CLN: Fix typos (mainly in docs and comments) (#27007)

Author: minho42

asv_bench/benchmarks/offset.py

@@ -9,7 +9,7 @@
  pass
 
 hcal = pd.tseries.holiday.USFederalHolidayCalendar()
-# These offests currently raise a NotImplimentedError with .apply_index()
+# These offsets currently raise a NotImplimentedError with .apply_index()
 non_apply = [pd.offsets.Day(),
  pd.offsets.BYearEnd(),
  pd.offsets.BYearBegin(),

doc/source/getting_started/comparison/comparison_with_sas.rst

@@ -660,7 +660,7 @@ example, to subtract the mean for each observation by smoker group.
  run;
 
 
-pandas ``groubpy`` provides a ``transform`` mechanism that allows
+pandas ``groupby`` provides a ``transform`` mechanism that allows
 these type of operations to be succinctly expressed in one
 operation.
 

doc/source/getting_started/comparison/comparison_with_stata.rst

@@ -634,7 +634,7 @@ For example, to subtract the mean for each observation by smoker group.
  generate adj_total_bill = total_bill - group_bill
 
 
-pandas ``groubpy`` provides a ``transform`` mechanism that allows
+pandas ``groupby`` provides a ``transform`` mechanism that allows
 these type of operations to be succinctly expressed in one
 operation.
 

doc/source/user_guide/io.rst

@@ -488,7 +488,7 @@ specification:
 
 .. versionadded:: 0.21.0
 
-Specifying ``dtype='cateogry'`` will result in an unordered ``Categorical``
+Specifying ``dtype='category'`` will result in an unordered ``Categorical``
 whose ``categories`` are the unique values observed in the data. For more
 control on the categories and order, create a
 :class:`~pandas.api.types.CategoricalDtype` ahead of time, and pass that for
@@ -1679,7 +1679,7 @@ S3 URLs are handled as well but require installing the `S3Fs
 
  df = pd.read_csv('s3://pandas-test/tips.csv')
 
-If your S3 bucket requires cedentials you will need to set them as environment
+If your S3 bucket requires credentials you will need to set them as environment
 variables or in the ``~/.aws/credentials`` config file, refer to the `S3Fs
 documentation on credentials
 <https://s3fs.readthedocs.io/en/latest/#credentials>`_.
@@ -2078,7 +2078,7 @@ Dates written in nanoseconds need to be read back in nanoseconds:
 
  json = dfj2.to_json(date_unit='ns')
 
- # Try to parse timestamps as millseconds -> Won't Work
+ # Try to parse timestamps as milliseconds -> Won't Work
  dfju = pd.read_json(json, date_unit='ms')
  dfju
 

doc/source/user_guide/timeseries.rst

@@ -1133,7 +1133,7 @@ Valid business hours are distinguished by whether it started from valid ``Busine
  pd.Timestamp('2014-08-01 17:00') + bh
  pd.Timestamp('2014-08-01 23:00') + bh
 
- # Although 2014-08-02 is Satuaday,
+ # Although 2014-08-02 is Saturday,
  # it is valid because it starts from 08-01 (Friday).
  pd.Timestamp('2014-08-02 04:00') + bh
 

doc/source/whatsnew/v0.10.1.rst

@@ -170,7 +170,7 @@ combined result, by using ``where`` on a selector table.
  df_mt, selector='df1_mt')
  store
 
- # indiviual tables were created
+ # individual tables were created
  store.select('df1_mt')
  store.select('df2_mt')
 

doc/source/whatsnew/v0.14.0.rst

@@ -816,7 +816,7 @@ Enhancements
 - Implemented ``Panel.pct_change`` (:issue:`6904`)
 - Added ``how`` option to rolling-moment functions to dictate how to handle resampling; :func:`rolling_max` defaults to max,
  :func:`rolling_min` defaults to min, and all others default to mean (:issue:`6297`)
-- ``CustomBuisnessMonthBegin`` and ``CustomBusinessMonthEnd`` are now available (:issue:`6866`)
+- ``CustomBusinessMonthBegin`` and ``CustomBusinessMonthEnd`` are now available (:issue:`6866`)
 - :meth:`Series.quantile` and :meth:`DataFrame.quantile` now accept an array of
  quantiles.
 - :meth:`~DataFrame.describe` now accepts an array of percentiles to include in the summary statistics (:issue:`4196`)

doc/source/whatsnew/v0.14.1.rst

@@ -247,7 +247,7 @@ Bug Fixes
 - Bug in ``DatetimeIndex`` comparison doesn't handle ``NaT`` properly (:issue:`7529`)
 - Bug in passing input with ``tzinfo`` to some offsets ``apply``, ``rollforward`` or ``rollback`` resets ``tzinfo`` or raises ``ValueError`` (:issue:`7465`)
 - Bug in ``DatetimeIndex.to_period``, ``PeriodIndex.asobject``, ``PeriodIndex.to_timestamp`` doesn't preserve ``name`` (:issue:`7485`)
-- Bug in ``DatetimeIndex.to_period`` and ``PeriodIndex.to_timestanp`` handle ``NaT`` incorrectly (:issue:`7228`)
+- Bug in ``DatetimeIndex.to_period`` and ``PeriodIndex.to_timestamp`` handle ``NaT`` incorrectly (:issue:`7228`)
 - Bug in ``offsets.apply``, ``rollforward`` and ``rollback`` may return normal ``datetime`` (:issue:`7502`)
 - Bug in ``resample`` raises ``ValueError`` when target contains ``NaT`` (:issue:`7227`)
 - Bug in ``Timestamp.tz_localize`` resets ``nanosecond`` info (:issue:`7534`)

doc/source/whatsnew/v0.19.0.rst

@@ -1513,7 +1513,7 @@ Bug Fixes
 - Bug in ``Series`` comparison may output incorrect result if rhs contains ``NaT`` (:issue:`9005`)
 - Bug in ``Series`` and ``Index`` comparison may output incorrect result if it contains ``NaT`` with ``object`` dtype (:issue:`13592`)
 - Bug in ``Period`` addition raises ``TypeError`` if ``Period`` is on right hand side (:issue:`13069`)
-- Bug in ``Peirod`` and ``Series`` or ``Index`` comparison raises ``TypeError`` (:issue:`13200`)
+- Bug in ``Period`` and ``Series`` or ``Index`` comparison raises ``TypeError`` (:issue:`13200`)
 - Bug in ``pd.set_eng_float_format()`` that would prevent NaN and Inf from formatting (:issue:`11981`)
 - Bug in ``.unstack`` with ``Categorical`` dtype resets ``.ordered`` to ``True`` (:issue:`13249`)
 - Clean some compile time warnings in datetime parsing (:issue:`13607`)

doc/source/whatsnew/v0.21.0.rst

@@ -263,7 +263,7 @@ Now, to find prices per store/product, we can simply do:
 See the :ref:`documentation <groupby.pipe>` for more.
 
 
-.. _whatsnew_0210.enhancements.reanme_categories:
+.. _whatsnew_0210.enhancements.rename_categories:
 
 ``Categorical.rename_categories`` accepts a dict-like
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
@@ -418,7 +418,7 @@ New Behavior, without regard to the bottleneck installation:
 
  s.sum()
 
-Note that this also changes the sum of an empty ``Series``. Previously this always returned 0 regardless of a ``bottlenck`` installation:
+Note that this also changes the sum of an empty ``Series``. Previously this always returned 0 regardless of a ``bottleneck`` installation:
 
 .. code-block:: ipython