In python, we can use either the csv module or the pandas.read_csv function to handle csv files. For Excel files we can use the xlrd module or the pandas.read_excel function.
I use pandas a lot and I feel that the read_csv and read_excel functions come in handy for me. Can anyone explain me what are the pros and cons of each of these methods?
.xlsx files!This change happened in version 2.0.0
However regarding CSV files I think it would be interesting to do a speed comparison between pandas and csv.
My experience is that the pandas module reads CSV files more strictly. If a column is all numbers and one row is empty, pandas produces a NaN value unless you use df.fillna('', inplace=True) or something similar. This can be annoying if you have mixed data types or if you expect None or blank values in a column. The csv library seems to handle this a little nicer.
When I used csv on python2, utf-8 was a nightmare, but I assume that's better now with python3.