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Merge branch 'main' into depr-downcast-fillna
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jbrockmendel committed Sep 14, 2023
2 parents 991d95c + f00efd0 commit 4d3124c
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5 changes: 2 additions & 3 deletions .circleci/config.yml
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Expand Up @@ -48,7 +48,7 @@ jobs:
name: Build aarch64 wheels
no_output_timeout: 30m # Sometimes the tests won't generate any output, make sure the job doesn't get killed by that
command: |
pip3 install cibuildwheel==2.14.1
pip3 install cibuildwheel==2.15.0
cibuildwheel --prerelease-pythons --output-dir wheelhouse
environment:
CIBW_BUILD: << parameters.cibw-build >>
Expand Down Expand Up @@ -92,5 +92,4 @@ workflows:
only: /^v.*/
matrix:
parameters:
# TODO: Enable Python 3.12 wheels when numpy releases a version that supports Python 3.12
cibw-build: ["cp39-manylinux_aarch64", "cp310-manylinux_aarch64", "cp311-manylinux_aarch64"]#, "cp312-manylinux_aarch64"]
cibw-build: ["cp39-manylinux_aarch64", "cp310-manylinux_aarch64", "cp311-manylinux_aarch64", "cp312-manylinux_aarch64"]
8 changes: 4 additions & 4 deletions .github/workflows/code-checks.yml
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Expand Up @@ -33,7 +33,7 @@ jobs:

steps:
- name: Checkout
uses: actions/checkout@v3
uses: actions/checkout@v4
with:
fetch-depth: 0

Expand Down Expand Up @@ -109,7 +109,7 @@ jobs:

steps:
- name: Checkout
uses: actions/checkout@v3
uses: actions/checkout@v4
with:
fetch-depth: 0

Expand Down Expand Up @@ -143,7 +143,7 @@ jobs:
run: docker image prune -f

- name: Checkout
uses: actions/checkout@v3
uses: actions/checkout@v4
with:
fetch-depth: 0

Expand All @@ -164,7 +164,7 @@ jobs:

steps:
- name: Checkout
uses: actions/checkout@v3
uses: actions/checkout@v4
with:
fetch-depth: 0

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2 changes: 1 addition & 1 deletion .github/workflows/codeql.yml
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Expand Up @@ -27,7 +27,7 @@ jobs:
- python

steps:
- uses: actions/checkout@v3
- uses: actions/checkout@v4
- uses: github/codeql-action/init@v2
with:
languages: ${{ matrix.language }}
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2 changes: 1 addition & 1 deletion .github/workflows/comment-commands.yml
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Expand Up @@ -51,7 +51,7 @@ jobs:

steps:
- name: Checkout
uses: actions/checkout@v3
uses: actions/checkout@v4
with:
fetch-depth: 0

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2 changes: 1 addition & 1 deletion .github/workflows/docbuild-and-upload.yml
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Expand Up @@ -36,7 +36,7 @@ jobs:

steps:
- name: Checkout
uses: actions/checkout@v3
uses: actions/checkout@v4
with:
fetch-depth: 0

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4 changes: 2 additions & 2 deletions .github/workflows/package-checks.yml
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Expand Up @@ -34,7 +34,7 @@ jobs:

steps:
- name: Checkout
uses: actions/checkout@v3
uses: actions/checkout@v4
with:
fetch-depth: 0

Expand Down Expand Up @@ -62,7 +62,7 @@ jobs:
cancel-in-progress: true
steps:
- name: Checkout
uses: actions/checkout@v3
uses: actions/checkout@v4
with:
fetch-depth: 0

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6 changes: 3 additions & 3 deletions .github/workflows/unit-tests.yml
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Expand Up @@ -136,7 +136,7 @@ jobs:

steps:
- name: Checkout
uses: actions/checkout@v3
uses: actions/checkout@v4
with:
fetch-depth: 0

Expand Down Expand Up @@ -194,7 +194,7 @@ jobs:

steps:
- name: Checkout
uses: actions/checkout@v3
uses: actions/checkout@v4
with:
fetch-depth: 0

Expand Down Expand Up @@ -330,7 +330,7 @@ jobs:
PYTEST_TARGET: pandas

steps:
- uses: actions/checkout@v3
- uses: actions/checkout@v4
with:
fetch-depth: 0

