Description Usage Arguments Details Value Author(s) Examples
Take time series dataset and fields, then refill the missing date records and other fields.
1 2 | dateRefill.fromData(data, dateCol.index, fixedCol.index,
uninterpolatedCol.index, uninterpolatedCol.newValue)
|
data |
The data.frame dataset which is ready to be processed |
dateCol.index |
Date column |
fixedCol.index |
A row of column number which should be kept same values with the original |
uninterpolatedCol.index |
The column number which should be changed to different value into new record. |
uninterpolatedCol.newValue |
The value of a specific column which should be put into the new record. |
Real time series sales dataset could be not continuous in 'date' field. e.g., monthly sales data is continuous, but discrete in daily data.
This hollow dataset is not complete for time series analysis. Function dateRefill.fromFile is a transformation which tranforms uncomplete dataset into complete dataset.
The dataset which is completed.
Will Kuan
1 2 3 | # mydata <- data.example
# mydata.final <- dateRefill.fromData(data = mydata,dateCol = 2,fixedVec = c(3:10),
# uninterpolatedCol.index = 11,uninterpolatedCol.newValue = 0)
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