Merge remote-tracking branch 'upstream/master' into mask_pos_args_deprecation

Author: ShreyDixit

ci/deps/actions-37-db-min.yaml

@@ -6,7 +6,7 @@ dependencies:
 
   # tools
   - cython>=0.29.21
-  - pytest>=5.0.1
+  - pytest>=6.0
   - pytest-cov
   - pytest-xdist>=1.21
   - hypothesis>=3.58.0

ci/deps/actions-37-db.yaml

@@ -6,7 +6,7 @@ dependencies:
 
   # tools
   - cython>=0.29.21
-  - pytest>=5.0.1
+  - pytest>=6.0
   - pytest-xdist>=1.21
   - hypothesis>=3.58.0
   - pytest-cov>=2.10.1  # this is only needed in the coverage build, ref: GH 35737
@@ -25,7 +25,7 @@ dependencies:
   - flask
   - nomkl
   - numexpr
-  - numpy=1.16.*
+  - numpy=1.17.*
   - odfpy
   - openpyxl
   - pandas-gbq

ci/deps/actions-37-locale_slow.yaml

@@ -7,7 +7,7 @@ dependencies:
 
   # tools
   - cython>=0.29.21
-  - pytest>=5.0.1
+  - pytest>=6.0
   - pytest-cov
   - pytest-xdist>=1.21
   - hypothesis>=3.58.0
@@ -17,13 +17,13 @@ dependencies:
   - bottleneck=1.2.*
   - lxml
   - matplotlib=3.0.0
-  - numpy=1.16.*
+  - numpy=1.17.*
   - openpyxl=3.0.0
   - python-dateutil
   - python-blosc
   - pytz=2017.3
   - scipy
-  - sqlalchemy=1.2.8
+  - sqlalchemy=1.3.0
   - xlrd=1.2.0
   - xlsxwriter=1.0.2
   - xlwt=1.3.0

ci/deps/actions-37-slow.yaml

@@ -7,7 +7,7 @@ dependencies:
 
   # tools
   - cython>=0.29.21
-  - pytest>=5.0.1
+  - pytest>=6.0
   - pytest-cov
   - pytest-xdist>=1.21
   - hypothesis>=3.58.0

ci/deps/actions-37.yaml

@@ -7,7 +7,7 @@ dependencies:
 
   # tools
   - cython>=0.29.21
-  - pytest>=5.0.1
+  - pytest>=6.0
   - pytest-cov
   - pytest-xdist>=1.21
   - hypothesis>=3.58.0

ci/deps/actions-38-locale.yaml

@@ -6,7 +6,7 @@ dependencies:
 
   # tools
   - cython>=0.29.21
-  - pytest>=5.0.1
+  - pytest>=6.0
   - pytest-cov
   - pytest-xdist>=1.21
   - pytest-asyncio>=0.12.0
@@ -20,7 +20,7 @@ dependencies:
   - jinja2
   - jedi<0.18.0
   - lxml
-  - matplotlib <3.3.0
+  - matplotlib<3.3.0
   - moto
   - nomkl
   - numexpr

ci/deps/actions-38-numpydev.yaml

@@ -5,14 +5,14 @@ dependencies:
   - python=3.8.*
 
   # tools
-  - pytest>=5.0.1
+  - pytest>=6.0
   - pytest-cov
   - pytest-xdist>=1.21
   - hypothesis>=3.58.0
 
   # pandas dependencies
   - pytz
-  - pip=20.2
+  - pip
   - pip:
     - cython==0.29.21 # GH#34014
     - "git+git://github.com/dateutil/dateutil.git"

ci/deps/actions-38-slow.yaml

@@ -6,7 +6,7 @@ dependencies:
 
   # tools
   - cython>=0.29.21
-  - pytest>=5.0.1
+  - pytest>=6.0
   - pytest-cov
   - pytest-xdist>=1.21
   - hypothesis>=3.58.0

ci/deps/actions-38.yaml

@@ -7,7 +7,7 @@ dependencies:
 
   # tools
   - cython>=0.29.21
-  - pytest>=5.0.1
+  - pytest>=6.0
   - pytest-cov
   - pytest-xdist>=1.21
   - hypothesis>=3.58.0

ci/deps/actions-39.yaml

@@ -6,7 +6,7 @@ dependencies:
 
   # tools
   - cython>=0.29.21
-  - pytest>=5.0.1
+  - pytest>=6.0
   - pytest-cov
   - pytest-xdist>=1.21
   - hypothesis>=3.58.0

ci/deps/azure-macos-37.yaml

@@ -6,7 +6,7 @@ dependencies:
   - python=3.7.*
 
   # tools
-  - pytest>=5.0.1
+  - pytest>=6.0
   - pytest-xdist>=1.21
   - hypothesis>=3.58.0
   - pytest-azurepipelines

ci/deps/azure-windows-37.yaml

@@ -7,7 +7,7 @@ dependencies:
 
   # tools
   - cython>=0.29.21
-  - pytest>=5.0.1
+  - pytest>=6.0
   - pytest-xdist>=1.21
   - hypothesis>=3.58.0
   - pytest-azurepipelines

ci/deps/azure-windows-38.yaml

@@ -7,7 +7,7 @@ dependencies:
 
   # tools
   - cython>=0.29.21
-  - pytest>=5.0.1
+  - pytest>=6.0
   - pytest-xdist>=1.21
   - hypothesis>=3.58.0
   - pytest-azurepipelines

ci/deps/travis-37-arm64.yaml

@@ -6,7 +6,7 @@ dependencies:
 
   # tools
   - cython>=0.29.21
-  - pytest>=5.0.1
+  - pytest>=6.0
   - pytest-xdist>=1.21
   - hypothesis>=3.58.0
 

doc/source/_static/style/tg_ax0.png

@@ -56,6 +56,7 @@ Builtin styles
    Styler.highlight_min
    Styler.highlight_between
    Styler.background_gradient
+   Styler.text_gradient
    Styler.bar
 
 Style export and import

doc/source/_static/style/tg_axNone.png

@@ -1012,7 +1012,8 @@
     " - [.highlight_min][minfunc] and [.highlight_max][maxfunc]: for use with identifying extremeties in data.\n",
     " - [.highlight_between][betweenfunc] and [.highlight_quantile][quantilefunc]: for use with identifying classes within data.\n",
     " - [.background_gradient][bgfunc]: a flexible method for highlighting cells based or their, or other, values on a numeric scale.\n",
-    " -  [.bar][barfunc]: to display mini-charts within cell backgrounds.\n",
+    " - [.text_gradient][textfunc]: similar method for highlighting text based on their, or other, values on a numeric scale.\n",
+    " - [.bar][barfunc]: to display mini-charts within cell backgrounds.\n",
     " \n",
     "The individual documentation on each function often gives more examples of their arguments.\n",
     "\n",
@@ -1022,6 +1023,7 @@
     "[betweenfunc]: ../reference/api/pandas.io.formats.style.Styler.highlight_between.rst\n",
     "[quantilefunc]: ../reference/api/pandas.io.formats.style.Styler.highlight_quantile.rst\n",
     "[bgfunc]: ../reference/api/pandas.io.formats.style.Styler.background_gradient.rst\n",
+    "[textfunc]: ../reference/api/pandas.io.formats.style.Styler.text_gradient.rst\n",
     "[barfunc]: ../reference/api/pandas.io.formats.style.Styler.bar.rst"
    ]
   },
@@ -1098,14 +1100,14 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Background Gradient"
+    "### Background Gradient and Text Gradient"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "You can create \"heatmaps\" with the `background_gradient` method. These require matplotlib, and we'll use [Seaborn](https://stanford.edu/~mwaskom/software/seaborn/) to get a nice colormap."
+    "You can create \"heatmaps\" with the `background_gradient` and `text_gradient` methods. These require matplotlib, and we'll use [Seaborn](https://stanford.edu/~mwaskom/software/seaborn/) to get a nice colormap."
    ]
   },
   {
@@ -1120,19 +1122,31 @@
     "df2.style.background_gradient(cmap=cm)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df2.style.text_gradient(cmap=cm)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "[.background_gradient][bgfunc] has a number of keyword arguments to customise the gradients and colors. See its documentation.\n",
+    "[.background_gradient][bgfunc] and [.text_gradient][textfunc] have a number of keyword arguments to customise the gradients and colors. See the documentation.\n",
     "\n",
-    "[bgfunc]: ../reference/api/pandas.io.formats.style.Styler.background_gradient.rst"
+    "[bgfunc]: ../reference/api/pandas.io.formats.style.Styler.background_gradient.rst\n",
+    "[textfunc]: ../reference/api/pandas.io.formats.style.Styler.text_gradient.rst"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
+    "### Set properties\n",
+    "\n",
     "Use `Styler.set_properties` when the style doesn't actually depend on the values. This is just a simple wrapper for `.applymap` where the function returns the same properties for all cells."
    ]
   },

doc/source/_static/style/tg_axNone_gmap.png

@@ -120,8 +120,8 @@ to allow custom CSS highlighting instead of default background coloring (:issue:
 Enhancements to other built-in methods include extending the :meth:`.Styler.background_gradient`
 method to shade elements based on a given gradient map and not be restricted only to
 values in the DataFrame (:issue:`39930` :issue:`22727` :issue:`28901`). Additional
-built-in methods such as :meth:`.Styler.highlight_between` and :meth:`.Styler.highlight_quantile`
-have been added (:issue:`39821` and :issue:`40926`).
+built-in methods such as :meth:`.Styler.highlight_between`, :meth:`.Styler.highlight_quantile`
+and :math:`.Styler.text_gradient` have been added (:issue:`39821`, :issue:`40926`, :issue:`41098`).
 
 The :meth:`.Styler.apply` now consistently allows functions with ``ndarray`` output to
 allow more flexible development of UDFs when ``axis`` is ``None`` ``0`` or ``1`` (:issue:`39393`).
@@ -618,7 +618,7 @@ Optional libraries below the lowest tested version may still work, but are not c
 +-----------------+-----------------+---------+
 | scipy           | 1.2.0           |         |
 +-----------------+-----------------+---------+
-| sqlalchemy      | 1.2.8           |         |
+| sqlalchemy      | 1.3.0           |    X    |
 +-----------------+-----------------+---------+
 | tabulate        | 0.8.7           |    X    |
 +-----------------+-----------------+---------+
@@ -655,6 +655,7 @@ Build
 Deprecations
 ~~~~~~~~~~~~
 - Deprecated allowing scalars to be passed to the :class:`Categorical` constructor (:issue:`38433`)
+- Deprecated constructing :class:`CategoricalIndex` without passing list-like data (:issue:`38944`)
 - Deprecated allowing subclass-specific keyword arguments in the :class:`Index` constructor, use the specific subclass directly instead (:issue:`14093`, :issue:`21311`, :issue:`22315`, :issue:`26974`)
 - Deprecated ``astype`` of datetimelike (``timedelta64[ns]``, ``datetime64[ns]``, ``Datetime64TZDtype``, ``PeriodDtype``) to integer dtypes, use ``values.view(...)`` instead (:issue:`38544`)
 - Deprecated :meth:`MultiIndex.is_lexsorted` and :meth:`MultiIndex.lexsort_depth`, use :meth:`MultiIndex.is_monotonic_increasing` instead (:issue:`32259`)
@@ -845,6 +846,7 @@ Indexing
 
 - Bug in :meth:`Index.union` dropping duplicate ``Index`` values when ``Index`` was not monotonic or ``sort`` was set to ``False`` (:issue:`36289`, :issue:`31326`, :issue:`40862`)
 - Bug in :meth:`CategoricalIndex.get_indexer` failing to raise ``InvalidIndexError`` when non-unique (:issue:`38372`)
+- Bug in :meth:`Series.loc` raising ``ValueError`` when input was filtered with a boolean list and values to set were a list with lower dimension (:issue:`20438`)
 - Bug in inserting many new columns into a :class:`DataFrame` causing incorrect subsequent indexing behavior (:issue:`38380`)
 - Bug in :meth:`DataFrame.__setitem__` raising ``ValueError`` when setting multiple values to duplicate columns (:issue:`15695`)
 - Bug in :meth:`DataFrame.loc`, :meth:`Series.loc`, :meth:`DataFrame.__getitem__` and :meth:`Series.__getitem__` returning incorrect elements for non-monotonic :class:`DatetimeIndex` for string slices (:issue:`33146`)
@@ -873,6 +875,7 @@ Indexing
 - Bug in :meth:`DataFrame.__setitem__` and :meth:`DataFrame.iloc.__setitem__` raising ``ValueError`` when trying to index with a row-slice and setting a list as values (:issue:`40440`)
 - Bug in :meth:`DataFrame.loc` not raising ``KeyError`` when key was not found in :class:`MultiIndex` when levels contain more values than used (:issue:`41170`)
 - Bug in :meth:`DataFrame.loc.__setitem__` when setting-with-expansion incorrectly raising when the index in the expanding axis contains duplicates (:issue:`40096`)
