Pandas - Pandas.dataframe.from_csv Vs Pandas.read_csv

What's the difference between: pandas.DataFrame.from_csv, doc link: http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.from_csv.html and pandas.read_csv, doc li

Solution 1:

There is no real difference (both are based on the same underlying function), but as noted in the comments, they have some different default values (index_col is 0 or None, parse_dates is True or False for read_csv and DataFrame.from_csv respectively) and read_csv supports more arguments (in from_csv they are just not passed through).

Apart from that, it is recommended to use pd.read_csv. DataFrame.from_csv exists merely for historical reasons and to keep backwards compatibility (plans are to deprecate it, see here), but all new features are only added to read_csv (as you can see in the much longer list of keyword arguments). Actually, this should be made more clear in the docs.

Solution 2:

Another difference is that pandas.read_csv is 46x to 490x as fast as pandas.DataFrame.from_csv (in my testing).

I tested it on Python 3.4.4 and pandas 0.19.2 on Windows on my proprietary csv file.