Pandas Panel (Legacy – For Reference Only)

Introduction – What Was a Pandas Panel?

A Pandas Panel was a three-dimensional data structure designed for working with data that has items, major axis (rows), and minor axis (columns)—similar to a collection of DataFrames. It was part of older versions of Pandas, but is now deprecated since version 0.25.0 and fully removed in later versions.

In this guide, you’ll learn:

• What a Panel is and how it was structured
• How to create and access data in Panels (for legacy understanding)
• Why Panels were deprecated
• Modern alternatives using MultiIndex or xarray

1. What is a Panel in Pandas?

A Panel was a container for 3D data, like a dictionary of DataFrames.

Structure:

• Items → Axis 0 → DataFrames (like pages)
• Major axis → Axis 1 → Rows
• Minor axis → Axis 2 → Columns

Think of it as: Panel[Item][Row][Column]

2. Creating a Panel (Legacy Syntax)

import pandas as pd
import numpy as np

data = {
    'Item1': pd.DataFrame(np.random.randn(3, 4)),
    'Item2': pd.DataFrame(np.random.randn(3, 4))
}

panel = pd.Panel(data)
print(panel)

Output (in older Pandas versions):

<class 'pandas.core.panel.Panel'>
Dimensions: 2 (items) x 3 (major_axis) x 4 (minor_axis)
Items axis: Item1 to Item2
Major axis: 0 to 2
Minor axis: 0 to 3

This will raise an error in Pandas ≥ 1.0.

3. Accessing Data from Panel

panel['Item1']            # Returns DataFrame
panel['Item1'].iloc[0]    # Returns a row from Item1
panel['Item2'].loc[1, 2]  # Access specific cell from Item2

Access via item labels, then use standard DataFrame methods.

4. Why Was Panel Deprecated?

5. Modern Alternatives to Panel

Use MultiIndex DataFrames

arrays = [
    ['Item1', 'Item1', 'Item2', 'Item2'],
    [0, 1, 0, 1]
]

index = pd.MultiIndex.from_tuples(arrays, names=['Item', 'Index'])
df = pd.DataFrame(np.random.randn(4, 3), index=index, columns=['A', 'B', 'C'])
print(df)

Use xarray (Recommended)

import xarray as xr

data = xr.DataArray(np.random.randn(2, 3, 4),
                    coords=[['Item1', 'Item2'], range(3), ['A', 'B', 'C', 'D']],
                    dims=['Item', 'Row', 'Col'])
print(data)

xarray is ideal for N-dimensional labeled arrays.

Summary – Recap & Next Steps

Pandas Panel was once the go-to tool for 3D labeled data, but due to limited performance and flexibility, it was deprecated in favor of MultiIndex DataFrames and xarray.

Key Takeaways:

• Panels were 3D containers: item × rows × columns
• Deprecated in Pandas 0.25.0 and removed afterward
• Use MultiIndex or xarray for multi-dimensional data handling
• xarray is designed specifically for labeled n-dimensional arrays

Real-world relevance: Use xarray for time series, geospatial, and scientific data that require multi-dimensional indexing.

FAQs – Pandas Panel

Can I still use Panel in the latest version of Pandas?
No. Panels are fully removed since Pandas 1.0. Use xarray or MultiIndex DataFrames instead.

Why not just use nested dictionaries or lists of DataFrames?
While possible, MultiIndex or xarray offers better performance and labeling.

Is there a direct migration path from Panel to DataFrame?
Yes. Use panel.to_frame() (in older versions) to convert Panels to stacked DataFrames.

What is the best alternative to Panel today?
For labeled multi-dimensional data, xarray is the preferred replacement.