Extending a pandas panel frame along the minor axis

pandas, panel, python

Solution

This doesn't work right now see this, https://github.com/pydata/pandas/issues/2578 But you can accomplish what you want this way. This is a pretty cheap operation as nothing is copied.

In [18]: x = pf.transpose(2,0,1)

In [19]: x
Out[19]: 
<class 'pandas.core.panel.Panel'>
Dimensions: 4 (items) x 3 (major_axis) x 100 (minor_axis)
Items axis: A to D
Major_axis axis: df1 to df3
Minor_axis axis: 2013-01-01 00:00:00 to 2013-04-10 00:00:00

In [20]: x['E'] = new_df

In [21]: x.transpose(1,2,0)
Out[21]: 
<class 'pandas.core.panel.Panel'>
Dimensions: 3 (items) x 100 (major_axis) x 5 (minor_axis)
Items axis: df1 to df3
Major_axis axis: 2013-01-01 00:00:00 to 2013-04-10 00:00:00
Minor_axis axis: A to E

Problem

I would like to extend a Panel frame of data along a minor axis in pandas. I start off creating a `dic` of `DataFrame`s to generate a Panel. ``` import pandas as pd import numpy as np rng = pd.date_range('1/1/2013',periods=100,freq='D') df1 = pd.DataFrame(np.random.randn(100, 4), index = rng, columns = ['A','B','C','D']) df2 = pd.DataFrame(np.random.randn(100, 4), index = rng, columns = ['A','B','C','D']) df3 = pd.DataFrame(np.random.randn(100, 4), index = rng, columns = ['A','B','C','D']) pf = pd.Panel({'df1':df1,'df2':df2,'df3':df3}) ``` As expected I, find I have a panel with the following dimensions: Dimensions: 3 (items) x 100 (major_axis) x 4 (minor_axis) Items axis: df1 to df3 Major_axis axis: 2013-01-01 00:00:00 to 2013-04-10 00:00:00 Minor_axis axis: A to D I would now like to add a new data set to the Minor axis: ``` pf['df1']['E'] = pd.DataFrame(np.random.randn(100, 1), index = rng) pf['df2']['E'] = pd.DataFrame(np.random.randn(100, 1), index = rng) pf['df2']['E'] = pd.DataFrame(np.random.randn(100, 1), index = rng) ``` I find that after adding this new minor axis the shape of the panel array dimensions has not changed: ``` shape(pf) ``` [3,100,4] I am able to access the data for each of the items in the major_axis: ``` pf.ix['df1',-10:,'E'] ``` 2013-04-01 0.168205 2013-04-02 0.677929 2013-04-03 0.845444 2013-04-04 0.431610 2013-04-05 0.501003 2013-04-06 -0.403605 2013-04-07 -0.185033 2013-04-08 0.270093 2013-04-09 1.569180 2013-04-10 -1.374779 Freq: D, Name: E But if I extend the slicing to include more than one major axis: ``` pf.ix[:,:,'E'] ``` Then I encounter an error saying that 'E' is unknown. Can anyone suggest where I am going wrong or a better way of performing this operation?

Original source