@classmethod<EOL><INDENT>def from_csv(cls, path, header=<NUM_LIT:0>, sep='<STR_LIT:U+002C>', index_col=<NUM_LIT:0>, parse_dates=True,<EOL>encoding=None, tupleize_cols=None,<EOL>infer_datetime_format=False):<DEDENT>
warnings.warn("<STR_LIT>"<EOL>"<STR_LIT>"<EOL>"<STR_LIT>"<EOL>"<STR_LIT>",<EOL>FutureWarning, stacklevel=<NUM_LIT:2>)<EOL>from pandas.io.parsers import read_csv<EOL>return read_csv(path, header=header, sep=sep,<EOL>parse_dates=parse_dates, index_col=index_col,<EOL>encoding=encoding, tupleize_cols=tupleize_cols,<EOL>infer_datetime_format=infer_datetime_format)<EOL>
Read CSV file.

.. deprecated:: 0.21.0
    Use :func:`read_csv` instead.

It is preferable to use the more powerful :func:`read_csv`
for most general purposes, but ``from_csv`` makes for an easy
roundtrip to and from a file (the exact counterpart of
``to_csv``), especially with a DataFrame of time series data.

This method only differs from the preferred :func:`read_csv`
in some defaults:

- `index_col` is ``0`` instead of ``None`` (take first column as index
  by default)
- `parse_dates` is ``True`` instead of ``False`` (try parsing the index
  as datetime by default)

So a ``pd.DataFrame.from_csv(path)`` can be replaced by
``pd.read_csv(path, index_col=0, parse_dates=True)``.

Parameters
----------
path : string file path or file handle / StringIO
header : int, default 0
    Row to use as header (skip prior rows)
sep : string, default ','
    Field delimiter
index_col : int or sequence, default 0
    Column to use for index. If a sequence is given, a MultiIndex
    is used. Different default from read_table
parse_dates : boolean, default True
    Parse dates. Different default from read_table
tupleize_cols : boolean, default False
    write multi_index columns as a list of tuples (if True)
    or new (expanded format) if False)
infer_datetime_format : boolean, default False
    If True and `parse_dates` is True for a column, try to infer the
    datetime format based on the first datetime string. If the format
    can be inferred, there often will be a large parsing speed-up.

Returns
-------
DataFrame

See Also
--------
read_csv