In Lightdash, the data in your results tables can be visualized in a bunch of different ways: The visualization type that you pick determines how Lightdash shows the data series in your chart. To change how your data is displayed, click Configure when you’re querying from a table. You have the option to change the chart type in the drop-down:

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Chart types and options

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Bar chart

Bar charts are helpful to:
  • compare things between different groups (e.g. the number of orders you have by product type)
  • track how a number changes over time if you have a smaller number of x-axis values (e.g. number of new users per month over a year).
Check out more details about bar chart configurations here.

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Stacked bar chart

You can also stack bar charts to compare proportions across different groups. Stacked bar charts work best when:
  • the focus of the chart is to compare the totals and one part of the totals. It’s hard to compare bars if they don’t start at the same baseline. So, if you’re trying to build a chart to compare multiple parts of your total with each other, consider keeping your bar chart unstacked!
  • you’re trying to show the parts of multiple totals. If you only want to show parts of one total, consider an unstacked bar chart instead. If you only want to communicate one part of one total, consider if you should be using a big value chart instead.

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100% Stacked Bar Chart

You can create a 100% stacked bar chart by setting up a table calculation for percent of group total. Use your x-axis dimension as the column_i_want_to_group_by, then in your chart configuration choose your x-axis, group dimension, and the new table calculation as your y-axis. 100% Stacked Bar Charts are useful when you need to visualize how the composition of a metric changes over time, or how the composition changes across different groups.

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Horizontal bar chart

Horizontal bar charts are just bar charts, except the columns are placed on the chart horizontally instead of vertically. Horizontal bar charts are useful when:
  • you’re trying to group a number by something with a lot of possible values.
  • your groups have really long label names.
You can see more details about horizontal bar chart configurations here.

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Line chart

Line charts are used to show changes in a number over a short or long period of time. They’re a good option when:
  • you have small changes between your values. The y-axis of a line chart doesn’t need to start at zero. This means that your y-axis can be stretched to show the tiny differences.
  • you have lots of x-axis values. In this case, line charts are better to use than bar charts.
Line charts with multiple lines can also be used to compare changes over the same period of time for more than one group.
You can see more details about line chart configurations here.

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Area chart

Area charts are best if:
  • you want to show how values develop over time. If you want to show how values differ in different categories, consider a (stacked) bar, or horizontal bar chart instead.
  • the total is as important as its parts. If the total (= the height of all your stacked areas) is not important, consider a line chart instead. Many readers will have an easier time understanding a line chart than an area chart.
  • there are big differences between your values. If the differences between your values are very small, consider a line chart instead. Compared to an area chart, the y-axis of a line chart doesn’t need to start at zero. This means that your y-axis can be stretched to show the tiny differences.
  • you’re showing multiple series over time. If you just want to show one value over time, also consider a line chart instead; especially if you don’t want your y-axis to start at zero. If you only have a few dates, you can also consider using a column chart. In both cases, labelling will be better.
  • you have many data points. If you have less than ten or so data points, consider a stacked bar chart instead.
You can see more details about line chart configurations here.

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Mixed chart

You can combine bars, line, and scatter charts on the same chart using a Mixed chart. To use a Mixed chart, you’ll need to start with either a line, scatter or horizontal bar chart type and have two or more series on your chart. Either from having two or more fields selected for your y-axis or from having a group with two or more groups. Once you have the series you want on your chart, you can pick and choose the different chart types you’d like for each series in the series tab of the Configure space.
You can see more details about mixed chart configurations here.

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Scatter chart

A scatter chart is useful if you want to to look at the relationship, a.k.a. correlation, between two variables. Something like the age of your users vs. the amount of time they’ve spent on your website. You can group your scatter chart using a third variable. This will make the points on the scatter the same colour if they have the same group value.
You can see more details about scatter chart configurations here.

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Pie chart

Pie charts can be useful to visualize data that adds up to a meaningful “whole”. For example, the split of total revenue across each of our product lines. To use a pie chart, you need at least one metric and one dimension in your query results. You can add multiple dimensions to create more granular groups in your pie charts. By default, pie charts are shown in a donut shape (i.e. with the center removed) but you can easily toggle the donut toggle to switch between a traditional pie and donut chart.

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Funnel chart

Funnel charts work well for showing pipeline performance, product conversion metrics, onboarding flows, or any other process where things move from one discrete stage to another. To use a funnel chart, you should have discrete stages of a process and numeric counts of entities in each stage. The funnel will show the count at each stage and the percentage that number represents of the starting count, making it easy to visualize the proportion moving from one stage to the next. General settings
With the Lightdash funnel chart, you can use either a row or a column to describe the stages in your funnel. Use the Data orientation switch to specify which orientation you would like to use. When rows is selected, each row of your data represent one step. The first column in the data will be treated as the labels for the steps, and you can choose which numeric column to treat as the value of the step. When columns is selected, you should have a numeric column for each step you want to display. Only the first row of data will be represented and the column names will be used as the step labels. Non-numeric columns will be ignored.

