- 14 Mar 2023
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Bar Chart
- Updated on 14 Mar 2023
- 2 Minutes to read
- Print
- DarkLight
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 Chart: A walkthrough of the overall process of chart selection and creation.
- Using Preset Chart Builder: How to work with the Chart Builder page, the primary interface used when creating a chart.
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
| |
Metric(s) on 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
|
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: