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Panel in Pandas

To put it simply, a Panel in Pandas is a three-dimensional container of data. Think of it like a box that can hold information in width, height, and depth. It's a term borrowed from econometrics and is not commonly used in Python. The name 'Panel' comes from 'Panel Data', which is data that follows a given sample over a period and time and across various sub-groups.

What Exactly is a Panel in Pandas?

Simply put, a Panel is a three-dimensional data structure in Pandas. Imagine a regular spreadsheet, but with an added layer of depth - that's what a Panel looks like. It can hold items in width, height, and depth, offering a unique way of dealing with complex data.

Here's a quick overview of how the data in a Panel is organized:

  1. 'Items' axis: These are like the different spreadsheets within a workbook, each holding a unique dataset.
  2. 'Major_axis' : This corresponds to the rows within each spreadsheet or 'item.'
  3. 'Minor_axis' : These are the individual columns within each spreadsheet.

Creating a Panel is easy. Here's an example of how you might do it:

# Import pandas
import pandas as pd
import numpy as np

# Create a 3D numpy array
data = np.random.rand(2,5,4)

# Create a Panel
panel = pd.Panel(data)

# Or create a Panel from a dictionary of DataFrames
data = {'Item1' : pd.DataFrame(np.random.randn(4, 3)), 
        'Item2' : pd.DataFrame(np.random.randn(4, 2))}
panel = pd.Panel(data)

However, it's important to note that since version 0.20.0, the Panel is deprecated in Pandas. This means it might not be available in the future versions of Pandas. As an alternative, Pandas recommends using MultiIndex DataFrame, another powerful tool for handling multidimensional data.

In conclusion, while the Panel in Pandas may not be commonly used today, it's an interesting part of the library's history and capabilities. It showcases the versatility of Python and Pandas when it comes to handling and analyzing complex, multidimensional data.


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