Visualize

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

count#

The count visualization counts all matching events and produces a time series chart.

Arguments#

This visualization doesn’t take an argument.

Group-by behaviour#

The visualization produces a separate result for each group plotted on a time series chart.

count overview

distinct#

The distinct visualization counts each distinct occurrence of the distinct field inside the dataset and produce a time series chart.

Arguments#

field: any is the field to aggregate.

Group-By Behaviour#

The visualization produces a separate result for each group plotted on a time series chart.

distinct overview

avg#

The avg visualization averages the values of the field inside the dataset and produces a time series chart.

Arguments#

field: number is the number field to average.

Group-by behaviour#

The visualization produces a separate result for each group plotted on a time series chart.

avg overview

max#

The max visualization finds the maximum value of the field inside the dataset and produces a time series chart.

Arguments#

field: number is the number field where Axiom finds the maximum value.

Group-by behaviour#

The visualization produces a separate result for each group plotted on a time series chart.

max overview

min#

The min visualization finds the minimum value of the field inside the dataset and produces a time series chart.

Arguments#

field: number is the number field where Axiom finds the minimum value.

Group-by behaviour#

The visualization produces a separate result for each group plotted on a time series chart.

min overview

sum#

The sum visualization adds all the values of the field inside the dataset and produces a time series chart.

Arguments#

field: number is the number field where Axiom calculates the sum.

Group-by behaviour#

The visualization produces a separate result for each group plotted on a time series chart.

sum overview

percentiles#

The percentiles visualization calculates the requested percentiles of the field in the dataset and produces a time series chart.

Arguments#

• field: number is the number field where Axiom calculates the percentiles.
• percentiles: number [, ...] is a list of percentiles , each a float between 0 and 100. For example, percentiles(request_size, 95, 99, 99.9).

Group-by behaviour#

The visualization produces a separate result for each group plotted on a horizontal bar chart, allowing for visual comparison across the groups.

percentile overview

histogram#

The histogram visualization buckets the field into a distribution of N buckets, returning a time series heatmap chart.

Arguments#

• field: number is the number field where Axiom calculates the distribution.
• nBuckets is the number of buckets to return. For example, histogram(request_size, 15).

Group-by behaviour#

The visualization produces a separate result for each group plotted on a time series histogram. Hovering over a group in the totals table shows only the results for that group in the histogram.

histogram overview

topk#

The topk visualization calculates the top values for a field in a dataset.

Arguments#

• field: number is the number field where Axiom calculates the top values.
• nResults is the number of top values to return. For example, topk(method, 10).

Group-by behaviour#

The visualization produces a separate result for each group plotted on a time series chart.

topk overview

variance#

The variance visualization calculates the variance of the field in the dataset and produces a time series chart. The variance aggregation returns the sample variance of the fields of the dataset.

Arguments#

field: number is the number field where Axiom calculates the variance.

Group-by behaviour#

The visualization produces a separate result for each group plotted on a time series chart.

variance overview

stddev#

The stddev visualization calculates the standard deviation of the field in the dataset and produces a time series chart. The stddev aggregation returns the sample standard deviation of the fields of the dataset.

Arguments#

field: number is the number field where Axiom calculates the standard deviation.

Group-by behaviour#

The visualization produces a separate result for each group plotted on a time series chart.

stddev overview