DOC: Replaced single backticks with double backticks in several rst files (pandas-dev#36627)

Author: kaptajnen

.pre-commit-config.yaml

@@ -36,23 +36,6 @@ repos:
       - id: rst-backticks
         # these exclusions should be removed and the files fixed
         exclude: (?x)(
-          text\.rst|
-          timeseries\.rst|
-          visualization\.rst|
-          missing_data\.rst|
-          options\.rst|
-          reshaping\.rst|
-          scale\.rst|
-          merging\.rst|
-          cookbook\.rst|
-          enhancingperf\.rst|
-          groupby\.rst|
-          io\.rst|
-          overview\.rst|
-          panel\.rst|
-          plotting\.rst|
-          10min\.rst|
-          basics\.rst|
           categorical\.rst|
           contributing\.rst|
           contributing_docstring\.rst|

doc/source/getting_started/overview.rst

@@ -40,7 +40,7 @@ Here are just a few of the things that pandas does well:
     higher dimensional objects
   - Automatic and explicit **data alignment**: objects can be explicitly
     aligned to a set of labels, or the user can simply ignore the labels and
-    let `Series`, `DataFrame`, etc. automatically align the data for you in
+    let ``Series``, ``DataFrame``, etc. automatically align the data for you in
     computations
   - Powerful, flexible **group by** functionality to perform
     split-apply-combine operations on data sets, for both aggregating and

doc/source/reference/panel.rst

@@ -7,4 +7,4 @@ Panel
 =====
 .. currentmodule:: pandas
 
-`Panel` was removed in 0.25.0. For prior documentation, see the `0.24 documentation <https://pandas.pydata.org/pandas-docs/version/0.24/reference/panel.html>`_
+``Panel`` was removed in 0.25.0. For prior documentation, see the `0.24 documentation <https://pandas.pydata.org/pandas-docs/version/0.24/reference/panel.html>`_

doc/source/reference/plotting.rst

@@ -7,7 +7,7 @@ Plotting
 ========
 .. currentmodule:: pandas.plotting
 
-The following functions are contained in the `pandas.plotting` module.
+The following functions are contained in the ``pandas.plotting`` module.
 
 .. autosummary::
    :toctree: api/

doc/source/user_guide/10min.rst

@@ -431,9 +431,9 @@ See more at :ref:`Histogramming and Discretization <basics.discretization>`.
 String Methods
 ~~~~~~~~~~~~~~
 
-Series is equipped with a set of string processing methods in the `str`
+Series is equipped with a set of string processing methods in the ``str``
 attribute that make it easy to operate on each element of the array, as in the
-code snippet below. Note that pattern-matching in `str` generally uses `regular
+code snippet below. Note that pattern-matching in ``str`` generally uses `regular
 expressions <https://docs.python.org/3/library/re.html>`__ by default (and in
 some cases always uses them). See more at :ref:`Vectorized String Methods
 <text.string_methods>`.

doc/source/user_guide/basics.rst

@@ -1459,7 +1459,7 @@ for altering the ``Series.name`` attribute.
 .. versionadded:: 0.24.0
 
 The methods :meth:`DataFrame.rename_axis` and :meth:`Series.rename_axis`
-allow specific names of a `MultiIndex` to be changed (as opposed to the
+allow specific names of a ``MultiIndex`` to be changed (as opposed to the
 labels).
 
 .. ipython:: python
@@ -1592,7 +1592,7 @@ index value along with a Series containing the data in each row:
       row
 
    All values in ``row``, returned as a Series, are now upcasted
-   to floats, also the original integer value in column `x`:
+   to floats, also the original integer value in column ``x``:
 
    .. ipython:: python
 
@@ -1787,8 +1787,8 @@ used to sort a pandas object by its index levels.
 .. versionadded:: 1.1.0
 
 Sorting by index also supports a ``key`` parameter that takes a callable
-function to apply to the index being sorted. For `MultiIndex` objects,
-the key is applied per-level to the levels specified by `level`.
+function to apply to the index being sorted. For ``MultiIndex`` objects,
+the key is applied per-level to the levels specified by ``level``.
 
 .. ipython:: python
 
@@ -1812,8 +1812,8 @@ For information on key sorting by value, see :ref:`value sorting
 By values
 ~~~~~~~~~
 
