Converting .txt to .csv file

[palladium]

Easiest way to find out is to print out the dataframe and see how many columns you get. I can't see any ';' delimiters in your text file, though. The solution may be to use sep = None, this will force the Python engine which can automatically detect the separator (read the docs for details).

Pandas can also directly write to an Excel file, fyi.

Hi Palladium,

I just tried adding "sep = None" and this is the error message I get...

runfile('C:/Users/vhubb/Documents/Python Scripts/temp.py', wdir='C:/Users/vhubb/Documents/Python Scripts')
C:\Users\vhubb\Documents\Python Scripts\temp.py:37: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.
  df = pd.read_csv(in_filename, sep="None")

It's not an error message. Its a warning to let you know that the pandas engine is using a non default method to parse your file (the default is C engine which does not guessing delimiters; pandas is telling you that it has switched to the python engine which I understand is slower but has some built in support for guessing delimiters). If you add the keyword argument engine = 'python' as per the warning message, the message should disappear.

An error message will tell you what type of error it is (e.g. "TypeError" or "ValueError") followed by a message.

If you don't see anything else it means the process is successful. Print out the resulting dataframe to verify.

As buran pointed out you can use pandas' built in to_excel() method, which dumps the dataframe into an xlsx file format. It is customisable to some extent,b ut as (s)he astutely pointed out, given your complex needs openpyxl may be a better bet.