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Treemap chart

Treemaps show parts of a whole using nested rectangles. Each rectangle’s size represents the value of a metric, and dimensions define how the data is grouped and nested. You can use a single dimension or multiple and they will work as described below. One dimension: Each category becomes a rectangle, sized by the metric value.
Two dimensions: Creates a hierarchy where each rectangle is split into sub-rectangles based on the second dimension.
Three or more dimensions: The chart displays the top-level hierarchy. Users can click to drill down into deeper layers.
Treemaps are useful when:
  • You want to compare proportions across categories
  • You’re visualizing hierarchical data
  • Space is limited and you want a compact alternative to bar or pie charts
To create a treemap, select Treemap as the chart type and choose your dimensions. Layout
  • Dimension hierarchy tells Lightdash how to group or nest the dimensions.
  • Size metric determines how large each section of the treemap chart is.
  • Color metric allows you to set a color scale for Highlighting each section of the treemap.
Display
  • Minimum section size determines when to start hiding sections, anything smaller than this size can be shown by zooming in.
  • Max leaf depth allows you to choose when a user needs to start drilling into sections to see the next tier, default value is 2.

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Table

The Table option is good for looking at (surprise, surprise) tabular data, or for lists of things like user IDs or transactions. The options for Tables include:
  • Renaming the columns in your table.
  • Showing and hiding the columns in your table.
  • Showing and hiding the table name from the column labels.
  • Showing and hiding the totals for your columns.
  • Pivoting by a column.
  • Transposing your table (a.k.a. pivoting your metrics)
  • Locking a column from scrolling in your table.
  • Adding conditional formatting to your cells.
By default, we attach the table name to your field name (just in case you’ve got any duplicate fields from joined tables). But, you can easily turn this off in your table viz with a toggle. Columns, Rows, and Metrics Table visualizations have three components:
  • Rows: When a field is chosen for the row area, all of the unique values for that field are populated as values in the rows of your table.
  • Columns: When a field is chosen for the column area, all of the unique values for that field are populated as values in the columns of your table.
  • Metrics: If you have metrics in your table, then each metric cell shows the summarized information for a given row + column combination.

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Pivot tables

Pivot tables allow you to summarize larger sets of data in table visualizations by moving row values into columns. They’re also helpful to identify trends between two dimensions in your data using a table visualization. To add a pivot in your table, move a dimension to the column section of your table configuration. This will change the dimension from having its values populate the rows values of your table, to having it populate the column values of your table.
You can move up to 3 dimensions as columns and there is a limit of 60 column values in your table (e.g. pivoting by a dimension with 30 months, and another with 4 statuses won’t work because that will generate 4 x 30 = 120 column values). Transposing your table You can transpose your table so that your metrics become rows in your table instead of columns. This can be helpful if you want to compare a lot of metrics to each other (e.g. how my metrics are changing over time). To move your metrics to rows in your table, you need to have at least 1 dimension as a column (i.e. at least one pivot) then, you can click on show metrics as rows in the table configuration.

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Totals

You can add column totals or row totals (in pivot tables) to your tables by selecting Show column totals or Show row totals in the chart configuration panel. The column totals in your results and table visualizations are calculated using the underlying data from your table, not only the values that are visible in the table.
Totals are not calculated for table calculations. Also, in pivot tables, totals are only shown for count and sum metric types.

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Incorrect totals

Why are my totals lower? When using the count_distinct metric type, you can sometimes get totals that are smaller than if you sum up the values seen in the table. For example, if you count the distinct number of devices that viewed pages on our website each month, it would look something like this:
If you manually add each row in the Anonymous device count column, the value you get is much higher than the total shown in the table. This is because the same device can view pages on our website across many months. So, when you add up the values in the table, you’ll be counting some devices more than once. Lightdash uses a SQL query to calculate the distinct number of devices across all of the months so we avoid double-counting devices. Why are my totals higher? There are two reasons why this could be happening:
  1. You’ve set a row limit in your query that’s truncating the results. If the number of possible results from your query is larger than the row limit you’ve set, Lightdash will calculate the totals using all of the results (including the rows that have been removed from your table because of the limit).
  2. You’re using metric or table calculation filters. When you use metric or table calculation filters, the totals are calculated before the filters are applied.
How do I calculate totals based on what’s shown in my table? If you want to calculate totals based on just the values shown in your table, you can create a new column using a table calculation to do this. Here’s the table calculation you’ll need to use to do this: 
SUM(${my_table_name.my_metric_name}) OVER()
This calculation isn’t a “true” total when you’re using metrics types that are count_distinct!