-The :meth:`Series.sort_values` method is used to sort a `Series` by its values. The
-:meth:`DataFrame.sort_values` method is used to sort a `DataFrame` by its column or row values.
+The :meth:`Series.sort_values` method is used to sort a ``Series`` by its values. The
+:meth:`DataFrame.sort_values` method is used to sort a ``DataFrame`` by its column or row values.
 The optional ``by`` parameter to :meth:`DataFrame.sort_values` may used to specify one or more columns
 to use to determine the sorted order.
 
@@ -1855,8 +1855,8 @@ to apply to the values being sorted.
    s1.sort_values()
    s1.sort_values(key=lambda x: x.str.lower())
 
-`key` will be given the :class:`Series` of values and should return a ``Series``
-or array of the same shape with the transformed values. For `DataFrame` objects,
+``key`` will be given the :class:`Series` of values and should return a ``Series``
+or array of the same shape with the transformed values. For ``DataFrame`` objects,
 the key is applied per column, so the key should still expect a Series and return
 a Series, e.g.
 

doc/source/user_guide/cookbook.rst

@@ -1270,7 +1270,7 @@ Often it's useful to obtain the lower (or upper) triangular form of a correlatio
 
     corr_mat.where(mask)
 
-The `method` argument within `DataFrame.corr` can accept a callable in addition to the named correlation types.  Here we compute the `distance correlation <https://en.wikipedia.org/wiki/Distance_correlation>`__ matrix for a `DataFrame` object.
+The ``method`` argument within ``DataFrame.corr`` can accept a callable in addition to the named correlation types.  Here we compute the ``distance correlation <https://en.wikipedia.org/wiki/Distance_correlation>``__ matrix for a ``DataFrame`` object.
 
 .. ipython:: python
 

doc/source/user_guide/enhancingperf.rst

@@ -488,9 +488,9 @@ These operations are supported by :func:`pandas.eval`:
 * Attribute access, e.g., ``df.a``
 * Subscript expressions, e.g., ``df[0]``
 * Simple variable evaluation, e.g., ``pd.eval('df')`` (this is not very useful)
-* Math functions: `sin`, `cos`, `exp`, `log`, `expm1`, `log1p`,
-  `sqrt`, `sinh`, `cosh`, `tanh`, `arcsin`, `arccos`, `arctan`, `arccosh`,
-  `arcsinh`, `arctanh`, `abs`, `arctan2` and `log10`.
+* Math functions: ``sin``, ``cos``, ``exp``, ``log``, ``expm1``, ``log1p``,
+  ``sqrt``, ``sinh``, ``cosh``, ``tanh``, ``arcsin``, ``arccos``, ``arctan``, ``arccosh``,
+  ``arcsinh``, ``arctanh``, ``abs``, ``arctan2`` and ``log10``.
 
 This Python syntax is **not** allowed:
 

doc/source/user_guide/groupby.rst

@@ -216,10 +216,10 @@ in case you want to include ``NA`` values in group keys, you could pass ``dropna
 
 .. ipython:: python
 
-    # Default `dropna` is set to True, which will exclude NaNs in keys
+    # Default ``dropna`` is set to True, which will exclude NaNs in keys
     df_dropna.groupby(by=["b"], dropna=True).sum()
 
-    # In order to allow NaN in keys, set `dropna` to False
+    # In order to allow NaN in keys, set ``dropna`` to False
     df_dropna.groupby(by=["b"], dropna=False).sum()
 
 The default setting of ``dropna`` argument is ``True`` which means ``NA`` are not included in group keys.