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.circleci/config.yml

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version: 2
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jobs:
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# --------------------------------------------------------------------------
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# 1. py36_locale
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# --------------------------------------------------------------------------
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py36_locale:
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docker:
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- image: continuumio/miniconda:latest
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# databases configuration
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- image: circleci/postgres:9.6.5-alpine-ram
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environment:
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POSTGRES_USER: postgres
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POSTGRES_DB: pandas_nosetest
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- image: circleci/mysql:8-ram
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environment:
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MYSQL_USER: "root"
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MYSQL_HOST: "localhost"
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MYSQL_ALLOW_EMPTY_PASSWORD: "true"
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MYSQL_DATABASE: "pandas_nosetest"
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environment:
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JOB: "3.6_LOCALE"
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ENV_FILE: "ci/circle-36-locale.yaml"
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LOCALE_OVERRIDE: "zh_CN.UTF-8"
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MINICONDA_DIR: /home/ubuntu/miniconda3
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steps:
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- checkout
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- run:
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name: build
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command: |
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./ci/circle/install_circle.sh
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./ci/circle/show_circle.sh
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- run:
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name: test
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command: ./ci/circle/run_circle.sh --skip-slow --skip-network
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workflows:
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version: 2
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build_and_test:
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jobs:
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- py36_locale

.coveragerc

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This file was deleted.

.gitignore

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@@ -62,6 +62,8 @@ dist
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coverage.xml
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coverage_html_report
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*.pytest_cache
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# hypothesis test database
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.hypothesis/
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# OS generated files #
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######################

.pep8speaks.yml

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scanner:
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diff_only: True # If True, errors caused by only the patch are shown
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6+
# Opened issue in pep8speaks, so we can directly use the config in setup.cfg
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# (and avoid having to duplicate it here):
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# https://github.com/OrkoHunter/pep8speaks/issues/95
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610
pycodestyle:
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max-line-length: 79
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ignore: # Errors and warnings to ignore
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ignore:
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- W503, # line break before binary operator
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- W504, # line break after binary operator
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- E402, # module level import not at top of file
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- E722, # do not use bare except
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- E731, # do not assign a lambda expression, use a def
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- E741, # do not use variables named 'l', 'O', or 'I'
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- W503 # line break before binary operator
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- C406, # Unnecessary list literal - rewrite as a dict literal.
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- C408, # Unnecessary dict call - rewrite as a literal.
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- C409 # Unnecessary list passed to tuple() - rewrite as a tuple literal.

.travis.yml

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@@ -30,12 +30,8 @@ matrix:
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exclude:
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# Exclude the default Python 3.5 build
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- python: 3.5
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include:
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- os: osx
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language: generic
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env:
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- JOB="3.5, OSX" ENV_FILE="ci/travis-35-osx.yaml" TEST_ARGS="--skip-slow --skip-network"
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include:
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- dist: trusty
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env:
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- JOB="3.7" ENV_FILE="ci/travis-37.yaml" TEST_ARGS="--skip-slow --skip-network"
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- language-pack-zh-hans
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- dist: trusty
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env:
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- JOB="2.7, lint" ENV_FILE="ci/travis-27.yaml" TEST_ARGS="--skip-slow" LINT=true
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- JOB="2.7" ENV_FILE="ci/travis-27.yaml" TEST_ARGS="--skip-slow"
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addons:
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apt:
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packages:
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- python-gtk2
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- dist: trusty
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env:
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- JOB="3.6, coverage" ENV_FILE="ci/travis-36.yaml" TEST_ARGS="--skip-slow --skip-network" PANDAS_TESTING_MODE="deprecate" COVERAGE=true
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# In allow_failures
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- dist: trusty
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env:
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- JOB="3.6, slow" ENV_FILE="ci/travis-36-slow.yaml" SLOW=true
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# In allow_failures
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- JOB="3.6, lint, coverage" ENV_FILE="ci/travis-36.yaml" TEST_ARGS="--skip-slow --skip-network" PANDAS_TESTING_MODE="deprecate" COVERAGE=true LINT=true
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- dist: trusty
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env:
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- JOB="3.6, NumPy dev" ENV_FILE="ci/travis-36-numpydev.yaml" TEST_ARGS="--skip-slow --skip-network" PANDAS_TESTING_MODE="deprecate"
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- JOB="3.7, NumPy dev" ENV_FILE="ci/travis-37-numpydev.yaml" TEST_ARGS="--skip-slow --skip-network -W error" PANDAS_TESTING_MODE="deprecate"
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addons:
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apt:
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packages:
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- xsel
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# In allow_failures
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- dist: trusty
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env:
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- JOB="3.6, slow" ENV_FILE="ci/travis-36-slow.yaml" SLOW=true
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# In allow_failures
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- dist: trusty
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env:
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- dist: trusty
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env:
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- JOB="3.6, slow" ENV_FILE="ci/travis-36-slow.yaml" SLOW=true
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- dist: trusty
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env:
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- JOB="3.6, NumPy dev" ENV_FILE="ci/travis-36-numpydev.yaml" TEST_ARGS="--skip-slow --skip-network" PANDAS_TESTING_MODE="deprecate"
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addons:
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apt:
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packages:
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- xsel
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- dist: trusty
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env:
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- JOB="3.6, doc" ENV_FILE="ci/travis-36-doc.yaml" DOC=true
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- ci/run_build_docs.sh
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- ci/script_single.sh
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- ci/script_multi.sh
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- ci/lint.sh
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- echo "checking imports"
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- source activate pandas && python ci/check_imports.py
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- echo "script done"
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- ci/code_checks.sh
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after_success:
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- ci/upload_coverage.sh
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after_script:
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- echo "after_script start"
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- source activate pandas && pushd /tmp && python -c "import pandas; pandas.show_versions();" && popd
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- if [ -e /tmp/single.xml ]; then
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ci/print_skipped.py /tmp/single.xml;
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- if [ -e test-data-single.xml ]; then
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ci/print_skipped.py test-data-single.xml;
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fi
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- if [ -e /tmp/multiple.xml ]; then
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ci/print_skipped.py /tmp/multiple.xml;
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- if [ -e test-data-multiple.xml ]; then
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ci/print_skipped.py test-data-multiple.xml;
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fi
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- echo "after_script done"

