From 259ad4194e2a42682172e206dcfed71fd1a0ae19 Mon Sep 17 00:00:00 2001 From: Maximilian Roos Date: Mon, 23 Mar 2020 13:47:31 -0400 Subject: [PATCH] update panel documentation --- doc/pandas.rst | 17 ++++++++--------- 1 file changed, 8 insertions(+), 9 deletions(-) diff --git a/doc/pandas.rst b/doc/pandas.rst index b1660e48dd2..9bd3f796cf9 100644 --- a/doc/pandas.rst +++ b/doc/pandas.rst @@ -6,7 +6,7 @@ Working with pandas =================== One of the most important features of xarray is the ability to convert to and -from :py:mod:`pandas` objects to interact with the rest of the PyData + ecosystem. For example, for plotting labeled data, we highly recommend using the visualization `built in to pandas itself`__ or provided by the pandas aware libraries such as `Seaborn`__. @@ -112,8 +112,8 @@ automatically stacking them into a ``MultiIndex``. :py:meth:`DataArray.to_pandas()` is a shortcut that lets you convert a DataArray directly into a pandas object with the same -dimensionality (i.e., a 1D array is converted to a :py:class:`~pandas.Series`, -2D to :py:class:`~pandas.DataFrame` and 3D to ``pandas.Panel``): +dimensionality (i.e., a 1D array is converted to a :py:class:`~pandas.Series` and +2D to :py:class:`~pandas.DataFrame`): .. ipython:: python @@ -151,11 +151,10 @@ However, you will need to set dimension names explicitly, either with the Transitioning from pandas.Panel to xarray ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -``Panel``, pandas' data structure for 3D arrays, has always -been a second class data structure compared to the Series and DataFrame. To -allow pandas developers to focus more on its core functionality built around -the DataFrame, pandas has deprecated ``Panel``. It will be removed in pandas -0.25. +``Panel``, pandas' data structure for 3D arrays, was always a second class +data structure compared to the Series and DataFrame. To allow pandas +developers to focus more on its core functionality built around the +DataFrame, pandas removed ``Panel``. xarray has most of ``Panel``'s features, a more explicit API (particularly around indexing), and the ability to scale to >3 dimensions with the same interface. @@ -210,7 +209,7 @@ You can also easily convert this data into ``Dataset``: array.to_dataset(dim='dim_0') Here, there are two data variables, each representing a DataFrame on panel's -``items`` axis, and labelled as such. Each variable is a 2D array of the +``items`` axis, and labeled as such. Each variable is a 2D array of the respective values along the ``items`` dimension. While the xarray docs are relatively complete, a few items stand out for Panel users: