From 5d01187ea02b770304142f4d2f55606f27d9856e Mon Sep 17 00:00:00 2001 From: Takuya N Date: Fri, 15 Feb 2019 13:07:54 +0900 Subject: [PATCH] Fix typos in docs (#25305) --- doc/source/user_guide/groupby.rst | 2 +- doc/source/whatsnew/v0.10.0.rst | 2 +- doc/source/whatsnew/v0.16.1.rst | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/doc/source/user_guide/groupby.rst b/doc/source/user_guide/groupby.rst index 2c2e5c5425216c..e4dd82afcdf65b 100644 --- a/doc/source/user_guide/groupby.rst +++ b/doc/source/user_guide/groupby.rst @@ -1317,7 +1317,7 @@ arbitrary function, for example: df.groupby(['Store', 'Product']).pipe(mean) where ``mean`` takes a GroupBy object and finds the mean of the Revenue and Quantity -columns repectively for each Store-Product combination. The ``mean`` function can +columns respectively for each Store-Product combination. The ``mean`` function can be any function that takes in a GroupBy object; the ``.pipe`` will pass the GroupBy object as a parameter into the function you specify. diff --git a/doc/source/whatsnew/v0.10.0.rst b/doc/source/whatsnew/v0.10.0.rst index bc2a4918bc27b4..2d6550bb6888dd 100644 --- a/doc/source/whatsnew/v0.10.0.rst +++ b/doc/source/whatsnew/v0.10.0.rst @@ -370,7 +370,7 @@ Updated PyTables Support df1.get_dtype_counts() - performance improvements on table writing -- support for arbitrarly indexed dimensions +- support for arbitrarily indexed dimensions - ``SparseSeries`` now has a ``density`` property (:issue:`2384`) - enable ``Series.str.strip/lstrip/rstrip`` methods to take an input argument to strip arbitrary characters (:issue:`2411`) diff --git a/doc/source/whatsnew/v0.16.1.rst b/doc/source/whatsnew/v0.16.1.rst index 7621cb9c1e27c7..cbcb23e3565771 100644 --- a/doc/source/whatsnew/v0.16.1.rst +++ b/doc/source/whatsnew/v0.16.1.rst @@ -136,7 +136,7 @@ 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. .. code-block:: ipython