Merge pull request #11837 from seales/master

Spelling fixes

Author: jorisvandenbossche

doc/source/advanced.rst

@@ -525,7 +525,7 @@ they have a MultiIndex:
 
    df.T.sort_index(level=1, axis=1)
 
-The ``MultiIndex`` object has code to **explicity check the sort depth**. Thus,
+The ``MultiIndex`` object has code to **explicitly check the sort depth**. Thus,
 if you try to index at a depth at which the index is not sorted, it will raise
 an exception. Here is a concrete example to illustrate this:
 

doc/source/api.rst

@@ -552,7 +552,7 @@ These can be accessed like ``Series.dt.<property>``.
 String handling
 ~~~~~~~~~~~~~~~
 ``Series.str`` can be used to access the values of the series as
-strings and apply several methods to it. These can be acccessed like
+strings and apply several methods to it. These can be accessed like
 ``Series.str.<function/property>``.
 
 .. autosummary::

doc/source/basics.rst

@@ -1097,7 +1097,7 @@ Note that the same result could have been achieved using
    ts2.reindex(ts.index).fillna(method='ffill')
 
 :meth:`~Series.reindex` will raise a ValueError if the index is not monotonic
-increasing or descreasing. :meth:`~Series.fillna` and :meth:`~Series.interpolate`
+increasing or decreasing. :meth:`~Series.fillna` and :meth:`~Series.interpolate`
 will not make any checks on the order of the index.
 
 .. _basics.limits_on_reindex_fill:

doc/source/categorical.rst

@@ -178,7 +178,7 @@ It's also possible to pass in the categories in a specific order:
 
 .. note::
 
-    New categorical data are NOT automatically ordered. You must explicity pass ``ordered=True`` to
+    New categorical data are NOT automatically ordered. You must explicitly pass ``ordered=True`` to
     indicate an ordered ``Categorical``.
 
 
@@ -342,7 +342,7 @@ necessarily make the sort order the same as the categories order.
 Multi Column Sorting
 ~~~~~~~~~~~~~~~~~~~~
 
-A categorical dtyped column will partcipate in a multi-column sort in a similar manner to other columns.
+A categorical dtyped column will participate in a multi-column sort in a similar manner to other columns.
 The ordering of the categorical is determined by the ``categories`` of that column.
 
 .. ipython:: python

doc/source/comparison_with_sas.rst

@@ -271,15 +271,15 @@ date/datetime columns.
        date2 = mdy(2, 15, 2015);
        date1_year = year(date1);
        date2_month = month(date2);
-       * shift date to begninning of next interval;
+       * shift date to beginning of next interval;
        date1_next = intnx('MONTH', date1, 1);
        * count intervals between dates;
        months_between = intck('MONTH', date1, date2);
    run;
 
 The equivalent pandas operations are shown below.  In addition to these
 functions pandas supports other Time Series features
-not available in Base SAS (such as resampling and and custom offets) -
+not available in Base SAS (such as resampling and and custom offsets) -
 see the :ref:`timeseries documentation<timeseries>` for more details.
 
 .. ipython:: python
@@ -350,7 +350,7 @@ Sorting in SAS is accomplished via ``PROC SORT``
    run;
 
 pandas objects have a :meth:`~DataFrame.sort_values` method, which
-takes a list of columnns to sort by.
+takes a list of columns to sort by.
 
 .. ipython:: python
 

doc/source/cookbook.rst

@@ -333,7 +333,7 @@ The :ref:`multindexing <advanced.hierarchical>` docs.
 
    # As Labelled Index
    df = df.set_index('row');df
-   # With Heirarchical Columns
+   # With Hierarchical Columns
    df.columns = pd.MultiIndex.from_tuples([tuple(c.split('_')) for c in df.columns]);df
    # Now stack & Reset
    df = df.stack(0).reset_index(1);df

doc/source/dsintro.rst

@@ -46,7 +46,7 @@ Series
 
 .. warning::
 
-   In 0.13.0 ``Series`` has internaly been refactored to no longer sub-class ``ndarray``
+   In 0.13.0 ``Series`` has internally been refactored to no longer sub-class ``ndarray``
    but instead subclass ``NDFrame``, similarly to the rest of the pandas containers. This should be
    a transparent change with only very limited API implications (See the :ref:`Internal Refactoring<whatsnew_0130.refactoring>`)
 

doc/source/ecosystem.rst

@@ -155,7 +155,7 @@ or multi-indexed DataFrames.
 fredapi is a Python interface to the `Federal Reserve Economic Data (FRED) <http://research.stlouisfed.org/fred2/>`__
 provided by the Federal Reserve Bank of St. Louis. It works with both the FRED database and ALFRED database that
 contains point-in-time data (i.e. historic data revisions). fredapi provides a wrapper in python to the FRED
-HTTP API, and also provides several conveninent methods for parsing and analyzing point-in-time data from ALFRED.
+HTTP API, and also provides several convenient methods for parsing and analyzing point-in-time data from ALFRED.
 fredapi makes use of pandas and returns data in a Series or DataFrame. This module requires a FRED API key that
 you can obtain for free on the FRED website.
 

doc/source/enhancingperf.rst

@@ -745,7 +745,7 @@ Technical Minutia Regarding Expression Evaluation
 
 Expressions that would result in an object dtype or involve datetime operations
 (because of ``NaT``) must be evaluated in Python space. The main reason for
-this behavior is to maintain backwards compatbility with versions of numpy <
+this behavior is to maintain backwards compatibility with versions of numpy <
 1.7. In those versions of ``numpy`` a call to ``ndarray.astype(str)`` will
 truncate any strings that are more than 60 characters in length. Second, we
 can't pass ``object`` arrays to ``numexpr`` thus string comparisons must be

doc/source/groupby.rst

@@ -649,7 +649,7 @@ For dataframes with multiple columns, filters should explicitly specify a column
 .. note::
 
    Some functions when applied to a groupby object will act as a **filter** on the input, returning
-   a reduced shape of the original (and potentitally eliminating groups), but with the index unchanged.
+   a reduced shape of the original (and potentially eliminating groups), but with the index unchanged.
    Passing ``as_index=False`` will not affect these transformation methods.
 
    For example: ``head, tail``.