Parameters values [sequence] A 1-D sequence. Sequences that aren’t pandas objects are coerced to ndar- rays before factorization. sort [bool, default False] Sort uniques and shuffle labels to maintain valid value. A negative value for the protocol parameter is equivalent to setting its value to HIGH- EST_PROTOCOL. New in version 0.21.0. See also: read_pickle Load pickled pandas object (or any object) valid value. A negative value for the protocol parameter is equivalent to setting its value to HIGH- EST_PROTOCOL. New in version 0.21.0. See also: read_pickle Load pickled pandas object (or any object)

) Compute NDFrame with “consolidated” internals (data of each dtype grouped together in a single ndar- ray). Mainly an internal API function, but available here to the savvy user Parameters inplace : ) Compute NDFrame with “consolidated” internals (data of each dtype grouped together in a single ndar- ray). Mainly an internal API function, but available here to the savvy user Parameters inplace : ) Compute NDFrame with “consolidated” internals (data of each dtype grouped together in a single ndar- ray). Mainly an internal API function, but available here to the savvy user Parameters inplace :

) Compute NDFrame with “consolidated” internals (data of each dtype grouped together in a single ndar- ray). Mainly an internal API function, but available here to the savvy user Parameters inplace : ) Compute NDFrame with “consolidated” internals (data of each dtype grouped together in a single ndar- ray). Mainly an internal API function, but available here to the savvy user Parameters inplace : ) Compute NDFrame with “consolidated” internals (data of each dtype grouped together in a single ndar- ray). Mainly an internal API function, but available here to the savvy user Parameters inplace :

) Compute NDFrame with “consolidated” internals (data of each dtype grouped together in a single ndar- ray). Mainly an internal API function, but available here to the savvy user Parameters inplace : ) Compute NDFrame with “consolidated” internals (data of each dtype grouped together in a single ndar- ray). Mainly an internal API function, but available here to the savvy user Parameters inplace : ) Compute NDFrame with “consolidated” internals (data of each dtype grouped together in a single ndar- ray). Mainly an internal API function, but available here to the savvy user Parameters inplace :

) Compute NDFrame with “consolidated” internals (data of each dtype grouped together in a single ndar- ray). Mainly an internal API function, but available here to the savvy user Parameters inplace : ) Compute NDFrame with “consolidated” internals (data of each dtype grouped together in a single ndar- ray). Mainly an internal API function, but available here to the savvy user Parameters inplace : ) Compute NDFrame with “consolidated” internals (data of each dtype grouped together in a single ndar- ray). Mainly an internal API function, but available here to the savvy user Parameters inplace :

) Compute NDFrame with “consolidated” internals (data of each dtype grouped together in a single ndar- ray). Mainly an internal API function, but available here to the savvy user Parameters inplace : ) Compute NDFrame with “consolidated” internals (data of each dtype grouped together in a single ndar- ray). Mainly an internal API function, but available here to the savvy user Parameters inplace : ) Compute NDFrame with “consolidated” internals (data of each dtype grouped together in a single ndar- ray). Mainly an internal API function, but available here to the savvy user Parameters inplace :

default HIGH- EST_PROTOCOL (see [1] paragraph 12.1.2). The possible values are 0, 1, 2, 3, 4, 5. A negative value for the protocol parameter is equivalent to setting its value to HIGH- EST_PROTOCOL. storage_options Parameters values [sequence] A 1-D sequence. Sequences that aren’t pandas objects are coerced to ndar- rays before factorization. sort [bool, default False] Sort uniques and shuffle codes to maintain cases, this should return a NumPy ndarray. For exceptional cases like SparseArray, where returning an ndar- ray would be expensive, an ExtensionArray may be returned. Notes If returning an ExtensionArray

default HIGH- EST_PROTOCOL (see [1] paragraph 12.1.2). The possible values are 0, 1, 2, 3, 4, 5. A negative value for the protocol parameter is equivalent to setting its value to HIGH- EST_PROTOCOL. storage_options Parameters values [sequence] A 1-D sequence. Sequences that aren’t pandas objects are coerced to ndar- rays before factorization. sort [bool, default False] Sort uniques and shuffle codes to maintain cases, this should return a NumPy ndarray. For exceptional cases like SparseArray, where returning an ndar- ray would be expensive, an ExtensionArray may be returned. 3.15. Extensions 2771 pandas: powerful

default HIGH- EST_PROTOCOL (see [1] paragraph 12.1.2). The possible values are 0, 1, 2, 3, 4, 5. A negative value for the protocol parameter is equivalent to setting its value to HIGH- EST_PROTOCOL. storage_options Parameters values [sequence] A 1-D sequence. Sequences that aren’t pandas objects are coerced to ndar- rays before factorization. sort [bool, default False] Sort uniques and shuffle codes to maintain cases, this should return a NumPy ndarray. For exceptional cases like SparseArray, where returning an ndar- ray would be expensive, an ExtensionArray may be returned. 3.15. Extensions 2773 pandas: powerful

) Compute NDFrame with “consolidated” internals (data of each dtype grouped together in a single ndar- ray). Mainly an internal API function, but available here to the savvy user Parameters inplace : ) Compute NDFrame with “consolidated” internals (data of each dtype grouped together in a single ndar- ray). Mainly an internal API function, but available here to the savvy user 35.5. Panel 1441 pandas: ) Compute NDFrame with “consolidated” internals (data of each dtype grouped together in a single ndar- ray). Mainly an internal API function, but available here to the savvy user Parameters inplace :