Makefile

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python setup.py build_ext --inplace
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lint-diff:
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git diff master --name-only -- "*.py" | grep "pandas" | xargs flake8
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git diff master --name-only -- "*.py" | grep -E "pandas|scripts" | xargs flake8
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develop: build
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-python setup.py develop

README.md

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<tr>
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<td></td>
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<td>
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<a href="https://ci.appveyor.com/project/pandas-dev/pandas">
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<img src="https://ci.appveyor.com/api/projects/status/86vn83mxgnl4xf1s/branch/master?svg=true" alt="appveyor build status" />
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<a href="https://dev.azure.com/pandas-dev/pandas/_build/latest?definitionId=1&branch=master">
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<img src="https://dev.azure.com/pandas-dev/pandas/_apis/build/status/pandas-dev.pandas?branch=master" alt="Azure Pipelines build status" />
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</a>
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</td>
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</tr>
@@ -89,15 +89,15 @@
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## What is it
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## What is it?
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**pandas** is a Python package providing fast, flexible, and expressive data
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structures designed to make working with "relational" or "labeled" data both
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easy and intuitive. It aims to be the fundamental high-level building block for
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doing practical, **real world** data analysis in Python. Additionally, it has
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the broader goal of becoming **the most powerful and flexible open source data
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analysis / manipulation tool available in any language**. It is already well on
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its way toward this goal.
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its way towards this goal.
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## Main Features
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Here are just a few of the things that pandas does well:

appveyor.yml

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asv_bench/benchmarks/algorithms.py

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try:
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hashing = import_module(imp)
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break
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except:
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except (ImportError, TypeError, ValueError):
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pass
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15-
from .pandas_vb_common import setup # noqa
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1816
class Factorize(object):
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20-
goal_time = 0.2
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params = [True, False]
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param_names = ['sort']
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4137
class Duplicated(object):
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goal_time = 0.2
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params = ['first', 'last', False]
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param_names = ['keep']
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6458
class DuplicatedUniqueIndex(object):
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66-
goal_time = 0.2
67-
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def setup(self):
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N = 10**5
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self.idx_int_dup = pd.Int64Index(np.arange(N * 5))
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7870
class Match(object):
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80-
goal_time = 0.2
81-
8272
def setup(self):
8373
self.uniques = tm.makeStringIndex(1000).values
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self.all = self.uniques.repeat(10)
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9080

9181
class Hashing(object):
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93-
goal_time = 0.2
94-
9583
def setup_cache(self):
9684
N = 10**5
9785

@@ -126,3 +114,6 @@ def time_series_timedeltas(self, df):
126114

127115
def time_series_dates(self, df):
128116
hashing.hash_pandas_object(df['dates'])
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119+
from .pandas_vb_common import setup # noqa: F401

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