I have a CSV file that I read it as a table with 'readtable'. The original CSV file contains timestamps for a wide range of days. In most of the cases, I do not need that massive amount of timestamps available, because my analyze is centred in a shorter period. Let me put an example to explain better my problem:
The CSV file contains the timestamps in column 1. It starts at timestamp=1573377305, and it starts increasing the timestamps without a determined size, the next timestamp can be at 8 seconds, the third at 10 seconds and so on. What I know are the timestamps of my analysis, the beginning and the end, but I don't know the number of rows that correspond with that interval.
For instance: my timestamps
1573377305 1573377312 1573377326 1573377334 1573377349 1573377355 1573377365 1573377373 1573377386 1573377393 1573377404 1573377416 1573377427 1573377433 1573377445 1573377455 1573377465 1573377475 1573377485
Imagine that my timestamp for analysis is from 1573377326 to 1573377433. I don't want to read all the previous and end information with readtable(). In this case, I could do DataLines = [4 15], but it is an illustrative example. Imagine that you have much more than 20 timestamps, and what you know is the timestamp from beginning to end.
If I upload all the data with 'readtable()', it is inefficient as I am loading information that I am not going to use. How can I do to select the precise interval I am going to use before using readtable()? Or how can I do this process more efficient?
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