read_csv takes an encoding option to deal with files in different formats. I mostly use read_csv('file', encoding = "ISO-8859-1"), or alternatively encoding = "utf-8" for reading, and generally utf-8 for to_csv.

You can also use one of several alias options like 'latin' or 'cp1252' (Windows) instead of 'ISO-8859-1' (see python docs, also for numerous other encodings you may encounter).

See relevant Pandas documentation, python docs examples on csv files, and plenty of related questions here on SO. A good background resource is What every developer should know about unicode and character sets.

To detect the encoding (assuming the file contains non-ascii characters), you can use enca (see man page) or file -i (linux) or file -I (osx) (see man page).

byte 0xff in position 0 means that your .csv is probably encoded in utf-16.

Try this :

data1 = pd.read_csv("data1.csv", encoding="utf-16")

Managed to solve this.

I made a function that goes through my columns that have strings and managed to decode/encode them into utf8 and it now works.

def changeencode(data, cols):
    for col in cols:
        data[col] = data[col].str.decode('iso-8859-1').str.encode('utf-8')
    return data