Frequently I get data as “pretty tables” in many worksheets in an Excel workbook. By “pretty” I mean that there is explanatory text at the top and bottom of every worksheet, headers have merged cells, there are blanks lines between the header and the first data row, there are blank columns between data columns, etc.

Is there a best practice for reducing manual labor here?
One approach could be to fix all of these tables in Excel. Another could be to save “as-is” to tab-delimited txt, manually select and import the data rows, drop the blank columns, and manually enter the header information. I tend to do the later, but even this is fairly manual.
What are the pros doing? When I do it this way I feel like the guy who doesn’t know about cut and paste.
FWIW, I use Python, Stata, and R for most things, but I’m open to any tool that simplifies this process. Thanks!
To be honest the amount of automation that I use in the process of cleaning data depends on the number of times I have to do it. For me I think modifying the files in Excel via macro.
If your files always have the same format (for a particular task) you can simply record a macro of the steps you are doing to clean them up, and save them in your personal workbook
If they are slightly different but have variations on a theme you can modify the recorded marco (ideally factoring out into functions like
DeleteTopRowsandDeleteEmptyColumnswhich would accept different parameters depending on the input file)I think Excel VBA is the easiest place to work from for this type of job because the excel app can help with a lot of built in functions. For example in your sheet above
Range("10:11").Deletewill remove them.