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20 changes: 11 additions & 9 deletions .github/workflows/wheels.yml
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Expand Up @@ -48,7 +48,7 @@ jobs:
sdist_file: ${{ steps.save-path.outputs.sdist_name }}
steps:
- name: Checkout pandas
uses: actions/checkout@v3
uses: actions/checkout@v4
with:
fetch-depth: 0

Expand Down Expand Up @@ -97,14 +97,13 @@ jobs:
- [macos-12, macosx_*]
- [windows-2022, win_amd64]
# TODO: support PyPy?
# TODO: Enable Python 3.12 wheels when numpy releases a version that supports Python 3.12
python: [["cp39", "3.9"], ["cp310", "3.10"], ["cp311", "3.11"]]#, ["cp312", "3.12"]]
python: [["cp39", "3.9"], ["cp310", "3.10"], ["cp311", "3.11"], ["cp312", "3.12"]]
env:
IS_PUSH: ${{ github.event_name == 'push' && startsWith(github.ref, 'refs/tags/v') }}
IS_SCHEDULE_DISPATCH: ${{ github.event_name == 'schedule' || github.event_name == 'workflow_dispatch' }}
steps:
- name: Checkout pandas
uses: actions/checkout@v3
uses: actions/checkout@v4
with:
fetch-depth: 0

Expand Down Expand Up @@ -150,8 +149,10 @@ jobs:
uses: mamba-org/setup-micromamba@v1
with:
environment-name: wheel-env
# Use a fixed Python, since we might have an unreleased Python not
# yet present on conda-forge
create-args: >-
python=${{ matrix.python[1] }}
python=3.11
anaconda-client
wheel
cache-downloads: true
Expand All @@ -167,12 +168,13 @@ jobs:
shell: pwsh
run: |
$TST_CMD = @"
python -m pip install pytz six numpy python-dateutil tzdata>=2022.1 hypothesis>=6.46.1 pytest>=7.3.2 pytest-xdist>=2.2.0 pytest-asyncio>=0.17;
python -m pip install --find-links=pandas\wheelhouse --no-index pandas;
python -m pip install hypothesis>=6.46.1 pytest>=7.3.2 pytest-xdist>=2.2.0 pytest-asyncio>=0.17;
python -m pip install `$(Get-Item pandas\wheelhouse\*.whl);
python -c `'import pandas as pd; pd.test(extra_args=[\"`\"--no-strict-data-files`\"\", \"`\"-m not clipboard and not single_cpu and not slow and not network and not db`\"\"])`';
"@
docker pull python:${{ matrix.python[1] }}-windowsservercore
docker run --env PANDAS_CI='1' -v ${PWD}:C:\pandas python:${{ matrix.python[1] }}-windowsservercore powershell -Command $TST_CMD
# add rc to the end of the image name if the Python version is unreleased
docker pull python:${{ matrix.python[1] == '3.12' && '3.12-rc' || format('{0}-windowsservercore', matrix.python[1]) }}
docker run --env PANDAS_CI='1' -v ${PWD}:C:\pandas python:${{ matrix.python[1] == '3.12' && '3.12-rc' || format('{0}-windowsservercore', matrix.python[1]) }} powershell -Command $TST_CMD
- uses: actions/upload-artifact@v3
with:
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8 changes: 4 additions & 4 deletions .pre-commit-config.yaml
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Expand Up @@ -24,7 +24,7 @@ repos:
hooks:
- id: black
- repo: https://github.com/astral-sh/ruff-pre-commit
rev: v0.0.285
rev: v0.0.287
hooks:
- id: ruff
args: [--exit-non-zero-on-fix]
Expand All @@ -34,7 +34,7 @@ repos:
alias: ruff-selected-autofixes
args: [--select, "ANN001,ANN204", --fix-only, --exit-non-zero-on-fix]
- repo: https://github.com/jendrikseipp/vulture
rev: 'v2.7'
rev: 'v2.9.1'
hooks:
- id: vulture
entry: python scripts/run_vulture.py
Expand Down Expand Up @@ -84,7 +84,7 @@ repos:
'--filter=-readability/casting,-runtime/int,-build/include_subdir,-readability/fn_size'
]
- repo: https://github.com/pylint-dev/pylint
rev: v3.0.0a6
rev: v3.0.0a7
hooks:
- id: pylint
stages: [manual]
Expand Down Expand Up @@ -124,7 +124,7 @@ repos:
types: [text] # overwrite types: [rst]
types_or: [python, rst]
- repo: https://github.com/sphinx-contrib/sphinx-lint
rev: v0.6.7
rev: v0.6.8
hooks:
- id: sphinx-lint
- repo: local
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2 changes: 1 addition & 1 deletion asv_bench/benchmarks/array.py
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Expand Up @@ -90,7 +90,7 @@ def time_setitem(self, multiple_chunks):
self.array[i] = "foo"

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

def time_setitem_slice(self, multiple_chunks):
Expand Down
4 changes: 2 additions & 2 deletions asv_bench/benchmarks/join_merge.py
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Expand Up @@ -360,14 +360,14 @@ class MergeCategoricals:
def setup(self):
self.left_object = DataFrame(
{
"X": np.random.choice(range(0, 10), size=(10000,)),
"X": np.random.choice(range(10), size=(10000,)),
"Y": np.random.choice(["one", "two", "three"], size=(10000,)),
}
)

self.right_object = DataFrame(
{
"X": np.random.choice(range(0, 10), size=(10000,)),
"X": np.random.choice(range(10), size=(10000,)),
"Z": np.random.choice(["jjj", "kkk", "sss"], size=(10000,)),
}
)
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1 change: 1 addition & 0 deletions ci/deps/actions-310.yaml
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Expand Up @@ -46,6 +46,7 @@ dependencies:
- pymysql>=1.0.2
- pyreadstat>=1.1.5
- pytables>=3.7.0
- python-calamine>=0.1.6
- pyxlsb>=1.0.9
- s3fs>=2022.05.0
- scipy>=1.8.1
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1 change: 1 addition & 0 deletions ci/deps/actions-311-downstream_compat.yaml
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Expand Up @@ -47,6 +47,7 @@ dependencies:
- pymysql>=1.0.2
- pyreadstat>=1.1.5
- pytables>=3.7.0
- python-calamine>=0.1.6
- pyxlsb>=1.0.9
- s3fs>=2022.05.0
- scipy>=1.8.1
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1 change: 1 addition & 0 deletions ci/deps/actions-311.yaml
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Expand Up @@ -46,6 +46,7 @@ dependencies:
- pymysql>=1.0.2
- pyreadstat>=1.1.5
# - pytables>=3.7.0, 3.8.0 is first version that supports 3.11
- python-calamine>=0.1.6
- pyxlsb>=1.0.9
- s3fs>=2022.05.0
- scipy>=1.8.1
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1 change: 1 addition & 0 deletions ci/deps/actions-39-minimum_versions.yaml
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Expand Up @@ -48,6 +48,7 @@ dependencies:
- pymysql=1.0.2
- pyreadstat=1.1.5
- pytables=3.7.0
- python-calamine=0.1.6
- pyxlsb=1.0.9
- s3fs=2022.05.0
- scipy=1.8.1
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1 change: 1 addition & 0 deletions ci/deps/actions-39.yaml
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Expand Up @@ -46,6 +46,7 @@ dependencies:
- pymysql>=1.0.2
- pyreadstat>=1.1.5
- pytables>=3.7.0
- python-calamine>=0.1.6
- pyxlsb>=1.0.9
- s3fs>=2022.05.0
- scipy>=1.8.1
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1 change: 1 addition & 0 deletions ci/deps/circle-310-arm64.yaml
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Expand Up @@ -47,6 +47,7 @@ dependencies:
- pymysql>=1.0.2
# - pyreadstat>=1.1.5 not available on ARM
- pytables>=3.7.0
- python-calamine>=0.1.6
- pyxlsb>=1.0.9
- s3fs>=2022.05.0
- scipy>=1.8.1
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22 changes: 22 additions & 0 deletions doc/cheatsheet/README.md
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@@ -0,0 +1,22 @@
# Pandas Cheat Sheet

The Pandas Cheat Sheet was created using Microsoft Powerpoint 2013.
To create the PDF version, within Powerpoint, simply do a "Save As"
and pick "PDF" as the format.

