Mixed.txt -

Before writing code, understand what you are dealing with. Using tools like file or checking for carriage returns (CRLF vs LF) is essential. A mixed file often needs custom parsing rather than standard csv.reader . 2. Using numpy.genfromtxt (The Power Tool)

If the file is truly chaotic (different numbers of columns per line), reading it line-by-line using Python’s built-in csv module is often safer. You can use regex to identify scientific notation ( -1.000e+01 ) and convert it to numbers manually. 4. The "Final Boss": Cleaning the Data Once you’ve loaded the data, you’ll likely need to: Remove extra whitespace. Convert scientific notation strings to floats. Filter out comment lines (e.g., lines starting with # ). MIxed.txt

If you can share a few lines of the actual content of "MIxed.txt", I can: Before writing code, understand what you are dealing with

Mixed-type files are intimidating, but with the right approach—loading as raw text first and then casting types—you can master them. Filter out comment lines (e.g.