7ff9d2e3ee
### What changes were proposed in this pull request? This PR proposes to rename Koalas to pandas-on-Spark in main codes ### Why are the changes needed? To have the correct name in PySpark. NOTE that the official name in the main documentation will be pandas APIs on Spark to be extra clear. pandas-on-Spark is not the official term. ### Does this PR introduce _any_ user-facing change? No, it's master-only change. It changes the docstring and class names. ### How was this patch tested? Manually tested via: ```bash ./python/run-tests --python-executable=python3 --modules pyspark-pandas ``` Closes #32166 from HyukjinKwon/rename-koalas. Authored-by: HyukjinKwon <gurwls223@apache.org> Signed-off-by: HyukjinKwon <gurwls223@apache.org>
60 lines
2 KiB
Python
60 lines
2 KiB
Python
#
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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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memory_usage = lambda f: f(
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"memory_usage",
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reason="Unlike pandas, most DataFrames are not materialized in memory in Spark "
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"(and pandas-on-Spark), and as a result memory_usage() does not do what you intend it "
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"to do. Use Spark's web UI to monitor disk and memory usage of your application.",
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)
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array = lambda f: f(
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"array", reason="If you want to collect your data as an NumPy array, use 'to_numpy()' instead."
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)
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to_pickle = lambda f: f(
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"to_pickle",
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reason="For storage, we encourage you to use Delta or Parquet, instead of Python pickle "
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"format.",
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)
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to_xarray = lambda f: f(
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"to_xarray",
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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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to_list = lambda f: f(
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"to_list",
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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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tolist = lambda f: f(
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"tolist", reason="If you want to collect your data as an NumPy array, use 'to_numpy()' instead."
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)
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__iter__ = lambda f: f(
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"__iter__",
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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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duplicated = lambda f: f(
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"duplicated",
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reason="'duplicated' API returns np.ndarray and the data size is too large."
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"You can just use DataFrame.deduplicated instead",
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)
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