Write a Python program to find the average of first row in a Panel

A Panel was a 3-dimensional data structure in older versions of pandas (deprecated since v0.25). To find the average of the first row, we use the major_xs() method to select a specific row and then calculate its mean.

Creating a Panel

First, let's create a Panel with sample data ?

import pandas as pd
import numpy as np

# Create data dictionary with DataFrame
data = {'Column1': pd.DataFrame(np.random.randn(5, 3))}

# Create Panel from data
p = pd.Panel(data)
print("Panel values:")
print(p['Column1'])

Panel values:
          0         1         2
0  0.629910  0.275741 -0.083281
1 -0.509143 -1.794204  0.300390
2 -1.944141  0.085508 -0.155167
3  1.551087 -0.671242 -0.838922
4 -0.643543  0.622777  1.112745

Finding Average of First Row

Use major_xs(0) to select the first row and mean() to calculate its average ?

import pandas as pd
import numpy as np

data = {'Column1': pd.DataFrame(np.random.randn(5, 3))}
p = pd.Panel(data)

print("Average of first row is:")
result = p.major_xs(0).mean()
print(result)

Average of first row is:
Column1    0.274124
dtype: float64

How It Works

The major_xs(0) method selects the first row (index 0) across all items in the Panel. The mean() function then calculates the average of all values in that row.

Modern Alternative

Since Panel is deprecated, use MultiIndex DataFrames for 3D data ?

import pandas as pd
import numpy as np

# Create MultiIndex DataFrame instead of Panel
arrays = [['Column1'] * 15, list(range(5)) * 3, [0, 1, 2] * 5]
index = pd.MultiIndex.from_arrays(arrays, names=['item', 'major', 'minor'])
df = pd.DataFrame(np.random.randn(15, 1), index=index, columns=['value'])

# Get average of first row
first_row_avg = df.xs(0, level='major').groupby('item')['value'].mean()
print("Average of first row:")
print(first_row_avg)

Conclusion

Use major_xs(0).mean() to find the average of the first row in a Panel. For modern pandas, prefer MultiIndex DataFrames over deprecated Panel structures.