3 Ways to Create Pandas Panel – Learn to Transpose & Deprecate a Panel

Python Pandas Panel is an important container for data which is 3-dimensional. It is a little less used. The term panel data has its origins in econometrics and is actually partially responsible for the name of the library pandas: panel datas.

The naming of the three axes should be done in a way so as to give a meaning to the operations which involve panel data. If you want to slice or dice a collection or rather dictionary of DataFrame objects, the axis names might seem slightly vague to you:

  • items: This is axis 0, where each item corresponds to a DataFrame.
  • major_axis: This is axis 1 and it contains the index or rows of each DataFrame.
  • minor_axis: This is axis 2 and it contains the columns of each DataFrame.

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1. Python Pandas Panel Parameters

Before we start the Pandas Panel Tutorial, here are the parameters of a panel function:

  1. data: The data will be represented by the panel.
  2. items: As mention, it is the axis 0, each item can represent and compare to a DataFrame.
  3. major-axis: This is the axis 1 (Rows of a DataFrame).
  4. minor-axis: This is the axis 2 (columns of a DataFrame).
  5. copy: Boolean value to denote whether data will be copied from inputs.
  6. dtype: Specifies a datatype.

Explore the 5 Core Pandas Options to Customize Your Data

2. How to Create an Empty Panel in Pandas?

Follow this code to create an empty panel in Pandas.

>>> empty = pd.Panel()
>>> empty

Output-

Create Empty panels in Pandas

3. How to Create Pandas Panel?

At first, we will first import the libraries –

>>> import pandas as pd
>>> import numpy as np

There are quite a few ways to create a Panel in Pandas-

  1. From a 3D ndarray while using optional axis labels
  2. Dict (dictionary) of DataFrame objects
  3. DataFrame using to_panel method

3.1. How to Create Panels in Pandas from a 3D ndarray?

Creating panels from 3D ndarray using optional axis labels.

>>> dataflair_pan = pd.Panel(np.random.randn(4,5,4), items=['1' ,’2' ,'3', '4'],major_axis=pd.date_range('1/2/2010', periods=5),minor_axis=['J','K','L','M'])
>>> dataflair_pan

Do you know major Pandas functions used by Data Scientist?

There it is, you have created a Panel from a ndarray successfully.

Pandas Panel created by ndarray

3.2. How to Create Panels in Pandas from a Dict (dictionary)

Creating panels from a dict (dictionary) of DataFrame objects

>>> dataflair_df = {'df1': pd.DataFrame(np.random.randn(5,6)),'df2': pd.DataFrame(np.random.randn(5,3))}
>>> pd.Panel(dataflair_df)

Output-

Pandas Panel created by dict

3.3. How to Create a Panel from a DataFrame?

Creating panels in pandas with a dataframe using a to_panel method.

>>> dataflair_mul = pd.MultiIndex(levels=[['one', 'two'], ['a', 'b']], codes=[[1, 0, 1, 0], [1, 1, 0, 0]])
>>> dataflair_dat = pd.DataFrame({'S1': [2, 3, 4, 5], 'S2': [6, 7, 8, 9]}, index=dataflair_mul)
>>> dataflair_dat.to_panel()

Output-

Pandas Panel created by dataframe

4. Column Selection/Addition/Deletion

4.1 How to Select Column in Panel?

>>> dataflair_pan = pd.Panel(np.random.randn(4,5,4), items=['1' ,'2' ,'3', '4'],major_axis=pd.date_range('1/2/2010', periods=5),minor_axis=['J','K','L','M'])
>>> dataflair_pan

Struggling with Sorting in Pandas?

>>> dataflair_pan['1’]

Output-

Select Column in Pandas Panel

4.2 How to Add Column in Panel?

>>> dataflair_pan['3']=dataflair_pan['1']+dataflair_pan['2']
>>> dataflair_pan['3']

Output-

Add Column in Pandas Panel

4.3 How to Delete Column in Panel?

>>> del dataflair_pan['4']
>>> dataflair_pan

5. How to Transpose a Panel in Pandas?

Let’s start the process of transposing of panels-

Creating a new panel

>>> dataflair_pan = pd.Panel(np.random.randn(4,5,4), items=['1' ,'2' ,'3', '4'],major_axis=pd.date_range('1/2/2010', periods=5),minor_axis=['J','K','L','M'])
>>> dataflair_pan

Output-

Create a Pandas panel

Transposing a panel

>>> dataflair_pan.transpose(1, 2, 0)

Output-

Transposing a pandas panel

6. How to Select a Data from a Pandas Panel?

Creating a Panel

>>> dataflair_pan = pd.Panel(np.random.randn(4,5,4), items=['1' ,'2' ,'3', '4'],major_axis=pd.date_range('1/2/2010', periods=5),minor_axis=['J','K','L','M'])
>>> dataflair_pan

Follow the steps-

1. Selecting an Item
>>> dataflair_pan['2']

Output-

Selecting an Item

2. Selecting a Major Axis
>>> dataflair_pan.major_xs(dataflair_pan.major_axis[3])

Output-

Selecting a Major Axis

3. Selecting a Minor Axis
>>> dataflair_pan.minor_xs('K')

Output-

Selecting a Minor Axis

7. How to Deprecate a Pandas Panel?

Since Pandas has increased in its versatility, efficient routines for indexing and functioning for Series, Panels, and DataFrames has made codes difficult to understand. A 3-D Panel is uncommon for Data Analysis, unlike a 1-D Series or 2-D DataFrame. In fact, the xarray package was built specifically to support the panel’s multidimensional analysis.

Hence, we deprecate the panel to a Multi-Index DataFrame or an xarray.

Deprecating to a Multi-Index DataFrame

>>> dataflair_pan.to_frame()

Output-

Deprecate a Pandas Panel

8. Summary

Panels play an important role in Pandas. Now, you studied 3 ways to create a panel in pandas – from ndarray, dict and dataframes. In this article, we practiced how to transpose and deprecate a Panel. In short, you are ready to face any query related to panels. But, don’t forget to check next pandas tutorial – Iteration in pandas.

If you have any query or suggestion, please approach our comment section.

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