CLN: Fix Spelling Errors (#17535)

Author: jschendel

doc/source/advanced.rst

@@ -625,7 +625,7 @@ Index Types
 We have discussed ``MultiIndex`` in the previous sections pretty extensively. ``DatetimeIndex`` and ``PeriodIndex``
 are shown :ref:`here <timeseries.overview>`. ``TimedeltaIndex`` are :ref:`here <timedeltas.timedeltas>`.
 
-In the following sub-sections we will highlite some other index types.
+In the following sub-sections we will highlight some other index types.
 
 .. _indexing.categoricalindex:
 
@@ -645,7 +645,7 @@ and allows efficient indexing and storage of an index with a large number of dup
    df.dtypes
    df.B.cat.categories
 
-Setting the index, will create create a ``CategoricalIndex``
+Setting the index, will create a ``CategoricalIndex``
 
 .. ipython:: python
 
@@ -681,7 +681,7 @@ Groupby operations on the index will preserve the index nature as well
 Reindexing operations, will return a resulting index based on the type of the passed
 indexer, meaning that passing a list will return a plain-old-``Index``; indexing with
 a ``Categorical`` will return a ``CategoricalIndex``, indexed according to the categories
-of the PASSED ``Categorical`` dtype. This allows one to arbitrarly index these even with
+of the PASSED ``Categorical`` dtype. This allows one to arbitrarily index these even with
 values NOT in the categories, similarly to how you can reindex ANY pandas index.
 
 .. ipython :: python
@@ -722,7 +722,7 @@ Int64Index and RangeIndex
 Prior to 0.18.0, the ``Int64Index`` would provide the default index for all ``NDFrame`` objects.
 
 ``RangeIndex`` is a sub-class of ``Int64Index`` added in version 0.18.0, now providing the default index for all ``NDFrame`` objects.
-``RangeIndex`` is an optimized version of ``Int64Index`` that can represent a monotonic ordered set. These are analagous to python `range types <https://docs.python.org/3/library/stdtypes.html#typesseq-range>`__.
+``RangeIndex`` is an optimized version of ``Int64Index`` that can represent a monotonic ordered set. These are analogous to python `range types <https://docs.python.org/3/library/stdtypes.html#typesseq-range>`__.
 
 .. _indexing.float64index:
 
@@ -963,7 +963,7 @@ index can be somewhat complicated. For example, the following does not work:
     s.loc['c':'e'+1]
 
 A very common use case is to limit a time series to start and end at two
-specific dates. To enable this, we made the design design to make label-based
+specific dates. To enable this, we made the design to make label-based
 slicing include both endpoints:
 
 .. ipython:: python

doc/source/api.rst

@@ -1291,7 +1291,7 @@ Index
 -----
 
 **Many of these methods or variants thereof are available on the objects
-that contain an index (Series/Dataframe) and those should most likely be
+that contain an index (Series/DataFrame) and those should most likely be
 used before calling these methods directly.**
 
 .. autosummary::

doc/source/basics.rst

@@ -923,7 +923,7 @@ Passing a named function will yield that name for the row:
 Aggregating with a dict
 +++++++++++++++++++++++
 
-Passing a dictionary of column names to a scalar or a list of scalars, to ``DataFame.agg``
+Passing a dictionary of column names to a scalar or a list of scalars, to ``DataFrame.agg``
 allows you to customize which functions are applied to which columns. Note that the results
 are not in any particular order, you can use an ``OrderedDict`` instead to guarantee ordering.
 

doc/source/computation.rst

@@ -654,7 +654,7 @@ aggregation with, outputting a DataFrame:
 
    r['A'].agg([np.sum, np.mean, np.std])
 
-On a widowed DataFrame, you can pass a list of functions to apply to each
+On a windowed DataFrame, you can pass a list of functions to apply to each
 column, which produces an aggregated result with a hierarchical index:
 
 .. ipython:: python

doc/source/groupby.rst

@@ -561,7 +561,7 @@ must be either implemented on GroupBy or available via :ref:`dispatching
 
