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Merge remote-tracking branch 'repo_org/master' into check_np_pd_fromExamples
* repo_org/master: (66 commits) CLN: doc string (pandas-dev#23469) DOC: Add cookbook entry for triangular correlation matrix (GH22840) (pandas-dev#23032) add number of Errors, Warnings to scripts/validate_docstrings.py (pandas-dev#23150) BUG: Allow freq conversion from dt64 to period (pandas-dev#23460) ENH: Add FrozenList.union and .difference (pandas-dev#23394) REF: cython cleanup, typing, optimizations (pandas-dev#23464) strictness and checks for Timedelta _simple_new (pandas-dev#23433) Fixing flake8 problems new to flake8 3.6.0 (pandas-dev#23472) DOC: Updating the docstring of Series.dot (pandas-dev#22890) TST: Fixturize series/test_analytics.py (pandas-dev#22755) BUG/ENH: Handle NonexistentTimeError in date rounding (pandas-dev#23406) PERF: speed up concat on Series by making _get_axis_number() a classmethod (pandas-dev#23404) REF: Remove DatetimelikeArrayMixin._shallow_copy (pandas-dev#23430) REF: strictness/simplification in DatetimeArray/Index _simple_new (pandas-dev#23431) REF: cython cleanup, typing, optimizations (pandas-dev#23456) TST: tweak Hypothesis configuration and idioms (pandas-dev#23441) BUG: fix HDFStore.append with all empty strings error (GH12242) (pandas-dev#23435) TST: Skip 32bit failing IntervalTree tests (pandas-dev#23442) BUG: Deprecate nthreads argument (pandas-dev#23112) style: fix import format at pandas/core/reshape (pandas-dev#23387) ...
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‎ci/azure-36-locale_slow.yaml

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- nomkl
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- numexpr
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- numpy
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- openpyxl=2.5.5
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- openpyxl
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- psycopg2
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- pymysql
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- pytables

‎ci/azure-37-locale.yaml

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- nomkl
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- numexpr
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- numpy
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- openpyxl=2.5.5
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- openpyxl
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- psycopg2
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- pymysql
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- pytables

‎ci/azure-macos-35.yaml

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- nomkl
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- numexpr
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- numpy=1.12.0
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- openpyxl=2.5.5
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- openpyxl
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- pytables
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- python=3.5*
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- pytz

‎ci/azure-windows-27.yaml

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- matplotlib=2.0.1
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- numexpr
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- numpy=1.12*
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- openpyxl=2.5.5
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- openpyxl
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- pytables
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- python=2.7.*
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- pytz

‎ci/azure-windows-36.yaml

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- bottleneck
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- boost-cpp<1.67
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- fastparquet
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- feather-format
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- matplotlib
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- numexpr
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- numpy=1.14*
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- openpyxl=2.5.5
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- openpyxl
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- parquet-cpp
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- pyarrow
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- pytables

‎ci/azure/windows-py27.yml

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displayName: 'Build'
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- script: |
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call activate %CONDA_ENV%
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pytest --junitxml=test-data.xml --skip-slow --skip-network pandas -n 2 -r sxX --strict %*
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pytest --junitxml=test-data.xml --skip-slow --skip-network pandas -n 2 -r sxX --strict --durations=10 %*
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displayName: 'Test'
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- task: PublishTestResults@2
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inputs:

‎ci/azure/windows.yml

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displayName: 'Build'
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- script: |
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call activate %CONDA_ENV%
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pytest --junitxml=test-data.xml --skip-slow --skip-network pandas -n 2 -r sxX --strict %*
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pytest --junitxml=test-data.xml --skip-slow --skip-network pandas -n 2 -r sxX --strict --durations=10 %*
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displayName: 'Test'
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- task: PublishTestResults@2
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inputs:

‎ci/circle-36-locale.yaml

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- nomkl
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- numexpr
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- numpy
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- openpyxl=2.5.5
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- openpyxl
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- psycopg2
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- pymysql
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- pytables

