Pandas Panel

　 　Basic operations of Pandas Panel

Panel data3D container. Term Panel data Originating from econometrics, the name comes from pandas − pan(el)-da(ta)-s.

3The names of the axes are described as follows- −

items − Axis 0, each item corresponds to a DataFrame contained within.

major_axis − Axis1which is each DataFrame's index (row).

minor_axis − Axis2which is each DataFrame's column.

pandas.Panel()

Panels can be created using the following constructor:- −

　pandas.Panel(data, items, major_axis, minor_axis, dtype, copy)

The parameters of the constructor are as follows:

Create Panel

Panels can be created in various ways, such as:

Create from ndarrays Create from DataFrame dictionary

Create from ndarrays

　# Create an empty panel
　import pandas as pd
　import numpy as np
　data = np.random.rand(2,4,5)
　p = pd.Panel(data)
　print(p)

The running result is as follows:

　<class 'pandas.core.panel.Panel'>
　Dimensions:　2　(items) x　4　(major_axis) x　5　(minor_axis)
　Items axis: 0 to　1
　Major_axis axis: 0 to　3
　Minor_axis axis: 0 to　4

Create from DataFrame dictionary

　　# Create an empty panel
　
　　import pandas
　　　as pd　　
　
　　import numpy
　　　as np　　
　data = {
　　'Item1': pd.
　　DataFrame(np.
　　random.randn(4,　3))　
　　
　　　　
　　'Item2': pd.
　　DataFrame(np.
　　random.randn(4,　2))}　　
　p = pd.
　　Panel(data)　　
　print(p)

Running Results:

　Dimensions:　2　(items) x　4　(major_axis) x　3　(minor_axis)
　Items axis: Item1　to Item2
　Major_axis axis: 0 to　3
　Minor_axis axis: 0 to　2

Create an empty Panel

A Panel can be created using the Panel constructor function, as shown below:

　# Create an empty panel
　import pandas as pd
　p = pd.Panel()
　print(p)

Running Results:

　<class 'pandas.core.panel.Panel'>
　Dimensions: 0 (items) x 0 (major_axis) x 0 (minor_axis)
　Items axis: None
　Major_axis axis: None
　Minor_axis axis: None

Query Data from Panel

You can query data from the panel using the following three items:

Items Major_axis Minor_axis

Query using Items

　# Create an empty panel
　import pandas as pd
　import numpy as np
　data = {

Running Results:

　0　　　　　　　　　1　　　　　　　　2
　0 0.488224　-0.128637　0.930817
　1　0.417497　0.896681　0.576657
　2　-2.775266　0.571668　0.290082
　3　-0.400538　-0.144234　1.110535

Query item from two items1, the output is a DataFrame with4Rows3Columns' DataFrame, respectively Major_axis and Minor_axis.

Query using major_axis

You can access the data using the panel.major_axis(index) method.

　# Create an empty panel
　import pandas as pd
　import numpy as np
　data = {'Item1' : pd.DataFrame(np.random.randn(4,　3))　
　　　　'Item2' : pd.DataFrame(np.random.randn(4,　2))}
　p = pd.Panel(data)
　print(p.major_xs(1))

Running Results:

　　　　Item1　Item2
　0 0.417497　0.748412
　1　0.896681　-0.557322
　2　0.576657　NaN

Query using minor_axis

You can access the data using the panel.minor_axis(index) method.

　# Create an empty panel
　import pandas as pd
　import numpy as np
　data = {'Item1' : pd.DataFrame(np.random.randn(4,　3))　
　　　　'Item2' : pd.DataFrame(np.random.randn(4,　2))}
　p = pd.Panel(data)
　print(p.minor_xs(1))

Running Results:

　　　　Item1　Item2
　0　-0.128637　-1.047032
　1　0.896681　-0.557322
　2　0.571668　0.431953
　3　-0.144234　1.302466