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This is the default option.
Web Service Filter
dpo_dataGaps=1Do not fill gaps
This option will not take action to fill in data gaps.
This option will cause action to be taken to remove all NaNs in the data. The main implication of this is if the clean option had been selected, data that failed quality control tests will be removed entirely. However, there is an exception to this: for multi-sensor time series scalar data, if one sensor at a given time stamp has valid data, the entire row/time stamp cannot be removed, so the remaining sensors will be left as NaNs. For clarification, see the following example, note that QAQC flags of 1s are good data, 4s are failures and 9s are missing data:
sample time | sensor 1 | sensor 1 flag | sensor 2 | sensor 2 flag | Comment |
|---|---|---|---|---|---|
12:00:00 | 42 | 1 | 42 | 1 | Good row. |
12:00:01 | NaN | 4 | NaN | 9 | Two bad values; one QAQC failure, one data gap. If the do not fill gaps is selected, this entire row will be removed. |
12:00:02 | NaN | 4 | 44 | 1 | One good value, can't remove row. |
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'NaN' is added to the file name when the data gaps are filled with NaNs.
Web Service Filter
dpo_dataGaps=0