Panel

A panel is an important container for 3-D data. It is somewhat less used and it is responsible for the name pandas pan(el)-da(ta)-s. Nowadays Panel is not used and is also not available on the newer version of Python. Panels are replaced by the multi-index properties of dataframe. Its 3 axes are named to so that they describe the operations that are performed on them.

  • items: axis 0, each item corresponds to a DataFrame contained inside
  • major_axis: axis 1, it is the index (rows) of each of the DataFrames
  • minor_axis: axis 2, it is the columns of each of the DataFrames

Construction of Panels works about like you would expect:

From 3D ndarray

For the construction of the panel from 3d ndarray 3 parameters are passed for each of the axes.

panel Robofied

From dict of Dataframe Objects

A dictionary of dataframe can also be used for the construction of Panel.

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Note: – Values in dataframe need only be convertible to dataframe. Thus they can be of the other valid inputs to dataframe as per above.

Selection/ Deletion/ Addition

A panel is a dict of dataframes just like dataframe is dict of series. Selecting a particular dataframe is same as selecting a key in the dict i.e by using square brackets.

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The addition is also same as of the dict i.e just by giving the name of the dataframe in the square brackets and assigning the dataframe.

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Deletion is also same as dict.

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Transpose

A Panel can be rearranged using its transpose method.

Transpose Robofied

Indexing and Selection

We can select any of the dataframe from a panel by using square brackets just like dict. But when slicing over major or minor axis we use two functions major_xs and minor_xs.

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Conversion to Dataframe

A Panel can be converted to a multi-indexed dataframe by where the axis of the panel will form the first index and each dataframe in the major axis will form the second index.

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Over the last few years, pandas has increased in both breadth and depth, with new features, datatype support, and manipulation routines. As a result, supporting efficient indexing and functional routines for Series, Dataframe and Panel has contributed to an increasingly fragmented and difficult-to-understand codebase.

The 3-D structure of a Panel is much less common for many types of data analysis than the 1-D of the Series or the 2-D of the Dataframe. Going forward it makes sense for pandas to focus on these areas exclusively.

Oftentimes, one can simply use a MultiIndex Dataframe for easily working with higher dimensional data.

In addition, the xarray package was built from the ground up, specifically in order to support the multi-dimensional analysis that is one of Panels main use cases. Here is a link to the xarray panel-transition documentation

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