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Revision as of 09:38, 7 December 2016
As you bring data into dataZoa, it is harmonized (or "normalized") so that any series can work with any other. While we preserve all the original series documentation, we load the dates and values into an idealized time series. This automatically handles the specific nuances of time series data, elimination the "data drudgery"; cleaning, aligning, pasting, re-typing and such.
Contents
Date Handling
Frequency/Periodicity
- PERIODICITIES (FREQUENCIES):
- Daily
- Weekly
- Monthly
- Quarterly
- Semiannual
- Annual
- Irregular
Date Range
- EARLIEST DATE:
- Because of the calendar discontinuity introduced at the Gregorian transition, the earliest year that can be stored accurately to the day is 1753.
- Non accurate dates can begin as early as 1/1/1000.
- LATEST DATE:
- 12/31/9999
Gaps
dataZoa handles data gaps automatically and gracefully for all regular periodicities. If you want to prevent the natural implicit behaviors in calculations, charts, etc., you can use the "Irregular" periodicity. If you want customized treatments of gaps, such as "carry forward" you can use the Computecloud.
Date Formats
Inputs
Both American-style mm-dd-yyyy dates and International Style dd-mm-yyyy date formats are supported.
Supported date formats include:
| Fully Specified | Year Only | Month, Year Only | Semi-Annual | Quarterly |
|---|---|---|---|---|
| 01-15-2011 01-15-11 01/15/2011 01/15/11 15-01-2011 15-01-11 15/01/2011 15/01/11 15-Jan-11 15JAN2011 2011-01-15 20110115 Jan 15 2011 January 15, 2011 Sunday, January 15, 2011 110115 |
2011 | 1/11 1/2011 01-2011 2011m01 2011 Jan 2011Jan Jan 2011 Jan2011 |
2011H1 2011h1 |
2011Q1 2011q1 |
Outputs
Dates are formatted using a "human friendly" method appropriate to the periodicity of the data.
Data Value Handling
Missing Values Handling
Values can be "missing" for different reasons, with different implications. dataZoa recognizes several different types of missing values and treats them appropriately.
| Non-Numeric Type | Meaning | String to enter as Input | String displayed as Output |
|---|---|---|---|
| No Data | Data point is known not to exist | ##ND## | ND |
| Non-Disclosed Data | Data point exists but is not being shown | ##NDD## | NDD |
| Not Available | Data may exist but is not available | ##NA## | NA |
Calculations
In all calculations, missing data has the highest precedence; e.g. a number plus an NA yields an NA. Specialized functions in the ComputeCloud can be used for specialized handling, such as carry-forward, etc.
Tables
By default, No Data (ND) formats as a blank, while NA, and NDD data are formatted with "NA" and "NDD", respectively. To fine tune these representations, see Displays.
Charts
Missing values are typically shown as gaps.
Value Formatting
Numeric values are formatted using a "human friendly" method that takes several factors into consideration; magnitude, sign, apparent significance, etc.
When specific formats are required for displays, options are generally available to control formatting at the display, row, column, and cell level, as appropriate.
