What\'s the difference between:
pandas.DataFrame.from_csv
, doc link: http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.from_csv.htm
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.
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.