Casualties are probably the most verbose and non-structured columns of the dataset. It will be extremely hard to make use of all the nuances of information here, so again—perhaps we can simplify the task, getting only the things we really want to use. Perhaps we can use code words to extract any digit preceding them; for example, ([\d|,]+)\s*dead should extract any consecutive digits or commas before the word 'dead'. We can define similar patterns for all types of casualties and loop over all of them, testing the patterns. There are, unfortunately, many keywords that mean the same thing ('captured', 'prisoners', and many more), so we have to make them optional, similar to the preceding month expression:
digit_pattern = '([\d|\,]+)(?:\[\d+\])?\s*(?:{words})'
keywords = { 'killed': ['dead&apos...