‎ci/circle/run_circle.sh

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source activate pandas
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echo "pytest --strict --junitxml=$CIRCLE_TEST_REPORTS/reports/junit.xml $@ pandas"
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pytest --strict --color=no --junitxml=$CIRCLE_TEST_REPORTS/reports/junit.xml $@ pandas
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echo "pytest --strict --durations=10 --color=no --junitxml=$CIRCLE_TEST_REPORTS/reports/junit.xml $@ pandas"
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pytest --strict --durations=10 --color=no --junitxml=$CIRCLE_TEST_REPORTS/reports/junit.xml $@ pandas

‎ci/requirements-optional-conda.txt

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blosc
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bottleneck>=1.2.0
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fastparquet
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feather-format
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gcsfs
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html5lib
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ipython>=5.6.0
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matplotlib>=2.0.0
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nbsphinx
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numexpr>=2.6.1
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openpyxl=2.5.5
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pyarrow
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openpyxl
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pyarrow>=0.4.1
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pymysql
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pytables>=3.4.2
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pytest-cov

‎ci/requirements-optional-pip.txt

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blosc
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bottleneck>=1.2.0
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fastparquet
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feather-format
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gcsfs
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html5lib
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ipython>=5.6.0
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matplotlib>=2.0.0
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nbsphinx
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numexpr>=2.6.1
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openpyxl==2.5.5
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pyarrow
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openpyxl
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pyarrow>=0.4.1
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pymysql
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tables
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pytest-cov
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xarray
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xlrd
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xlsxwriter
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xlwt
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xlwt

‎ci/script_multi.sh

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echo pytest -s -n 2 -m "not single" --cov=pandas --cov-report xml:/tmp/cov-multiple.xml --junitxml=test-data-multiple.xml --strict $TEST_ARGS pandas
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pytest -s -n 2 -m "not single" --cov=pandas --cov-report xml:/tmp/cov-multiple.xml --junitxml=test-data-multiple.xml --strict $TEST_ARGS pandas
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echo pytest -s -n 2 -m "not single" --durations=10 --cov=pandas --cov-report xml:/tmp/cov-multiple.xml --junitxml=test-data-multiple.xml --strict $TEST_ARGS pandas
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pytest -s -n 2 -m "not single" --durations=10 --cov=pandas --cov-report xml:/tmp/cov-multiple.xml --junitxml=test-data-multiple.xml --strict $TEST_ARGS pandas
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echo pytest -m "not single and slow" -v --junitxml=test-data-multiple.xml --strict $TEST_ARGS pandas
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pytest -m "not single and slow" -v --junitxml=test-data-multiple.xml --strict $TEST_ARGS pandas
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echo pytest -m "not single and slow" -v --durations=10 --junitxml=test-data-multiple.xml --strict $TEST_ARGS pandas
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pytest -m "not single and slow" -v --durations=10 --junitxml=test-data-multiple.xml --strict $TEST_ARGS pandas
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pytest -n 2 -m "not single" --junitxml=test-data-multiple.xml --strict $TEST_ARGS pandas # TODO: doctest
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echo pytest -n 2 -m "not single" --durations=10 --junitxml=test-data-multiple.xml --strict $TEST_ARGS pandas
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pytest -n 2 -m "not single" --durations=10 --junitxml=test-data-multiple.xml --strict $TEST_ARGS pandas # TODO: doctest
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‎ci/script_single.sh

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pytest -s -m "single" --strict --cov=pandas --cov-report xml:/tmp/cov-single.xml --junitxml=test-data-single.xml $TEST_ARGS pandas
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echo pytest -s -m "single" --durations=10 --strict --cov=pandas --cov-report xml:/tmp/cov-single.xml --junitxml=test-data-single.xml $TEST_ARGS pandas
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pytest -s -m "single" --durations=10 --strict --cov=pandas --cov-report xml:/tmp/cov-single.xml --junitxml=test-data-single.xml $TEST_ARGS pandas
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pytest -m "single" --junitxml=test-data-single.xml --strict $TEST_ARGS pandas
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echo pytest -m "single" --durations=10 --junitxml=test-data-single.xml --strict $TEST_ARGS pandas
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‎ci/travis-27.yaml

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- bottleneck
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- cython=0.28.2
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- fastparquet
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- feather-format
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- gcsfs
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- html5lib
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- ipython
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- s3fs
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- scipy
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- sqlalchemy=0.9.6
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- xarray=0.8.0
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- xarray=0.9.6
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- xlrd=0.9.2
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- xlsxwriter=0.5.2
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- xlwt=0.7.5

