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Build a histogram in Grafana

Histograms show how data is distributed. You can use one to graph the number of data points that fall into buckets on some scale. For example, histograms are often used to show the spread of financial instruments.

They can answer questions like:

  • What is the distribution of the Meta stock price today?
  • What was the transaction volume distribution of AMD stock last week?
  • What was the distribution of daily returns of the S&P in the past year?

Data for Grafana histograms

With Grafana, you can plot a histogram by providing data in 1 of 3 formats. Each comes with its own benefits and challenges:

  • Raw data: This method does not require you to pre-bucket or pre-aggregate the data. It increases histogram accuracy. But it requires more CPU, memory, and network usage, because all bucketing is done in the browser. This could lead to severe performance issues.
  • Pre-bucketed data: You need to configure the data source to pre-bucket your data. According to the Grafana documentation, any source can output pre-bucketed data for a histogram, as long as it meets the data format requirements. For example, it suggests that you can use Elastic Search's histogram bucket aggregation or Prometheus' histogram metric.
  • Aggregated data: Grafana also accepts pre-aggregated time-bucket data. You can aggregate your data using TimescaleDB's time_bucket function or PostgreSQL's date_trunc function. To create the histogram, Grafana further buckets the aggregated data. It automatically selects a bucket size, which is about 10% of your data's total range.

note

Histograms are great for analyzing the spread or distribution of data, but they don't show the change of data over time. If you need to see the distribution of your data over time, try a heatmap instead.

What you'll learn

This tutorial shows you how to:

Prerequisites

Before you begin, make sure you have:

If you are new to Grafana, see the Grafana tutorials to get familiar with creating your first dashboard and visualizations before you start.

The examples in this section use these variables and Grafana functions:

  • $symbol: a variable used to filter results by stock symbols.
  • $bucket_interval: the interval size to pass to the time_bucket function when aggregating data.
  • $__timeFrom()::timestamptz & $__timeTo()::timestamptz: Grafana variables. You change the values of these variables by using the dashboard's date chooser when viewing your graph.

Create a price/transaction histogram with raw data

A common histogram for evaluating stock trade data is a price/transaction volume histogram. This shows the number of trades occurring at a given price range, within some time interval. To make this histogram, select the raw transactions data from the stocks_real_time hypertable.

Creating a price/transaction histogram with raw data

  1. Add this query to a Grafana dashboard:

    SELECT time,
        price
    FROM stocks_real_time srt
    WHERE symbol = '$symbol'
        AND time >= $__timeFrom()::timestamptz and time < $__timeTo()::timestamptz
    ORDER BY time;
  2. Select a stock from the dashboard variable. Adjust the time range of your dashboard if desired.

  3. The returned data looks like this:

    time                         |price   |
    -----------------------------+--------+
    2022-03-02 17:01:07.000 -0700|  166.33|
    2022-03-02 17:01:26.000 -0700|165.8799|
    2022-03-02 17:01:31.000 -0700|165.8799|
    2022-03-02 17:01:46.000 -0700|  166.43|
    2022-03-02 17:02:22.000 -0700|  166.49|
    2022-03-02 17:02:40.000 -0700|166.6001|
                 …               |   …    |

    The key feature with any time-series data used by Grafana is that it must have a column named time with timestamp data. The other columns used for graphing data can have different names, but each time-series chart must have a time column in the results. For the Histogram visualization, the timestamp values must be in ascending order or you will receive an error.

  4. Select "Histogram" as your visualization type.

  5. Grafana turns the query into a histogram that looks like this:

    The histogram shows that the price of $AAPL ranges between $154 and $176. Grafana automatically picks a bucket size for us, in this case $2.

  6. To increase the granularity of the histogram, change the bucket size from 2 to 0.1.

  7. The histogram now looks similar, but shows more detail.

Create a price/transaction histogram with aggregated data

In the previous example, we queried raw data for Apple stock, which often trades ~40 000 times a day. The query returns more than 40 000 rows of data for Grafana to bucket every refresh interval, which is 30 seconds by default. This uses a lot of CPU, memory, and network bandwidth. In extreme cases, Grafana will show you the message: Results have been limited to 1000000 because the SQL row limit was reached

This means Grafana has decided not to display all rows returned by the query. To solve this problem, pre-aggregate the data in your query using TimescaleDB's time_bucket function. With time_bucket, you need to add a new variable called bucket_interval.

Creating a price/transaction histogram with pre-aggregated data

  1. In Grafana, add a new variable called $bucket_interval, of type INTERVAL.

  2. Use the $bucket_interval variable to aggregate the price for the selected interval:

    SELECT time_bucket('$bucket_interval', time) as time,
        AVG(price) avg_price
    FROM stocks_real_time srt
    WHERE symbol = '$symbol'
        AND time >= $__timeFrom()::timestamptz and time < $__timeTo()::timestamptz
    GROUP BY time_bucket('$date_range',time);
  3. This query yields the following histogram:

    This second histogram looks similar to the example that uses raw transaction data. But the query returns only around 1000 rows of data with each request. This reduces the network load and Grafana processing time.

Create a panel with multiple price/transaction histograms

To compare the distributions of 2 or more different stocks, create a panel with multiple histograms. Change the $symbol variable from a text variable to a query variable, and enable the multi-value option. This allows you to select more than one value for $symbol. The database returns the transactions for all selected values, and Grafana buckets them in separate histograms.

Creating a panel with multiple price/transaction histograms

  1. Fetch all company symbols from the dataset:

    SELECT DISTINCT symbol FROM company ORDER BY symbol ASC;
  2. Create a new dashboard variable with the previous query:

  3. Update the main query to the following:

    SELECT time_bucket('$bucket_interval', time) AS time,
        symbol,
        AVG(price) AS avg_price
    FROM stocks_real_time srt
    WHERE symbol in ($symbol)
        AND time >= $__timeFrom()::timestamptz AND time < $__timeTo()::timestamptz
    GROUP BY time_bucket('$bucket_interval', time), symbol;
  4. This query results in the following histograms:

    We can clearly see the 3 distinct histograms but it's impossible to tell them apart from each other.

  5. Click on the green line at the left side of the legend and pick a color:

  6. The plot clearly shows the 3 price distributions in different colors.

Create a price/volume histogram

Besides transaction price, you can also look at trade volumes. The distribution of trade volume shows you how often and how much people are buying a stock.

The stocks_real_time hypertable contains a column with the daily cumulative volume. You can use this to calculate the volume of data for each bucket. First, find the maximum day_volume value for a symbol within a bucket. Then subtract each maximum from the previous bucket's maximum. The difference equals the volume for that bucket.

You can do this with a pre-aggregation query, using:

  • TimescaleDB's time_bucket function.
  • PostgreSQL's max function.
  • PostgreSQL's lag function. Use this to subtract each from from the previous, when the rows are ordered by descending time.

Creating a price/volume histogram

  1. Create a new histogram panel with the following query:

    WITH buckets AS (
        SELECT time_bucket('$bucket_interval', time) AS time,
            symbol,
            MAX(day_volume) AS dv_max
        FROM stocks_real_time
        WHERE time >= $__timeFrom()::timestamptz AND time < $__timeTo()::timestamptz
            AND day_volume IS NOT NULL
            AND symbol in ($symbol)
        GROUP BY time_bucket('$bucket_interval', time), symbol
    )
    SELECT TIME,
        symbol,
        CASE WHEN lag(dv_max ,1) OVER (PARTITION BY symbol ORDER BY time) IS NULL THEN dv_max
        WHEN (dv_max - lag(dv_max, 1) OVER (PARTITION BY symbol ORDER BY time)) < 0 THEN dv_max
        ELSE (dv_max - lag(dv_max, 1) OVER (PARTITION BY symbol ORDER BY time)) END vol
    FROM buckets;
  2. This query results in the following histogram:

    The plot shows a left-skewed distribution for the AMZN symbol. For many symbols, you might see a distorted distribution, due to outliers representing a few very large volume transactions. There are 2 solutions:

    1. Limit your query to transactions with volumes less than a certain threshold.
    2. Use a logarithmic scale. Unfortunately these are not yet supported in Grafana histogram panels.

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