This cheat sheet, originally written by Irv Lustig, [Princeton Consultants](https://www.princetonoptimization.com/), was inspired by the [RStudio Data Wrangling Cheatsheet](https://www.rstudio.com/wp-content/uploads/2015/02/data-wrangling-cheatsheet.pdf).

| Topic | PDF | PPT |
|------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Pandas_Cheat_Sheet | <a href="https://github.com/pandas-dev/pandas/blob/main/doc/cheatsheet/Pandas_Cheat_Sheet.pdf" target="_parent"><img src="https://img.shields.io/badge/Open in PDF-%23FF0000.svg?style=flat-square&logo=adobe&logoColor=white"/></a> | <a href="https://github.com/pandas-dev/pandas/blob/main/doc/cheatsheet/Pandas_Cheat_Sheet.pptx" target="_parent"><img src="https://img.shields.io/badge/Open in PPT-B7472A?style=flat-square&logo=microsoft-powerpoint&logoColor=white"/></a> |
| Pandas_Cheat_Sheet_JA | <a href="https://github.com/pandas-dev/pandas/blob/main/doc/cheatsheet/Pandas_Cheat_Sheet_JA.pdf" target="_parent"><img src="https://img.shields.io/badge/Open in PDF-%23FF0000.svg?style=flat-square&logo=adobe&logoColor=white"/></a> | <a href="https://github.com/pandas-dev/pandas/blob/main/doc/cheatsheet/Pandas_Cheat_Sheet_JA.pptx" target="_parent"><img src="https://img.shields.io/badge/Open in PPT-B7472A?style=flat-square&logo=microsoft-powerpoint&logoColor=white"/></a> |


**Alternative**

Alternatively, if you want to complement your learning, you can use the Pandas Cheat sheets
developed by [DataCamp](https://www.datacamp.com/) in "PDF", "Google Colab" and "Streamlit" formats.

| Topic | PDF | Streamlit | Google Colab |
|-------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Pandas | <a href="https://github.com/fralfaro/DS-Cheat-Sheets/blob/main/docs/files/pandas_cs.pdf" target="_parent"><img src="https://img.shields.io/badge/Open in PDF-%23FF0000.svg?style=flat-square&logo=adobe&logoColor=white"/></a> | <a href="https://ds-cheat-sheets-pandas.streamlit.app/" target="_parent"><img src="https://static.streamlit.io/badges/streamlit_badge_black_white.svg"/></a> | <a href="https://colab.research.google.com/github/fralfaro/DS-Cheat-Sheets/blob/main/docs/examples/pandas/pandas.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a> |
8 changes: 0 additions & 8 deletions doc/cheatsheet/README.txt

This file was deleted.

1 change: 1 addition & 0 deletions doc/source/getting_started/install.rst
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Expand Up @@ -281,6 +281,7 @@ xlrd 2.0.1 excel Reading Excel
xlsxwriter 3.0.3 excel Writing Excel
openpyxl 3.0.10 excel Reading / writing for xlsx files
pyxlsb 1.0.9 excel Reading for xlsb files
python-calamine 0.1.6 excel Reading for xls/xlsx/xlsb/ods files
========================= ================== =============== =============================================================

HTML
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Expand Up @@ -106,9 +106,9 @@ between square brackets ``[]``.
</ul>

.. note::
If you are familiar to Python
If you are familiar with Python
:ref:`dictionaries <python:tut-dictionaries>`, the selection of a
single column is very similar to selection of dictionary values based on
single column is very similar to the selection of dictionary values based on
the key.

You can create a ``Series`` from scratch as well:
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4 changes: 2 additions & 2 deletions doc/source/user_guide/cookbook.rst
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Expand Up @@ -459,7 +459,7 @@ Unlike agg, apply's callable is passed a sub-DataFrame which gives you access to
df
# List the size of the animals with the highest weight.
df.groupby("animal").apply(lambda subf: subf["size"][subf["weight"].idxmax()])
df.groupby("animal").apply(lambda subf: subf["size"][subf["weight"].idxmax()], include_groups=False)
`Using get_group
<https://stackoverflow.com/questions/14734533/how-to-access-pandas-groupby-dataframe-by-key>`__
Expand All @@ -482,7 +482,7 @@ Unlike agg, apply's callable is passed a sub-DataFrame which gives you access to
return pd.Series(["L", avg_weight, True], index=["size", "weight", "adult"])
expected_df = gb.apply(GrowUp)
expected_df = gb.apply(GrowUp, include_groups=False)
expected_df
`Expanding apply
Expand Down
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