Bar Chart
  • 14 Mar 2023
  • 2 Minutes to read
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Bar Chart

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Article summary

The Bar Chartexcels at showcasing change over a dimension (e.g., time). In many domains, the distinction between discrete and continuous values is somewhat subtle. Here are some examples:

Reference Content

If you're new to visualizing data in Preset, we recommend the following reference articles:

Creating a Bar Chart

Preset currently has a few options for bar charts in the visualization picker:

  • Bar Chart
  • Bar Chart (legacy)

To visualize change over time using bars, we strongly recommend using the Bar Chart visualization type.

To create a Bar Chart, you need to define the following values:

  • the column you want as the X-axis
  • the metric(s) you want to visualize on the Y-axis
  • the column(s) you want the metric(s) to be grouped / categorized by

These are all defined in the Data tab within Explore.

Simple Bar Chart (no dimensions)

Below is a very simple bar chart that shows a single metric varying over time.

Here's an explanation of the selections we made in the chart builder interface to generate this chart.

X-axis
  • X-axis: Select the column (e.g., Time, Categories) to be visualized.
  • Time Grain: Define the granularity of the X-axis (Hourly, Daily, Weekly, etc.). The field will appear for temporal dimensions only. 
Metric(s) on Y-axis
  • Drag or select the Metric(s) to be visualized on the Y-axis

Here's the SQL query that Preset generated:

SELECT DATE_TRUNC('DAY', started_at) AS "started_at",
       count(DISTINCT ride_id) AS "COUNT_DISTINCT(ride_id)"
FROM dbt_smukherjee.citibike_trips
WHERE started_at >= '2022-04-01 00:00:00.000000'
  AND started_at < '2022-05-01 00:00:00.000000'
GROUP BY DATE_TRUNC('DAY', started_at)
ORDER BY "COUNT_DISTINCT(ride_id)" DESC
LIMIT 10000

This hopefully helps you understand the mapping from the chart builder options above to the final generated SQL query.

Bar Chart (with dimensions)

Below is a similar chart to the one above but with a dimension (rider type) added.

To generate this chart, we re-used the same selections from the first chart but made the following, additional selections:

Dimensions
  • Select any columns you want to slice/separate the bar series objects by. The unique values for those columns will be used to group together values and generate each bar series object.

Here's the SQL query that Preset generated:

SELECT DATE_TRUNC('DAY', started_at) AS "started_at",
       member_casual AS "member_casual",
       count(DISTINCT ride_id) AS "COUNT_DISTINCT(ride_id)"
FROM dbt_smukherjee.citibike_trips
WHERE started_at >= '2022-04-01 00:00:00.000000'
  AND started_at < '2022-05-01 00:00:00.000000'
GROUP BY DATE_TRUNC('DAY', started_at),
         member_casual
ORDER BY "COUNT_DISTINCT(ride_id)" DESC
LIMIT 10000

Advanced Analytics

As with most visualizations in Preset, the Bar Chart supports Advanced Analytics features like:


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