How do you import time series data into timetable where the timestamps are formatted strings as opposed to date serial?
For example, I have the following data in a csv file.
20191208 18:17:00,17,17,17,17
20191208 18:18:00,17.5,17,17,17.5
20191208 18:19:00,17.5,17.5,17.5,17.5
where the timestamps have the format YYYYMMDD hh:mm:ss
. Headings for each column may or may not be present in the file.
Using readtimetable
would give the error message
Unable to detect datetime or duration data in file
Of course, ultimately, the data can be parsed manually as plain text. At a minimum, since we are talking about well formed csv files, readtable
will always recognize it (and I think readtable
is able to accommodate potentially present column headings; not sure). From there, one can convert the data into timetable
after string processing the timestamp column.
My question is, what is the most efficient way possible to convert a time series stored in csv with timestamp in formatted string? Efficient as simple in coding and inexpensive computationally?