30 Years Of Excel Test Data I am a CS intern at an industrial company that has 30 years of excel files that need to be analyzed. Looking at the data, only a fraction of the files need to be looked at and used. After those files are identified, I need to pull out values from specific columns. The real issue is that there is no standard excel format for the tests and each column name can be different (ex. 'Front Axial Temperature' vs 'axial temp front') but contains the same type of data.

So, the data is semi-structured, are there any python/java libraries which are good at pulling such data out? I could create some regex patterns but as you can see the above names can be drastically different (while still meaning the same thing).

I would also be interested in looking at services that do this already.
I see three main ways of comparing columns: automated comparisons of column names (e.g. regex,  Levenshtein distance), comparing content (e.g. compare mean and standard deviation of the data for the column; if the mean value of a column is 10,000 then it probably isn't recording Front Axial Temperature), and manual comparison. You can combine these, for instance clustering on column names and content, then manually looking at the contents of each cluster. The smaller the number of different column names, the more you can rely on manual examination. You may also be able to get other metadata sources, such as looking for documentation for whatever process generated the files.