# Visualizations

Visualizations are powerful aggregations that are run across your data to produce insights that are easy to understand and monitor.

With Visualizations, teams can create and obtain data stats, group fields and observe methods in running deployments.

This page will introduce you to the visualizations supported by Axiom and some tips on how best to use them.

## count

The `count`

visualization will count all matching events and produces a timeseries chart.

#### Arguments

`none`

#### Group-By Behaviour

Visualization will produce a separate result for each group plotted on a timeseries chart.

## distinct

The `distinct`

visualization counts each distinct occurrence of the distinct field inside the dataset and produce a timeseries chart.

#### Arguments

`field: any`

- a field to aggregate

#### Group-By Behaviour

Visualization will produce a separate result for each group plotted on a timeseries chart.

## avg

The `avg`

visualization averages the values of the field inside the dataset and produces a timeseries chart

#### Arguments

`field: number`

- a number field

#### Group-By Behaviour

Visualization will produce a separate result for each group plotted on a timeseries chart.

## max

The `max`

visualization finds the maximum value of the field inside the dataset and produces a timeseries chart.

#### Arguments

`field: number`

- a number field

#### Group-By Behaviour

Visualization will produce a separate result for each group plotted on a timeseries chart.

## min

The `min`

visualization finds the minimum value of the field inside the dataset and produces a timeseries chart.

#### Arguments

`field: number`

- a number field

#### Group-By Behaviour

Visualization will produce a separate result for each group plotted on a timeseries chart.

## sum

The `sum`

visualization adds all the values of the field inside the dataset and produces a timeseries chart.

#### Arguments

`field: number`

- a number field

#### Group-By Behaviour

Visualization will produce a separate result for each group plotted on a timeseries chart.

## percentiles

The `percentiles`

visualization calculates the requested percentiles of the field in the dataset and produces a timeseries chart.

#### Arguments

`field: number`

- a number field`percentiles: number [, ...]`

- one or more percentiles (a float between 0 and 100)- e.g.
`percentiles(request_size, 95, 99, 99.9)`

- e.g.

#### Group-By Behaviour

Visualization will produce a separate result for each group plotted on a horizontal bar chart, allowing for visual comparison across the groups.

## histogram

The `histogram`

visualization buckets the field into a distribution of N buckets, returning a timeseries heatmap chart.

#### Arguments

`field: number`

- a number field`nBuckets`

: number of buckets to return- e.g.
`histogram(request_size, 15)`

- e.g.

#### Group-By Behaviour

Visualization will produce a separate result for each group plotted on a timeseries histogram. Hovering over a group in the totals table will show only the results for that group in the histogram.

## topk

The `topk`

visualization calculates the **top** values for a field in a dataset. Where `k`

can be *10*, *20* or any number you specify.

#### Arguments

`field: string`

- a string field`nResults`

: number of results to return- e.g.
`topk(method, 10)`

- e.g.

#### Group-By Behaviour

Visualization will produce a separate result for each group plotted on a timeseries chart.

## variance

The `variance`

visualization calculates the variance of the field in the dataset and produces a timeseries chart. Variance is calculated by taking the difference between each item in a dataset and the mean, squaring that number, summing them all up, and then dividing by one less than the number of events in a dataset.

- The variance aggregation returns the sample variance of the fields of the dataset.

#### Arguments

`field: number`

- a number field

#### Group-By Behaviour

Visualization will produce a separate result for each group plotted on a timeseries chart.

## stddev

The `stddev`

visualization calculates the standard deviation of the field in the dataset and produces a timeseries chart. Standard deviation is the `square root`

of the variance.

- The stdev aggregation returns the sample standard deviation of the fields of the dataset.

#### Arguments

`field: number`

- a number field

#### Group-By Behaviour

Visualization will produce a separate result for each group plotted on a timeseries chart.