126 lines
5.8 KiB
Python
126 lines
5.8 KiB
Python
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#
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# Licensed to the Apache Software Foundation (ASF) under one or more
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# contributor license agreements. See the NOTICE file distributed with
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# this work for additional information regarding copyright ownership.
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# The ASF licenses this file to You under the Apache License, Version 2.0
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# (the "License"); you may not use this file except in compliance with
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# the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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from distutils.version import LooseVersion
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import pandas as pd
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from pyspark.pandas.missing import unsupported_function, unsupported_property, common
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def _unsupported_function(method_name, deprecated=False, reason=""):
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return unsupported_function(
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class_name="pd.Series", method_name=method_name, deprecated=deprecated, reason=reason
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)
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def _unsupported_property(property_name, deprecated=False, reason=""):
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return unsupported_property(
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class_name="pd.Series", property_name=property_name, deprecated=deprecated, reason=reason
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)
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class MissingPandasLikeSeries(object):
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# Functions
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asfreq = _unsupported_function("asfreq")
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autocorr = _unsupported_function("autocorr")
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combine = _unsupported_function("combine")
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convert_dtypes = _unsupported_function("convert_dtypes")
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cov = _unsupported_function("cov")
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ewm = _unsupported_function("ewm")
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infer_objects = _unsupported_function("infer_objects")
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interpolate = _unsupported_function("interpolate")
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reorder_levels = _unsupported_function("reorder_levels")
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resample = _unsupported_function("resample")
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searchsorted = _unsupported_function("searchsorted")
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set_axis = _unsupported_function("set_axis")
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slice_shift = _unsupported_function("slice_shift")
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to_hdf = _unsupported_function("to_hdf")
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to_period = _unsupported_function("to_period")
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to_sql = _unsupported_function("to_sql")
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to_timestamp = _unsupported_function("to_timestamp")
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tshift = _unsupported_function("tshift")
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tz_convert = _unsupported_function("tz_convert")
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tz_localize = _unsupported_function("tz_localize")
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view = _unsupported_function("view")
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# Deprecated functions
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convert_objects = _unsupported_function("convert_objects", deprecated=True)
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nonzero = _unsupported_function("nonzero", deprecated=True)
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reindex_axis = _unsupported_function("reindex_axis", deprecated=True)
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select = _unsupported_function("select", deprecated=True)
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get_values = _unsupported_function("get_values", deprecated=True)
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# Properties we won't support.
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array = common.array(_unsupported_property)
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duplicated = common.duplicated(_unsupported_property)
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nbytes = _unsupported_property(
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"nbytes",
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reason="'nbytes' requires to compute whole dataset. You can calculate manually it, "
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"with its 'itemsize', by explicitly executing its count. Use Spark's web UI "
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"to monitor disk and memory usage of your application in general.",
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)
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# Functions we won't support.
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memory_usage = common.memory_usage(_unsupported_function)
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to_pickle = common.to_pickle(_unsupported_function)
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to_xarray = common.to_xarray(_unsupported_function)
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__iter__ = common.__iter__(_unsupported_function)
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ravel = _unsupported_function(
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"ravel",
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reason="If you want to collect your flattened underlying data as an NumPy array, "
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"use 'to_numpy().ravel()' instead.",
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)
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if LooseVersion(pd.__version__) < LooseVersion("1.0"):
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# Deprecated properties
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blocks = _unsupported_property("blocks", deprecated=True)
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ftypes = _unsupported_property("ftypes", deprecated=True)
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ftype = _unsupported_property("ftype", deprecated=True)
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is_copy = _unsupported_property("is_copy", deprecated=True)
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ix = _unsupported_property("ix", deprecated=True)
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asobject = _unsupported_property("asobject", deprecated=True)
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strides = _unsupported_property("strides", deprecated=True)
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imag = _unsupported_property("imag", deprecated=True)
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itemsize = _unsupported_property("itemsize", deprecated=True)
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data = _unsupported_property("data", deprecated=True)
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base = _unsupported_property("base", deprecated=True)
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flags = _unsupported_property("flags", deprecated=True)
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# Deprecated functions
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as_blocks = _unsupported_function("as_blocks", deprecated=True)
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as_matrix = _unsupported_function("as_matrix", deprecated=True)
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clip_lower = _unsupported_function("clip_lower", deprecated=True)
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clip_upper = _unsupported_function("clip_upper", deprecated=True)
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compress = _unsupported_function("compress", deprecated=True)
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get_ftype_counts = _unsupported_function("get_ftype_counts", deprecated=True)
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get_value = _unsupported_function("get_value", deprecated=True)
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set_value = _unsupported_function("set_value", deprecated=True)
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valid = _unsupported_function("valid", deprecated=True)
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to_dense = _unsupported_function("to_dense", deprecated=True)
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to_sparse = _unsupported_function("to_sparse", deprecated=True)
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to_msgpack = _unsupported_function("to_msgpack", deprecated=True)
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compound = _unsupported_function("compound", deprecated=True)
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put = _unsupported_function("put", deprecated=True)
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ptp = _unsupported_function("ptp", deprecated=True)
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# Functions we won't support.
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real = _unsupported_property(
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"real",
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reason="If you want to collect your data as an NumPy array, use 'to_numpy()' instead.",
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)
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