deprecated as of 0.25 and will be removed in a future version. It is recommended to use pyarrow for on-the-wire transmission of pandas objects. (GH27084) 1.3.3 Other deprecations • The deprecated .ix[] indexer deprecated as of 0.25 and will be removed in a future version. It is recommended to use pyarrow for on-the-wire transmission of pandas objects. Warning: read_msgpack() is only guaranteed backwards compatible back suite of methods in order to have purely label based indexing. This is a strict inclusion based protocol. Every label asked for must be in the index, or a KeyError will be raised. When slicing, both the

deprecated as of 0.25 and will be removed in a future version. It is recommended to use pyarrow for on-the-wire transmission of pandas objects. (GH27084) 1.3.3 Other deprecations • The deprecated .ix[] indexer deprecated as of 0.25 and will be removed in a future version. It is recommended to use pyarrow for on-the-wire transmission of pandas objects. Warning: read_msgpack() is only guaranteed backwards compatible back suite of methods in order to have purely label based indexing. This is a strict inclusion based protocol. Every label asked for must be in the index, or a KeyError will be raised. When slicing, both the

support for msgpack has been removed in version 1.0.0. It is recommended to use pyarrow for on-the-wire transmission of pandas objects. Example pyarrow usage: >>> import pandas as pd >>> import pyarrow suite of methods in order to have purely label based indexing. This is a strict inclusion based protocol. Every label asked for must be in the index, or a KeyError will be raised. When slicing, both the Using if/truth statements with pandas. NumPy ufuncs pandas.NA implements NumPy’s __array_ufunc__ protocol. Most ufuncs work with NA, and generally return NA: In [168]: np.log(pd.NA) Out[168]: In

also be a dict in order to pass options to the compression protocol. It must have a 'method' key set to the name of the compression protocol, which must be one of {'zip', 'gzip', 'bz2'}. All other key-value 361779 999 -1.197988 Name: A, Length: 1000, dtype: float64 Passing options to the compression protocol in order to speed up compression: In [345]: df.to_pickle( .....: "data.pkl.gz", .....: compression={"method": support for msgpack has been removed in version 1.0.0. It is recommended to use pyarrow for on-the-wire transmission of pandas objects. Example pyarrow usage: >>> import pandas as pd >>> import pyarrow

also be a dict in order to pass options to the compression protocol. It must have a 'method' key set to the name of the compression protocol, which must be one of {'zip', 'gzip', 'bz2'}. All other key-value 361779 999 -1.197988 Name: A, Length: 1000, dtype: float64 Passing options to the compression protocol in order to speed up compression: In [345]: df.to_pickle( .....: "data.pkl.gz", .....: compression={"method": support for msgpack has been removed in version 1.0.0. It is recommended to use pyarrow for on-the-wire transmission of pandas objects. Example pyarrow usage: >>> import pandas as pd >>> import pyarrow

also be a dict in order to pass options to the compression protocol. It must have a 'method' key set to the name of the compression protocol, which must be one of {'zip', 'gzip', 'bz2'}. All other key-value 361779 999 -1.197988 Name: A, Length: 1000, dtype: float64 Passing options to the compression protocol in order to speed up compression: In [344]: df.to_pickle("data.pkl.gz", compression={"method": support for msgpack has been removed in version 1.0.0. It is recommended to use pyarrow for on-the-wire transmission of pandas objects. Example pyarrow usage: import pandas as pd import pyarrow as pa

also be a dict in order to pass options to the compression protocol. It must have a 'method' key set to the name of the compression protocol, which must be one of {'zip', 'gzip', 'bz2'}. All other key-value 361779 999 -1.197988 Name: A, Length: 1000, dtype: float64 Passing options to the compression protocol in order to speed up compression: In [393]: df.to_pickle("data.pkl.gz", compression={"method": to use pickle instead. Alternatively, you can also the Arrow IPC serialization format for on-the-wire transmission of pandas objects. For documentation on pyarrow, see here. 2.4.12 HDF5 (PyTables) HDFStore

also be a dict in order to pass options to the compression protocol. It must have a 'method' key set to the name of the compression protocol, which must be one of {'zip', 'gzip', 'bz2'}. All other key-value 361779 999 -1.197988 Name: A, Length: 1000, dtype: float64 Passing options to the compression protocol in order to speed up compression: In [393]: df.to_pickle("data.pkl.gz", compression={"method": to use pickle instead. Alternatively, you can also the Arrow IPC serialization format for on-the-wire transmission of pandas objects. For documentation on pyarrow, see here. 2.4.12 HDF5 (PyTables) HDFStore

also be a dict in order to pass options to the compression protocol. It must have a 'method' key set to the name of the compression protocol, which must be one of {'zip', 'gzip', 'bz2'}. All other key-value 361779 999 -1.197988 Name: A, Length: 1000, dtype: float64 Passing options to the compression protocol in order to speed up compression: In [393]: df.to_pickle("data.pkl.gz", compression={"method": to use pickle instead. Alternatively, you can also the Arrow IPC serialization format for on-the-wire transmission of pandas objects. For documentation on pyarrow, see here. 2.4.12 HDF5 (PyTables) HDFStore

support for msgpack has been removed in version 1.0.0. It is recommended to use pyarrow for on-the-wire transmission of pandas objects. Example pyarrow usage: >>> import pandas as pd >>> import pyarrow suite of methods in order to have purely label based indexing. This is a strict inclusion based protocol. Every label asked for must be in the index, or a KeyError will be raised. When slicing, both the Using if/truth statements with pandas. NumPy ufuncs pandas.NA implements NumPy’s __array_ufunc__ protocol. Most ufuncs work with NA, and generally return NA: In [168]: np.log(pd.NA) Out[168]: In