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Subtotals

You can add subtotals to your tables by selecting Show subtotals in the chart configuration panel.
To use subtotals, you need to have at least 2 or more dimensions in your table visualization.

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Freeze columns

If you have a wide table, you may want some columns to be locked to the left while you’re scrolling. Click on the lock icon beside the column(s) you want to keep pinned to the left of your table visualization to lock them in place.

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Conditional formatting

Sometimes it’s helpful to highlight certain values in your tables when they meet a specific condition. You can set up conditional formatting rules by going to the Configure tab, then Conditional Formatting.
Highlighting cells
When you add a new rule, you’ll first need to pick which column should be highlighted and the type of rule you’d like to apply (Single or Range). There are three ways to compare data for each role:
  1. Values compares the chosen field to manual input values.
  • For example, color the Profit column red when a row is less than $10,000
  1. Field compares the chosen field to another field in your results.
  • For example, color the Revenue column green when it is greater than the Target revenue column.
  1. Field values compares another field in your results to manual input values, then formats your chosen field.
  • For example, color the Partner name column orange when the Total orders column is greater than 1,000.
You can set as many rules on a table as you want. If two or more rules disagree with each other, the rule that’s on the bottom of your list of rules will win.
Color ranges
To use color ranges for your rules, select Range under Conditional Formatting. You can choose specific minimum and maximum values, or you can automatically set them based on the values in your results. The color range will use a set of 5 colors mapped across the min and max colors selected in your rule.

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Big value

The Big value option is for displaying a single value, well, big. The Big value works for any type of value: string, numeric, boolean, you name it! We always display the first value from the field in your results table. The options for Big value include:
  • Selecting which field you want to use for your Big value.
  • Updating the label below the Big value value.
  • Adding a comparison to the previous row
    • Show raw value or percentage change
    • Show red or green for positive or negative change
    • Label your comparison value

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Configure your charts

Most chart types have very similar configuration options, so we put them all together below.

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Layout

This is where you can pick the columns from your results table that you want to plot on your x and y axes or that you want to group by. You can group by up to 3 fields in your chart. For bar charts, this is also where you have the option to stack your bars, or leave them unstacked (grouped).

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Series

The series tab is where you can adjust how your chart shows each data series. A data series is a set of related data points plotted on a chart. For example, the number of new users created each day over a set of dates is a series. In a bar chart, a series is represented by bars of the same color; in a line chart, a series is represented by a single line. You can see a list of the series for your chart in the Series menu, and on the chart legend.
The options available in here will depend on the data in your chart. But, in here you can:
  • Set the chart type for each series
  • Change series labels or colors
  • Put series on a left or right y-axis
  • Show value labels or group totals on data points
  • Hide a series from your chart

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Axes

In this section you have options to:
  • Override the default text for your axes labels
  • Adjust sort order of your x-axis
  • Rotate x-axis labels
  • Set the min and max axis values for your y-axes (or keep the default auto y-axis range)
  • Show x-axis and y-axis grid lines

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Display

This tab is where you’re able to control the legend, reference lines, and custom tooltips in your chart.

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Reference lines

You can add reference lines to your charts to easily visualize goals or thresholds.
To add a reference line, click + Add under Display -> Reference lines. You have these options in the settings:
  • Select a field you want to linke to your reference line (Page views in the image above)
  • Set a static value (50,000 in the image above)
  • Add a label (Halfway to our goal! in the image above)
  • Change the line color (green in the image above)
Most reference lines are static values, but you can also use these key words to plot a dynamic value: min, max, median, average.That way your reference line will automatically update to the global min, max, median, or average of the field you selected. See image below for examples.
dynamic reference lines example If you select a field plotted on your x-axis, then your line will be vertical. If you select a field plotted on your y-axis, then your line will be horizontal.
If your reference line label is cropped off your chart, try adjusting your right margin.

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Legend

You can add and adjust the legend in your chart to help people understand what data’s been plotted.
  • Show or hide the legend
  • Adjust the position of the legend on your chart
    • The values in position are the coordinates of the legend on your chart. They can either be numbers or percent. We suggest using %.
    • If you want the position to be in the bottom right, you would set: Right = 0%, Bottom = 0%. For the legend to be in the middle of the chart, you’d set: Top = 50%, Left = 50%.
  • Set your legend to scroll (if you have so many groups that they overlap your chart)
  • Orient the values in your legened to form a list vertically, or horizontally

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Margins

The Margin tab is where you’re able to add or remove margin around the grid. Removing margin means that your chart will fill more of the space in the chart tab. Adding margin will shrink your chart into a smaller space. You can either add numbers (e.g. 50) or percent values (e.g. 50%) to the margin settings listed. The default margin is set to top = 70, bottom = 30, left = 5%, right = 5%