Merge branch 'master' into enh-masked-2d

Author: jbrockmendel

.pre-commit-config.yaml

@@ -15,14 +15,24 @@ repos:
     hooks:
     -   id: codespell
         types_or: [python, rst, markdown]
-        files: ^pandas/
+        files: ^(pandas|doc)/
         exclude: ^pandas/tests/
 -   repo: https://github.com/pre-commit/pre-commit-hooks
     rev: v3.4.0
     hooks:
     -   id: end-of-file-fixer
         exclude: \.txt$
     -   id: trailing-whitespace
+-   repo: https://github.com/cpplint/cpplint
+    rev: f7061b1 # the latest tag does not have the hook
+    hooks:
+    -   id: cpplint
+        # We don't lint all C files because we don't want to lint any that are built
+        # from Cython files nor do we want to lint C files that we didn't modify for
+        # this particular codebase (e.g. src/headers, src/klib). However,
+        # we can lint all header files since they aren't "generated" like C files are.
+        exclude: ^pandas/_libs/src/(klib|headers)/
+        args: [--quiet, '--extensions=c,h', '--headers=h', --recursive, '--filter=-readability/casting,-runtime/int,-build/include_subdir']
 -   repo: https://gitlab.com/pycqa/flake8
     rev: 3.8.4
     hooks:

ci/code_checks.sh

@@ -59,14 +59,6 @@ if [[ -z "$CHECK" || "$CHECK" == "lint" ]]; then
     # runtime/int: Warnings about using C number types instead of C++ ones
     # build/include_subdir: Warnings about prefacing included header files with directory
 
-    # We don't lint all C files because we don't want to lint any that are built
-    # from Cython files nor do we want to lint C files that we didn't modify for
-    # this particular codebase (e.g. src/headers, src/klib). However,
-    # we can lint all header files since they aren't "generated" like C files are.
-    MSG='Linting .c and .h' ; echo $MSG
-    cpplint --quiet --extensions=c,h --headers=h --recursive --filter=-readability/casting,-runtime/int,-build/include_subdir pandas/_libs/src/*.h pandas/_libs/src/parser pandas/_libs/src/ujson pandas/_libs/tslibs/src/datetime pandas/_libs/*.cpp
-    RET=$(($RET + $?)) ; echo $MSG "DONE"
-
 fi
 
 ### PATTERNS ###

doc/source/development/contributing.rst

@@ -714,7 +714,7 @@ to run its checks with::
 
 without needing to have done ``pre-commit install`` beforehand.
 
-If you want to run checks on all recently commited files on upstream/master you can use::
+If you want to run checks on all recently committed files on upstream/master you can use::
 
     pre-commit run --from-ref=upstream/master --to-ref=HEAD --all-files
 

doc/source/development/debugging_extensions.rst

@@ -61,7 +61,7 @@ Now go ahead and execute your script:
 
    run <the_script>.py
 
-Code execution will halt at the breakpoint defined or at the occurance of any segfault. LLDB's `GDB to LLDB command map <https://lldb.llvm.org/use/map.html>`_ provides a listing of debugger command that you can execute using either debugger.
+Code execution will halt at the breakpoint defined or at the occurrence of any segfault. LLDB's `GDB to LLDB command map <https://lldb.llvm.org/use/map.html>`_ provides a listing of debugger command that you can execute using either debugger.
 
 Another option to execute the entire test suite under lldb would be to run the following:
 

doc/source/getting_started/comparison/comparison_with_spreadsheets.rst

@@ -461,4 +461,4 @@ pandas' :meth:`~DataFrame.replace` is comparable to Excel's ``Replace All``.
 
 .. ipython:: python
 
-    tips.replace("Thur", "Thu")
+    tips.replace("Thu", "Thursday")

doc/source/getting_started/comparison/comparison_with_sql.rst

@@ -193,7 +193,7 @@ to your grouped DataFrame, indicating which functions to apply to specific colum
     Fri   2.734737   19
     Sat   2.993103   87
     Sun   3.255132   76
-    Thur  2.771452   62
+    Thu  2.771452   62
     */
 
 .. ipython:: python
@@ -213,11 +213,11 @@ Grouping by more than one column is done by passing a list of columns to the
     No     Fri      4  2.812500
            Sat     45  3.102889
            Sun     57  3.167895
-           Thur    45  2.673778
+           Thu    45  2.673778
     Yes    Fri     15  2.714000
            Sat     42  2.875476
            Sun     19  3.516842
-           Thur    17  3.030000
+           Thu    17  3.030000
     */
 
 .. ipython:: python

doc/source/getting_started/index.rst

@@ -116,7 +116,7 @@ Intro to pandas
                 <div class="card-body">
 
 When working with tabular data, such as data stored in spreadsheets or databases, pandas is the right tool for you. pandas will help you
-to explore, clean and process your data. In pandas, a data table is called a :class:`DataFrame`.
+to explore, clean, and process your data. In pandas, a data table is called a :class:`DataFrame`.
 
 .. image:: ../_static/schemas/01_table_dataframe.svg
    :align: center
@@ -351,7 +351,7 @@ Adding a column to a :class:`DataFrame` based on existing data in other columns
                 <div class="card-body">
 
 Basic statistics (mean, median, min, max, counts...) are easily calculable. These or custom aggregations can be applied on the entire
-data set, a sliding window of the data or grouped by categories. The latter is also known as the split-apply-combine approach.
+data set, a sliding window of the data, or grouped by categories. The latter is also known as the split-apply-combine approach.
 
 .. image:: ../_static/schemas/06_groupby.svg
    :align: center
@@ -444,7 +444,7 @@ from long to wide format. With aggregations built-in, a pivot table is created w
             <div id="collapseEight" class="collapse" data-parent="#accordion">
                 <div class="card-body">
 
-Multiple tables can be concatenated both column wise as row wise and database-like join/merge operations are provided to combine multiple tables of data.
+Multiple tables can be concatenated both column wise and row wise as database-like join/merge operations are provided to combine multiple tables of data.
 
 .. image:: ../_static/schemas/08_concat_row.svg
    :align: center
@@ -547,7 +547,7 @@ Data sets do not only contain numerical data. pandas provides a wide range of fu
                         </span>
                         <span class="badge gs-badge-link">
 
-:ref:`To user guide <timeseries>`
+:ref:`To user guide <text>`
 
 .. raw:: html
 

doc/source/reference/style.rst

@@ -39,7 +39,6 @@ Style application
    Styler.set_table_styles
    Styler.set_table_attributes
    Styler.set_tooltips
-   Styler.set_tooltips_class
    Styler.set_caption
    Styler.set_properties
    Styler.set_uuid

doc/source/user_guide/dsintro.rst

@@ -869,5 +869,5 @@ completion mechanism so they can be tab-completed:
 
 .. code-block:: ipython
 
-    In [5]: df.fo<TAB>  # noqa: E225, E999
+    In [5]: df.foo<TAB>  # noqa: E225, E999
     df.foo1  df.foo2

doc/source/user_guide/io.rst

@@ -2189,7 +2189,7 @@ into a flat table.
 
    data = [
        {"id": 1, "name": {"first": "Coleen", "last": "Volk"}},
-       {"name": {"given": "Mose", "family": "Regner"}},
+       {"name": {"given": "Mark", "family": "Regner"}},
        {"id": 2, "name": "Faye Raker"},
    ]
    pd.json_normalize(data)
@@ -2995,7 +2995,7 @@ For example, below XML contains a namespace with prefix, ``doc``, and URI at
 
 Similarly, an XML document can have a default namespace without prefix. Failing
 to assign a temporary prefix will return no nodes and raise a ``ValueError``.
-But assiging *any* temporary name to correct URI allows parsing by nodes.
+But assigning *any* temporary name to correct URI allows parsing by nodes.
 
 .. ipython:: python