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hwalingahwalinga
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Merge remote-tracking branch 'upstream/master' into allow-special-characters-query
2 parents 291cd40 + f437a04 commit 2e17322

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‎asv_bench/benchmarks/index_object.py

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@@ -7,6 +7,7 @@
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Float64Index,
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Index,
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IntervalIndex,
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MultiIndex,
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RangeIndex,
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Series,
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date_range,
@@ -111,6 +112,18 @@ def time_get_loc_dec(self):
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self.idx_dec.get_loc(100000)
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class IndexEquals:
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def setup(self):
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idx_large_fast = RangeIndex(100000)
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idx_small_slow = date_range(start="1/1/2012", periods=1)
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self.mi_large_slow = MultiIndex.from_product([idx_large_fast, idx_small_slow])
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self.idx_non_object = RangeIndex(1)
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def time_non_object_equals_multiindex(self):
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self.idx_non_object.equals(self.mi_large_slow)
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class IndexAppend:
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def setup(self):
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‎asv_bench/benchmarks/multiindex_object.py

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import numpy as np
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from pandas import DataFrame, MultiIndex, date_range
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from pandas import DataFrame, MultiIndex, RangeIndex, date_range
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import pandas.util.testing as tm
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@@ -147,4 +147,16 @@ def time_categorical_level(self):
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self.df.set_index(["a", "b"])
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class Equals:
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def setup(self):
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idx_large_fast = RangeIndex(100000)
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idx_small_slow = date_range(start="1/1/2012", periods=1)
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self.mi_large_slow = MultiIndex.from_product([idx_large_fast, idx_small_slow])
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self.idx_non_object = RangeIndex(1)
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def time_equals_non_object_index(self):
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self.mi_large_slow.equals(self.idx_non_object)
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from .pandas_vb_common import setup # noqa: F401 isort:skip

‎ci/azure/posix.yml

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CONDA_PY: "36"
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PATTERN: "not slow and not network"
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py36_locale_slow_old_np:
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ENV_FILE: ci/deps/azure-36-locale.yaml
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ENV_FILE: ci/deps/azure-36-locale_slow.yaml
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CONDA_PY: "36"
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PATTERN: "slow"
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LOCALE_OVERRIDE: "zh_CN.UTF-8"
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EXTRA_APT: "language-pack-zh-hans"
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py36_locale_slow:
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ENV_FILE: ci/deps/azure-36-locale_slow.yaml
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py36_locale:
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ENV_FILE: ci/deps/azure-36-locale.yaml
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CONDA_PY: "36"
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PATTERN: "not slow and not network"
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LOCALE_OVERRIDE: "it_IT.UTF-8"

‎ci/code_checks.sh

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@@ -105,7 +105,12 @@ if [[ -z "$CHECK" || "$CHECK" == "lint" ]]; then
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# Imports - Check formatting using isort see setup.cfg for settings
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MSG='Check import format using isort ' ; echo $MSG
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isort --recursive --check-only pandas asv_bench
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ISORT_CMD="isort --recursive --check-only pandas asv_bench"
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if [[ "$GITHUB_ACTIONS" == "true" ]]; then
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eval $ISORT_CMD | awk '{print "##[error]" $0}'; RET=$(($RET + ${PIPESTATUS[0]}))
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else
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eval $ISORT_CMD
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fi
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RET=$(($RET + $?)) ; echo $MSG "DONE"
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fi

‎ci/deps/azure-36-locale.yaml

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- pytest-azurepipelines
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# pandas dependencies
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- beautifulsoup4==4.6.0
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- bottleneck=1.2.*
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- beautifulsoup4
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- gcsfs
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- html5lib
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- ipython
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- jinja2
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- lxml
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- matplotlib=2.2.2
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- numpy=1.14.*
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- openpyxl=2.4.8
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- python-dateutil
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- python-blosc
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- pytz=2017.2
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- scipy
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- sqlalchemy=1.1.4
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- xlrd=1.1.0
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- xlsxwriter=0.9.8
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- xlwt=1.2.0
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- matplotlib=3.0.*
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- nomkl
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- numexpr
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- numpy=1.15.*
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- openpyxl
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# lowest supported version of pyarrow (putting it here instead of in
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# azure-36-minimum_versions because it needs numpy >= 1.14)
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- pyarrow=0.12
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- pip
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- pip:
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- html5lib==1.0b2
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- pytables
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- python-dateutil
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- pytz
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- s3fs
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- scipy
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- xarray
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- xlrd
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- xlsxwriter
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- xlwt
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- moto

‎ci/deps/azure-36-locale_slow.yaml

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- pytest-azurepipelines
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# pandas dependencies
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- beautifulsoup4
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- gcsfs
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- html5lib
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- ipython
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- jinja2
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- beautifulsoup4==4.6.0
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- bottleneck=1.2.*
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- lxml
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- matplotlib=3.0.*
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- nomkl
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- numexpr
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- numpy=1.15.*
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- openpyxl
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- pytables
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- matplotlib=2.2.2
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- numpy=1.14.*
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- openpyxl=2.4.8
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- python-dateutil
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- pytz
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- s3fs
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- python-blosc
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- pytz=2017.2
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- scipy
32-
- xarray
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- xlrd
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- xlsxwriter
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- xlwt
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- moto
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- sqlalchemy=1.1.4
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- xlrd=1.1.0
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- xlsxwriter=0.9.8
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- xlwt=1.2.0
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- pip
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- pip:
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- html5lib==1.0b2

‎doc/redirects.csv

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@@ -319,7 +319,6 @@ generated/pandas.DataFrame.clip_upper,../reference/api/pandas.DataFrame.clip_upp
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generated/pandas.DataFrame.columns,../reference/api/pandas.DataFrame.columns
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generated/pandas.DataFrame.combine_first,../reference/api/pandas.DataFrame.combine_first
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generated/pandas.DataFrame.combine,../reference/api/pandas.DataFrame.combine
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generated/pandas.DataFrame.compound,../reference/api/pandas.DataFrame.compound
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generated/pandas.DataFrame.convert_objects,../reference/api/pandas.DataFrame.convert_objects
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generated/pandas.DataFrame.copy,../reference/api/pandas.DataFrame.copy
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generated/pandas.DataFrame.corr,../reference/api/pandas.DataFrame.corr
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generated/pandas.Series.clip_upper,../reference/api/pandas.Series.clip_upper
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generated/pandas.Series.combine_first,../reference/api/pandas.Series.combine_first
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generated/pandas.Series.combine,../reference/api/pandas.Series.combine
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generated/pandas.Series.compound,../reference/api/pandas.Series.compound
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generated/pandas.Series.compress,../reference/api/pandas.Series.compress
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generated/pandas.Series.convert_objects,../reference/api/pandas.Series.convert_objects
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generated/pandas.Series.copy,../reference/api/pandas.Series.copy

‎doc/source/getting_started/10min.rst

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df2.all df2.columns
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df2.any df2.combine
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df2.append df2.combine_first
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df2.apply df2.compound
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df2.applymap df2.consolidate
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df2.apply df2.consolidate
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df2.applymap
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df2.D
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As you can see, the columns ``A``, ``B``, ``C``, and ``D`` are automatically

‎doc/source/reference/frame.rst

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DataFrame.all
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DataFrame.any
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DataFrame.clip
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DataFrame.compound
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DataFrame.corr
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DataFrame.corrwith
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DataFrame.count

‎doc/source/reference/series.rst

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Series.is_monotonic_increasing
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Series.is_monotonic_decreasing
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Series.value_counts
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Series.compound
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Reindexing / selection / label manipulation
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-------------------------------------------

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