def to_pickle(self, path, compression='<STR_LIT>',<EOL>protocol=pickle.HIGHEST_PROTOCOL):
from pandas.io.pickle import to_pickle<EOL>return to_pickle(self, path, compression=compression,<EOL>protocol=protocol)<EOL>
Pickle (serialize) object to file.

Parameters
----------
path : str
    File path where the pickled object will be stored.
compression : {'infer', 'gzip', 'bz2', 'zip', 'xz', None}, \
default 'infer'
    A string representing the compression to use in the output file. By
    default, infers from the file extension in specified path.

    .. versionadded:: 0.20.0
protocol : int
    Int which indicates which protocol should be used by the pickler,
    default HIGHEST_PROTOCOL (see [1]_ paragraph 12.1.2). The possible
    values are 0, 1, 2, 3, 4. A negative value for the protocol
    parameter is equivalent to setting its value to HIGHEST_PROTOCOL.

    .. [1] https://docs.python.org/3/library/pickle.html
    .. versionadded:: 0.21.0

See Also
--------
read_pickle : Load pickled pandas object (or any object) from file.
DataFrame.to_hdf : Write DataFrame to an HDF5 file.
DataFrame.to_sql : Write DataFrame to a SQL database.
DataFrame.to_parquet : Write a DataFrame to the binary parquet format.

Examples
--------
>>> original_df = pd.DataFrame({"foo": range(5), "bar": range(5, 10)})
>>> original_df
   foo  bar
0    0    5
1    1    6
2    2    7
3    3    8
4    4    9
>>> original_df.to_pickle("./dummy.pkl")

>>> unpickled_df = pd.read_pickle("./dummy.pkl")
>>> unpickled_df
   foo  bar
0    0    5
1    1    6
2    2    7
3    3    8
4    4    9

>>> import os
>>> os.remove("./dummy.pkl")