Method for creating period profile for time-series data with recurrent patterns
Techniques are described for generating period profiles. According to an embodiment, a set of time series data is received, where the set of time series data includes data spanning a plurality of time windows having a seasonal period. Based at least in part on the set of time-series data, a first set of sub-periods of the seasonal period is associated with a particular class of seasonal pattern. A profile for a seasonal period that identifies which sub-periods of the seasonal period are associated with the particular class of seasonal pattern is generated and stored, in volatile or non-volatile storage. Based on the profile, a visualization is generated for at least one sub-period of the first set of sub-periods of the seasonal period that indicates that the at least one sub-period is part of the particular class of seasonal pattern.
1. A method comprising:
receiving a set of time series data that includes data spanning a plurality of time windows having a seasonal period;
associating, based at least in part on the set of time series data, a first set of sub-periods of the seasonal period with a particular class of seasonal pattern;
wherein, after associating the first set of sub-periods with the particular class of seasonal pattern, a second set of sub-periods is not associated with the particular class of seasonal pattern;
generating and storing, in volatile or non-volatile storage, a profile for the seasonal period that identifies which sub-periods of the seasonal period are associated with the particular class of seasonal pattern;
causing, based on the profile, a visualization for at least one sub-period of the first set of sub-periods of the seasonal period that indicates that the at least one sub-period is part of the particular class of seasonal pattern.
2. The method of claim 1 , wherein associating the particular seasonal class is one of a first class for dense highs, a second class for sparse highs, a third class for dense lows, or a fourth class for sparse lows.
3. The method of claim 2 , wherein the visualization identifies which sub-periods of the seasonal period are sparse highs.
4. The method of claim 1 , wherein the visualization identifies a buffer in values that fall within sub-periods associated with the particular class of seasonal pattern.
5. The method of claim 1 , wherein data within sub-periods that have been classified differently are displayed in different colors.
6. The method of claim 1 , wherein sub-periods that have been classified differently are displayed in different colors on a calendar interface.
7. The method of claim 1 , wherein values from the profile are displayed in a manner that is based on how the sub-periods have been classified.
8. The method of claim 1 , further comprising selecting or restricting values to display from the profile based on how the sub-periods have been classified.
9. The method of claim 8 , further comprising displaying only values from sub-periods that have been classified as sparse highs.
10. The method of claim 1 , wherein the visualization is marked to distinguish between different classifications of sub-periods.
11. One or more non-transitory computer-readable media storing instructions, which, when executed by one or more hardware processors, cause performance of operations comprising:
receiving a set of time series data that includes data spanning a plurality of time windows having a seasonal period;
associating, based at least in part on the set of time series data, a first set of sub-periods of the seasonal period with a particular class of seasonal pattern;
wherein, after associating the first set of sub-periods with the particular class of seasonal pattern, a second set of sub-periods is not associated with the particular class of seasonal pattern;
generating and storing, in volatile or non-volatile storage, a profile for the seasonal period that identifies which sub-periods of the seasonal period are associated with the particular class of seasonal pattern;
causing, based on the profile, a visualization for at least one sub-period of the first set of sub-periods of the seasonal period that indicates that the at least one sub-period is part of the particular class of seasonal pattern.
12. The one or more non-transitory computer-readable media of claim 11 , wherein associating the particular seasonal class is one of a first class for dense highs, a second class for sparse highs, a third class for dense lows, or a fourth class for sparse lows.
13. The one or more non-transitory computer-readable media of claim 12 , wherein the visualization identifies which sub-periods of the seasonal period are sparse highs.
14. The one or more non-transitory computer-readable media of claim 11 , wherein the visualization identifies a buffer in values that fall within sub-periods associated with the particular class of seasonal pattern.
15. The one or more non-transitory computer-readable media of claim 11 , wherein data within sub-periods that have been classified differently are displayed in different colors.
16. The one or more non-transitory computer-readable media of claim 11 , wherein sub-periods that have been classified differently are displayed in different colors on a calendar interface.
17. The one or more non-transitory computer-readable media of claim 11 , wherein values from the profile are displayed in a manner that is based on how the sub-periods have been classified.
18. The one or more non-transitory computer-readable media of claim 11 , the instructions further causing operations comprising selecting or restricting values to display from the profile based on how the sub-periods have been classified.
19. The one or more non-transitory computer-readable media of claim 18 , the instructions further causing operations comprising displaying only values from sub-periods that have been classified as sparse highs.
20. The one or more non-transitory computer-readable media of claim 11 , wherein the visualization is marked to distinguish between different classifications of sub-periods.