‎ci/travis-36-doc.yaml

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- bottleneck
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- cython>=0.28.2
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- fastparquet
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- feather-format
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- html5lib
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- hypothesis>=3.58.0
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- ipykernel
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- notebook
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- numpy=1.13*
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- openpyxl=2.5.5
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- openpyxl
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- pyarrow
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- pytables
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- python-dateutil

‎ci/travis-36-slow.yaml

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- numexpr
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- numpy
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- openpyxl
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- patsy
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- psycopg2
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- pymysql

‎ci/travis-36.yaml

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- dask
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- feather-format
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- flake8>=3.5
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- flake8-comprehensions
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- numexpr
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- numpy
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- openpyxl=2.5.5
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- openpyxl
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- pyarrow
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- pyarrow=0.9.0
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- pytables
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- python-snappy

‎ci/travis-37.yaml

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- nomkl
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- pyarrow
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- pytz
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‎doc/source/advanced.rst

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df[:5].reorder_levels([1,0], axis=0)
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.. _advanced.index_names:
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Renaming names of an ``Index`` or ``MultiIndex``
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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The :meth:`~DataFrame.rename` method is used to rename the labels of a
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``MultiIndex``, and is typically used to rename the columns of a ``DataFrame``.
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The ``columns`` argument of ``rename`` allows a dictionary to be specified
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that includes only the columns you wish to rename.
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.. ipython:: python
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df.rename(columns={0: "col0", 1: "col1"})
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This method can also be used to rename specific labels of the main index
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of the ``DataFrame``.
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.. ipython:: python
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df.rename(index={"one" : "two", "y" : "z"})
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The :meth:`~DataFrame.rename_axis` method is used to rename the name of a
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``Index`` or ``MultiIndex``. In particular, the names of the levels of a
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``MultiIndex`` can be specified, which is useful if ``reset_index()`` is later
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used to move the values from the ``MultiIndex`` to a column.
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.. ipython:: python
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df.rename_axis(index=['abc', 'def'])
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Note that the columns of a ``DataFrame`` are an index, so that using
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``rename_axis`` with the ``columns`` argument will change the name of that
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index.
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.. ipython:: python
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df.rename_axis(columns="Cols").columns
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Both ``rename`` and ``rename_axis`` support specifying a dictionary,
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``Series`` or a mapping function to map labels/names to new values.
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Sorting a ``MultiIndex``
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------------------------
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‎doc/source/api.rst

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Series.repeat
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Series.view
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Timedelta.to_timedelta64
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Timedelta.total_seconds
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.. _api.dateoffsets:
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Date Offsets
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------------
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.. currentmodule:: pandas.tseries.offsets
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.. autosummary::
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:toctree: generated/
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DateOffset
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BusinessDay
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BusinessHour
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CustomBusinessDay
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CustomBusinessHour
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MonthOffset
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MonthEnd
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MonthBegin
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BusinessMonthEnd
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BusinessMonthBegin
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CustomBusinessMonthEnd
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CustomBusinessMonthBegin
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SemiMonthOffset
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SemiMonthEnd
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SemiMonthBegin
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Week
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WeekOfMonth
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LastWeekOfMonth
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QuarterOffset
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BQuarterEnd
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BQuarterBegin
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QuarterEnd
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QuarterBegin
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YearOffset
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BYearEnd
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BYearBegin
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YearEnd
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YearBegin
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FY5253
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FY5253Quarter
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Easter
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Tick
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Day
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Hour
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Minute
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Second
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Milli
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Micro
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Nano
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BDay
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BMonthEnd
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BMonthBegin
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CBMonthEnd
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CBMonthBegin
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CDay
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‎doc/source/basics.rst

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The Panel class has a related :meth:`~Panel.rename_axis` class which can rename
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.. versionadded:: 0.24.0
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labels).
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.. ipython:: python
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df = pd.DataFrame({'x': [1, 2, 3, 4, 5, 6],
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'y': [10, 20, 30, 40, 50, 60]},
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df
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df.rename_axis(index=str.upper)
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