Pandas How To Uncategorized Which data structure of the Pandas work with 3D data?

Which data structure of the Pandas work with 3D data?

Pandas is a Python library that provides tools for data analysis and manipulation. Its core data structure is the DataFrame, which is a 2D table-like structure that can hold data of various types, including numerical, categorical, and textual. Each column of the DataFrame represents a variable or a feature, while each row represents a single observation or data point.

In addition to the DataFrame, Pandas also provides a 3D data structure called Panel. A Panel is a container that holds multiple DataFrames, each of which represents a 2D slice of the data. A Panel has three axes: items, major_axis, and minor_axis. The items axis corresponds to the different DataFrames contained within the Panel, while the major_axis and minor_axis axes correspond to the rows and columns of the DataFrames, respectively.

You can create a Panel in Pandas using the pd.Panel() constructor. The data in a Panel can be accessed using the iloc[] and loc[] indexing methods, which allow you to select data based on the different axes of the panel.

However, it’s worth noting that as of Pandas version 1.0, the Panel object is considered to be deprecated and is no longer actively developed. Instead, Pandas recommends using other data structures, such as multi-index DataFrames or xarray, for handling 3D data. These structures provide more flexibility and are better suited for handling complex, multi-dimensional data.

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