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Description |
Transforms each time series sample to the percentage of missing values according to the time scale up to it in the series (including itself). The count starts from the first actual example in the selected time range. |
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Input |
Time Series – Single time series or a multiple time series. |
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Parameters |
None |
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Output |
Transformed Time Series - multiple |
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Available in |
Dashboards |
Usage Example
Use the PercentMissingValue function when there are several gaps in the time series at a certain time scale. The function computes the percentage of missing values for each metric in the expression, so you can know how much of the metric is missing.
For example, the metric below exhibit multiple gaps in the daily time scale over the last 3 months:
But how many daily data points are actually missing? If we apply the PercentMissingValues function, we will see that the last point shows that over the last 3 months 72.09% of the days are missing:
However, when switching to the weekly time scale, we will see there was not a single missing weekly data point over the course of the last 3 months:
Expert tip: This function can help decide the optimal time scale to set for an alert (by assessing the metric sparseness in each time scale).
