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MarcoGorelli
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Merge remote-tracking branch 'upstream/main' into pt1-deprecate-ban-upcasting
2 parents 9b9e975 + 1d8b188 commit 2f980c6

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.circleci/config.yml

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@@ -14,7 +14,10 @@ jobs:
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steps:
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- checkout
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- run: .circleci/setup_env.sh
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- run: PATH=$HOME/miniconda3/envs/pandas-dev/bin:$HOME/miniconda3/condabin:$PATH ci/run_tests.sh
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- run: >
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PATH=$HOME/miniconda3/envs/pandas-dev/bin:$HOME/miniconda3/condabin:$PATH
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LD_PRELOAD=$HOME/miniconda3/envs/pandas-dev/lib/libgomp.so.1:$LD_PRELOAD
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ci/run_tests.sh
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workflows:
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test:

.github/ISSUE_TEMPLATE/bug_report.yaml

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@@ -17,7 +17,9 @@ body:
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[latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
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required: true
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- label: >
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I have confirmed this bug exists on the main branch of pandas.
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I have confirmed this bug exists on the
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[main branch](https://pandas.pydata.org/docs/dev/getting_started/install.html#installing-the-development-version-of-pandas)
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of pandas.
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- type: textarea
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id: example
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attributes:

.github/workflows/docbuild-and-upload.yml

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- name: Build Pandas
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uses: ./.github/actions/build_pandas
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- name: Set up maintainers cache
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uses: actions/cache@v3
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with:
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path: maintainers.json
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key: maintainers
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- name: Build website
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run: python web/pandas_web.py web/pandas --target-path=web/build
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.github/workflows/macos-windows.yml

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strategy:
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matrix:
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os: [macos-latest, windows-latest]
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env_file: [actions-38.yaml, actions-39.yaml, actions-310.yaml]
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env_file: [actions-38.yaml, actions-39.yaml, actions-310.yaml, actions-311.yaml]
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fail-fast: false
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runs-on: ${{ matrix.os }}
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name: ${{ format('{0} {1}', matrix.os, matrix.env_file) }}

.github/workflows/python-dev.yml

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@@ -23,12 +23,14 @@ name: Python Dev
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on:
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push:
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branches:
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- main
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- 1.5.x
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# - main
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# - 1.5.x
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- None
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pull_request:
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branches:
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- main
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- 1.5.x
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# - main
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# - 1.5.x
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- None
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paths-ignore:
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- "doc/**"
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.github/workflows/sdist.yml

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- name: Import pandas
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run: |
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cd ..
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conda list
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python -c "import pandas; pandas.show_versions();"

.github/workflows/ubuntu.yml

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timeout-minutes: 180
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strategy:
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matrix:
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env_file: [actions-38.yaml, actions-39.yaml, actions-310.yaml]
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env_file: [actions-38.yaml, actions-39.yaml, actions-310.yaml, actions-311.yaml]
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pattern: ["not single_cpu", "single_cpu"]
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pyarrow_version: ["7", "8", "9", "10"]
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include:
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env_file: actions-pypy-38.yaml
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pattern: "not slow and not network and not single_cpu"
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test_args: "--max-worker-restart 0"
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error_on_warnings: "0"
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- name: "Numpy Dev"
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env_file: actions-310-numpydev.yaml
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pattern: "not slow and not network and not single_cpu"
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test_args: "-W error::DeprecationWarning:numpy -W error::FutureWarning:numpy"
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test_args: "-W error::DeprecationWarning -W error::FutureWarning"
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error_on_warnings: "0"
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exclude:
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- env_file: actions-38.yaml
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pyarrow_version: "8"
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- env_file: actions-39.yaml
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pyarrow_version: "9"
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- env_file: actions-311.yaml
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pyarrow_version: "7"
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- env_file: actions-311.yaml
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pyarrow_version: "8"
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- env_file: actions-311.yaml
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pyarrow_version: "9"
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fail-fast: false
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name: ${{ matrix.name || format('{0} pyarrow={1} {2}', matrix.env_file, matrix.pyarrow_version, matrix.pattern) }}
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env:

.pre-commit-config.yaml

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types: [python]
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files: ^pandas/tests
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language: python
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exclude: |
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(?x)
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^pandas/tests/generic/test_generic.py # GH50380

asv_bench/benchmarks/array.py

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@@ -93,7 +93,7 @@ def time_setitem(self, multiple_chunks):
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self.array[i] = "foo"
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def time_setitem_list(self, multiple_chunks):
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indexer = list(range(0, 50)) + list(range(-50, 0))
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indexer = list(range(0, 50)) + list(range(-1000, 0, 50))
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self.array[indexer] = ["foo"] * len(indexer)
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def time_setitem_slice(self, multiple_chunks):

asv_bench/benchmarks/io/hdf.py

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@@ -128,9 +128,17 @@ def setup(self, format):
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self.df["object"] = tm.makeStringIndex(N)
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self.df.to_hdf(self.fname, "df", format=format)
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# Numeric df
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self.df1 = self.df.copy()
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self.df1 = self.df1.reset_index()
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self.df1.to_hdf(self.fname, "df1", format=format)
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def time_read_hdf(self, format):
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read_hdf(self.fname, "df")
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def peakmem_read_hdf(self, format):
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read_hdf(self.fname, "df")
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def time_write_hdf(self, format):
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self.df.to_hdf(self.fname, "df", format=format)
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asv_bench/benchmarks/io/json.py

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class ToJSONMem:
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def setup_cache(self):
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df = DataFrame([[1]])
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frames = {"int": df, "float": df.astype(float)}
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df2 = DataFrame(range(8), date_range("1/1/2000", periods=8, freq="T"))
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frames = {"int": df, "float": df.astype(float), "datetime": df2}
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return frames
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for _ in range(100_000):
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df.to_json()
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def peakmem_time(self, frames):
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df = frames["datetime"]
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for _ in range(10_000):
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df.to_json(orient="table")
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from ..pandas_vb_common import setup # noqa: F401 isort:skip

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