Hexagon shape selected
  • Click Apply to update the chart with the selected changes. Shown here, the number of charts was reset to one, and only a single Y axis is included.
  • Notice that when binning is active, a warning message will appear reading: "The number of individual points exceeds XX. The data is now grouped by density which overrides some layout options." XX will be either 10,000 or 1, if you selected "Always" as we did. Click Dismiss to remove that message from the plot display.

Save and Export Plots

  • When your plot is finished, click Save.
  • Name the plot, enter a description (optional), and choose whether to make it viewable by others. You will also see the default thumbnail which has been auto-generated, and can choose whether to use it. As with other charts, you can later attach a custom thumbnail if desired.

Once you have saved a scatter plot, it will appear in the Data Browser and on the (charts) menu for the source dataset. You can manage metadata about it as described in Manage Data Views.

Export Plot

Hover over the chart to reveal export option buttons in the upper right corner:

Export your completed chart by clicking an option:

  • PDF: generate a PDF file.
  • PNG: create a PNG image.
  • Script: pop up a window displaying the JavaScript for the chart which you can then copy and paste into a wiki. See Tutorial: Visualizations in JavaScript for a tutorial on this feature.

Video

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Time Charts



Time charts provide rich time-based visualizations for datasets and are available in LabKey study folders. In a time chart, the X-axis shows a calculated time interval or visit series, while the Y-axis shows one or more numerical measures of your choice. With a time chart you can:
  • Individually select which study participants, cohorts, or groups appear in the chart.
  • Refine your chart by defining data dimensions and groupings.
  • Export an image of your chart to a PDF or PNG file.
  • Export your chart to Javascript (for developers only).
Note: Only properties defined as measures in the dataset definition can be plotted on time charts.

Note: In a visit-based study, visits are a way of measuring sequential data gathering. To create a time chart of visit based data, you must first create an explicit ordering of visits in your study. In a continuous study, there are no calculated intervals for measures used for generating time charts.

Create a Time Chart

Time charts are only available in study folders.

  • Navigate to the dataset, view, or query of interest. In this example, we use the Lab Results dataset in the example study.
  • Select (Charts) > Create Chart. Click Time.
  • Whether the X-axis is date based or visit-based is determined by the study type. For a date-based study:
    • Choose the Time Interval to plot: Days, Weeks, Months, Years.
    • Select the desired Interval Start Date from the pulldown menu. All eligible date fields are listed.
  • At the top of the right panel is a drop down from which you select the desired dataset or query. Time charts are only supported for datasets/queries in the "study" schema which include columns designated as 'measures' for plotting. Queries must also include both the 'ParticipantId' and 'ParticipantVisit' columns to be listed here.
  • The list of columns designated as measures available in the selected dataset or query is shown in the Columns panel. Drag the desired selection to the Y-Axis box.
    • By default the axis will be shown on the left; click the right arrow to switch sides.
  • Click Apply.
  • The time chart will be displayed.
  • Use the checkboxes in the Filters panel on the left:
    • Click a label to select only that participant.
    • Click a checkbox to add or remove that participant from the chart.
  • Click View Data to see the underlying data.
  • Click View Chart(s) to return.

Time Chart Customizations

  • Customize your visualization using the Chart Type and Chart Layout links in the upper right.
  • Chart Type reopens the creation dialog allowing you to:
    • Change the X Axis options for time interval and start date.
    • Change the Y Axis to plot a different measure, or plot multiple measures at once. Time charts are unique in allowing cross-query plotting. You can select measures from different datasets or queries within the same study to show on the same time chart.
      • Remove the existing selection by hovering and clicking the X. Replace with another measure.
      • Add a second measure by dragging another column from the list into the Y-Axis box.
      • For each measure you can specify whether to show the Y-axis for it on the left or right.
      • Open and close information panels about time chart measures by clicking on them.
    • Click Apply to update the chart with the selected changes.

Change Layout

  • Chart Layout offers the ability to change the look and feel of your chart.

There are at least 4 tabs:

  • On the General tab:
    • Provide a Title to show above your chart. By default, the dataset name is used.
    • Specify the width and height of the plot.
    • Use the slider to customize the Line Width.
    • Check the boxes if you want to either Hide Trend Line or Hide Data Points to get the appearance you prefer. When you check either box, the other option becomes unavailable.
    • Number of Charts: Choose whether to show all data on one chart, or separate by group, or by measure.
    • Subject Selection: By default, you select participants from the filter panel. Select Participant Groups to enable charting of data by groups and cohorts using the same checkbox filter panel. Choose at least one charting option for groups:
      • Show Individual Lines: show plot lines for individual participant members of the selected groups.
      • Show Mean: plot the mean value for each participant group selected. Use the pull down to select whether to include range bars when showing mean. Options are: "None, Std Dev, or Std Err".
  • On the X-Axis tab:
    • Customize the Label shown on the X-axis. Note that changing this text will not change the interval or range plotted. Use the Chart Type settings to change what is plotted.
    • Specify a range of X values to plot, or use the default automatic setting.
  • There will be one Y-Axis tab for each side of the plot if you have elected to use both the left and right Y-axes. For each side:
    • Customize the Label shown on that Y-axis. Note that changing this text will not change the measure or range plotted.
    • Select whether to use a linear or log scale on this axis.
    • Range: Specify a range of values or use the default automatic setting.
    • For each Measure using that Y-axis:
      • Choose an Interval End Date. The pulldown menu includes eligible date columns from the source dataset or query.
      • Choose a column if you want to Divide Data Into Series by another measure.
      • When dividing data into series, choose how to display duplicate values (AVG, COUNT, MAX, MIN, or SUM).
  • On the Developer tab, users with developer access can provide a JavaScript function that will be called when a data point in the chart is clicked.
  • Click Apply to update the chart with the selected changes. In this example, we now plot data by participant group. Note that the filter panel now allows you to plot trends for cohorts and other groups. This example shows a plot combining trends for two measures, lymphs and viral load, for two study cohorts.

Save Chart

  • When your chart is ready, click Save.
  • Name the chart, enter a description (optional), and choose whether to make it viewable by others. You will also see the default thumbnail which has been auto-generated, and can choose whether to use it. As with other charts, you can later attach a custom thumbnail if desired.
  • Click Save.

Once you have created a time chart, it will appear in the Data Browser and on the charts menu for the source dataset.

Data Dimensions

By adding dimensions for a selected measure, you can further refine the timechart. You can group data for a measure on any column in your dataset that is defined as a "data dimension". To define a column as a data dimension:

  • Open a grid view of the dataset of interest.
  • Click Manage.
  • Click Edit Definition.
  • In the Dataset Fields section, select a column.
  • Select the Reporting tab.
  • Place a checkmark next to Data Dimension.
  • Click Save.

To use the data dimension in a time chart:

  • Click View Data to return to your grid view.
  • Create a new time chart, or select one from the (Charts) menu and click Edit.
  • Click Chart Layout.
  • Select the Y-Axis tab for the side of the plot you are interested in (if both are present.
    • The pulldown menu for Divide Data Into Series By will include the dimensions you have defined.
  • Select how you would like duplicate values displayed. Options: Average, Count, Max, Min, Sum.
  • Click Apply.
  • A new section appears in the filters panel where you can select specific values of the new data dimension to further refine your chart.

Export Chart

Hover over the chart to reveal export option buttons in the upper right corner:

Export your completed chart by clicking an option:

  • PDF: generate a PDF file.
  • PNG: create a PNG image.
  • Script: pop up a window displaying the JavaScript for the chart which you can then copy and paste into a wiki. See Tutorial: Visualizations in JavaScript for a tutorial on this feature.

Related Topics




Column Visualizations


Click a column header to see a list of Column Visualizations, small plots and charts that apply to a single column. When selected, the visualization is added to the top of the data grid. Several can be added at a time.
  • Bar Chart - Histogram displayed above the grid.
  • Box & Whisker - Distribution box displayed above the grid.
  • Pie Chart - Pie chart displayed above the grid.

Visualizations will be updated to reflect updates to the underlying data and any filters added to the data grid.

Column Visualizations are persisted within a saved custom view. When you come back to the saved view, the Column Visualizations will appear again.

To remove a chart, hover over the chart and click the 'X' in the upper right corner.

Available visualization types are determined by datatype as well as whether the column is a Measure and/or a Dimension.

  • The box plot option is shown for any column marked as a Measure.
  • The bar and pie chart options are shown for any column marked as a Dimension.
Column visualizations are simplified versions of standalone charts of the same types. Click any chart to open it within the plot editor which allows you to make many additional customizations and save it as a new standalone chart.

Bar Chart

A histogram of the Weight column.

Box and Whisker Plot

A basic box plot report. You can include several column visualizations above a grid simultaneously.

Pie Chart

A pie chart showing prevalence of ARV Regimen types.

Filters are also applied to the visualizations displayed. If you filter to exclude 'blank' ARV treatment types, the pie chart will update.

Related Topics




Quick Charts


Quick Charts provide a quick way to assess your data without deciding first what type of visualization you will use.

Create a Quick Chart

  • Navigate to a data grid you wish to visualize.
  • Click a column header and select Quick Chart. Depending on the content of the column, LabKey Server makes a best guess at the type and arrangement of chart to use as a starting place. A numeric column in a cohort study, for example, might be quickly charted as a box and whisker plot using cohorts as categories.
  • You can then alter and refine the chart in the following ways:
    • View Data: Toggle to the data grid, potentially to apply filters to the underlying data. Filters are reflected in the plot upon re-rendering.
    • Export: Export the chart as a PDF, PNG, or Script.
    • Help: Documentation links.
    • Chart Type: Click to open the plot editor. You can change the plot type to any of the following and the options for chart layout settings will update accordingly
    • Chart Layout: Click to customize the look and feel of your chart; options available vary based on the chart type. See individual chart type pages for a descriptions of options.
    • Save: Click to open the save dialog.

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