From 6e4cc41a1d947fe6098d4628e2aa7e6feaa28fb5 Mon Sep 17 00:00:00 2001 From: Paul <53956863+hutch3232@users.noreply.github.com> Date: Wed, 20 Mar 2024 08:17:30 -0500 Subject: [PATCH] fix minor typos and grammar missing_data.rst --- doc/source/user_guide/missing_data.rst | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/doc/source/user_guide/missing_data.rst b/doc/source/user_guide/missing_data.rst index aea7688c062b8..2e104ac06f9f4 100644 --- a/doc/source/user_guide/missing_data.rst +++ b/doc/source/user_guide/missing_data.rst @@ -88,7 +88,7 @@ To detect these missing value, use the :func:`isna` or :func:`notna` methods. .. warning:: - Experimental: the behaviour of :class:`NA`` can still change without warning. + Experimental: the behaviour of :class:`NA` can still change without warning. Starting from pandas 1.0, an experimental :class:`NA` value (singleton) is available to represent scalar missing values. The goal of :class:`NA` is provide a @@ -105,7 +105,7 @@ dtype, it will use :class:`NA`: s[2] s[2] is pd.NA -Currently, pandas does not yet use those data types using :class:`NA` by default +Currently, pandas does not use those data types using :class:`NA` by default in a :class:`DataFrame` or :class:`Series`, so you need to specify the dtype explicitly. An easy way to convert to those dtypes is explained in the :ref:`conversion section `. @@ -253,8 +253,8 @@ Conversion ^^^^^^^^^^ If you have a :class:`DataFrame` or :class:`Series` using ``np.nan``, -:meth:`Series.convert_dtypes` and :meth:`DataFrame.convert_dtypes` -in :class:`DataFrame` that can convert data to use the data types that use :class:`NA` +:meth:`DataFrame.convert_dtypes` and :meth:`Series.convert_dtypes`, respectively, +will convert your data to use the nullable data types supporting :class:`NA`, such as :class:`Int64Dtype` or :class:`ArrowDtype`. This is especially helpful after reading in data sets from IO methods where data types were inferred.