+- Bug in :meth:`DataFrame.loc.__getitem__` with :class:`MultiIndex` casting to float when at least one column is from has float dtype and we retrieve a scalar (:issue:`41369`)
 - Bug in :meth:`DataFrame.loc` incorrectly matching non-boolean index elements (:issue:`20432`)
 - Bug in :meth:`Series.__delitem__` with ``ExtensionDtype`` incorrectly casting to ``ndarray`` (:issue:`40386`)
 - Bug in :meth:`DataFrame.__setitem__` raising ``TypeError`` when using a str subclass as the column name with a :class:`DatetimeIndex` (:issue:`37366`)
@@ -1056,6 +1059,7 @@ Other
 - Bug in :meth:`DataFrame.agg()` not sorting the aggregated axis in the order of the provided aggragation functions when one or more aggregation function fails to produce results (:issue:`33634`)
 - Bug in :meth:`DataFrame.clip` not interpreting missing values as no threshold (:issue:`40420`)
 - Bug in :class:`Series` backed by :class:`DatetimeArray` or :class:`TimedeltaArray` sometimes failing to set the array's ``freq`` to ``None`` (:issue:`41425`)
+- Bug in creating a :class:`Series` from a ``range`` object that does not fit in the bounds of ``int64`` dtype (:issue:`30173`)
 
 .. ---------------------------------------------------------------------------
 

doc/source/_static/style/tg_axNone_lowhigh.png

@@ -22,11 +22,11 @@
     "openpyxl": "3.0.0",
     "pandas_gbq": "0.12.0",
     "pyarrow": "0.17.0",
-    "pytest": "5.0.1",
+    "pytest": "6.0",
     "pyxlsb": "1.0.6",
     "s3fs": "0.4.0",
     "scipy": "1.2.0",
-    "sqlalchemy": "1.2.8",
+    "sqlalchemy": "1.3.0",
     "tables": "3.5.1",
     "tabulate": "0.8.7",
     "xarray": "0.12.3",

doc/source/_static/style/tg_axNone_vminvmax.png

@@ -22,10 +22,7 @@
     Union,
 )
 
-from numpy import (
-    __version__,
-    ndarray,
-)
+from numpy import ndarray
 
 from pandas._libs.lib import (
     is_bool,
@@ -38,8 +35,6 @@
     validate_kwargs,
 )
 
-from pandas.util.version import Version
-
 
 class CompatValidator:
     def __init__(
@@ -128,10 +123,7 @@ def validate_argmax_with_skipna(skipna, args, kwargs):
 ARGSORT_DEFAULTS["axis"] = -1
 ARGSORT_DEFAULTS["kind"] = "quicksort"
 ARGSORT_DEFAULTS["order"] = None
-
-if Version(__version__) >= Version("1.17.0"):
-    # GH-26361. NumPy added radix sort and changed default to None.
-    ARGSORT_DEFAULTS["kind"] = None
+ARGSORT_DEFAULTS["kind"] = None
 
 
 validate_argsort = CompatValidator(

doc/source/_static/style/tg_gmap.png

@@ -1119,14 +1119,14 @@ def to_period(self, freq=None) -> PeriodArray:
         ...                                         "2000-08-31 00:00:00"]))
         >>> df.index.to_period("M")
         PeriodIndex(['2000-03', '2000-05', '2000-08'],
-                    dtype='period[M]', freq='M')
+                    dtype='period[M]')
 
         Infer the daily frequency
 
         >>> idx = pd.date_range("2017-01-01", periods=2)
         >>> idx.to_period()
         PeriodIndex(['2017-01-01', '2017-01-02'],
-                    dtype='period[D]', freq='D')
+                    dtype='period[D]')
         """
         from pandas.core.arrays import PeriodArray
 

doc/source/reference/style.rst

@@ -564,15 +564,15 @@ def asfreq(self, freq=None, how: str = "E") -> PeriodArray:
         >>> pidx = pd.period_range('2010-01-01', '2015-01-01', freq='A')
         >>> pidx
         PeriodIndex(['2010', '2011', '2012', '2013', '2014', '2015'],
-        dtype='period[A-DEC]', freq='A-DEC')
+        dtype='period[A-DEC]')
 
         >>> pidx.asfreq('M')
         PeriodIndex(['2010-12', '2011-12', '2012-12', '2013-12', '2014-12',
-        '2015-12'], dtype='period[M]', freq='M')
+        '2015-12'], dtype='period[M]')
 
         >>> pidx.asfreq('M', how='S')
         PeriodIndex(['2010-01', '2011-01', '2012-01', '2013-01', '2014-01',
-        '2015-01'], dtype='period[M]', freq='M')
+        '2015-01'], dtype='period[M]')
         """
         how = libperiod.validate_end_alias(how)