This Program is part of the tutorial.
This program takes a file under the parameter name \"raw_timeseries_file\" and attempts to extract a timeseries from it that is properly formatted and cleaned to be suitable for further use by machine learning algorithms. It also takes a parameter \"require_timeseries_to_predict_tag\", which is a Tag of type require_timeseries_to_predict.
This Program requires files in excel format (.xlsx).
It can find tables anywhere in the file, but it only works properly if there are no missing values in the table.
It outputs files in the Python pandas format.
The detection of timeseries works if:
-The content is either vertical or horizontal.
-The table's x-axis may optionally have a header.
-The table's y-axis may optionally have a header.
The detection does not work if:
-There are missing values in a table. If this happens, this program will treat the gap as the end of the column and will treat the next number as the beginning of another, entirely new column.
Created: Sept. 27, 2018, 3:15 p.m.
Docker Image: elody.com:444/extract_timeseries_from_excel_file@sha256:0855b16a1c2b6a121a527d5aec3272486b7ec138fc87c96a8ab621b6f76daca5
Source code: Run the following command in a terminal to download the source code: 'lod-tools download-program -f <destination_folder> --name "Extract_timeseries_from_excel_file" --version 5'
all versions of this Program: