We're looking at open data published in multiple excel spreadsheets with no standard format. The data can be embedded in multiple tables within a given sheet, e.g.
| | | | | | | | | | | |
|------|----------|---------------|----------|-------|------|----------|---------------|----------|-------|--|
| | Day: | Friday | | | | Day: | Saturday | | | |
| | Date: | 08/24/2012 | | | | Date: | 08/25/2012 | | | |
| | Weather: | 30°C, No Rain | | | | Weather: | 30°C, No Rain | | | |
| | | | | | | | | | | |
| | Hour | In | Out | Total | | Hour | In Park | Out | Total | |
| | 12:00 AM | 0 | 0 | 0 | | 12:00 AM | 0 | 0 | 0 | |
| | 1:00 AM | 0 | 0 | 0 | | 1:00 AM | 0 | 0 | 0 | |
| | 2:00 AM | 0 | 0 | 0 | | 2:00 AM | 0 | 0 | 0 | |
| | 3:00 AM | 0 | 0 | 0 | | 3:00 AM | 0 | 0 | 0 | |
But these tables are not necessarily located in the same location, nor is the data generally structured exactly the same, though it will generally follow the following pattern:
| Timestamp | Count | Count |
|-----------|-------|-------|
I've identified Python libraries that can interact with Excel spreadsheets, but are there parsing libraries built on top of these to identify patterns within spreadsheets? We want to be able to parse multiple spreadsheets and get the data into one file for manipulation/cleansing before loading it into a database. Non-Python solutions welcome.