 .. note::
 
-    If you pass a dict to ``aggregate``, the ordering of the output colums is
+    If you pass a dict to ``aggregate``, the ordering of the output columns is
     non-deterministic. If you want to be sure the output columns will be in a specific
     order, you can use an ``OrderedDict``.  Compare the output of the following two commands:
 
@@ -1211,7 +1211,7 @@ Groupby by Indexer to 'resample' data
 
 Resampling produces new hypothetical samples (resamples) from already existing observed data or from a model that generates data. These new samples are similar to the pre-existing samples.
 
-In order to resample to work on indices that are non-datetimelike , the following procedure can be utilized.
+In order to resample to work on indices that are non-datetimelike, the following procedure can be utilized.
 
 In the following examples, **df.index // 5** returns a binary array which is used to determine what gets selected for the groupby operation.
 

doc/source/indexing.rst

@@ -714,7 +714,7 @@ Finally, one can also set a seed for ``sample``'s random number generator using
 Setting With Enlargement
 ------------------------
 
-The ``.loc/[]`` operations can perform enlargement when setting a non-existant key for that axis.
+The ``.loc/[]`` operations can perform enlargement when setting a non-existent key for that axis.
 
 In the ``Series`` case this is effectively an appending operation
 

doc/source/io.rst

@@ -3077,7 +3077,7 @@ Compressed pickle files
 
 .. versionadded:: 0.20.0
 
-:func:`read_pickle`, :meth:`DataFame.to_pickle` and :meth:`Series.to_pickle` can read
+:func:`read_pickle`, :meth:`DataFrame.to_pickle` and :meth:`Series.to_pickle` can read
 and write compressed pickle files. The compression types of ``gzip``, ``bz2``, ``xz`` are supported for reading and writing.
 `zip`` file supports read only and must contain only one data file
 to be read in.

doc/source/merging.rst

@@ -1329,7 +1329,7 @@ By default we are taking the asof of the quotes.
                  on='time',
                  by='ticker')
 
-We only asof within ``2ms`` betwen the quote time and the trade time.
+We only asof within ``2ms`` between the quote time and the trade time.
 
 .. ipython:: python
 
@@ -1338,8 +1338,8 @@ We only asof within ``2ms`` betwen the quote time and the trade time.
                  by='ticker',
                  tolerance=pd.Timedelta('2ms'))
 
-We only asof within ``10ms`` betwen the quote time and the trade time and we exclude exact matches on time.
-Note that though we exclude the exact matches (of the quotes), prior quotes DO propogate to that point
+We only asof within ``10ms`` between the quote time and the trade time and we exclude exact matches on time.
+Note that though we exclude the exact matches (of the quotes), prior quotes DO propagate to that point
 in time.
 
 .. ipython:: python

doc/source/missing_data.rst

@@ -320,7 +320,7 @@ Interpolation
 
   The ``limit_direction`` keyword argument was added.
 
-Both Series and Dataframe objects have an ``interpolate`` method that, by default,
+Both Series and DataFrame objects have an ``interpolate`` method that, by default,
 performs linear interpolation at missing datapoints.
 
 .. ipython:: python

doc/source/options.rst

@@ -313,9 +313,9 @@ display.large_repr                  truncate     For DataFrames exceeding max_ro
 display.latex.repr                  False        Whether to produce a latex DataFrame
                                                  representation for jupyter frontends
                                                  that support it.
-display.latex.escape                True         Escapes special caracters in Dataframes, when
+display.latex.escape                True         Escapes special characters in DataFrames, when
                                                  using the to_latex method.
-display.latex.longtable             False        Specifies if the to_latex method of a Dataframe
+display.latex.longtable             False        Specifies if the to_latex method of a DataFrame
                                                  uses the longtable format.
 display.latex.multicolumn           True         Combines columns when using a MultiIndex
 display.latex.multicolumn_format    'l'          Alignment of multicolumn labels