What Does the `axis` Parameter Mean in Pandas Functions?

Axis in Pandas: Understanding Its Meaning

In Pandas, the axis keyword parameter in functions such as mean() defines along which axis the operation is performed.

Consider the following code:

import pandas as pd
import numpy as np

dff = pd.DataFrame(np.random.randn(1,2),columns=list('AB'))

This creates a dataframe:

+------------+---------+--------+
|            |  A      |  B     |
+------------+---------+---------
|      0     | 0.626386| 1.52325|
+------------+---------+--------+

Now, let's calculate the mean along the rows (axis=1):

dff.mean(axis=1)

This gives the following result:

0    1.074821
dtype: float64

Counterintuitively, the expected result is:

A    0.626386
B    1.523255
dtype: float64

Understanding the Axis Parameter

The axis parameter specifies the direction in which the operation is performed.

• axis=0: Operates along the rows (index) of the dataframe.
• axis=1: Operates along the columns (columns) of the dataframe.

In the given example, the mean is calculated along the columns (axis=1), resulting in a single value for each row.

Visualizing the Axis

To visualize the axis, consider the following diagram:

+------------+---------+--------+
|            |  A      |  B     |
+------------+---------+---------
|      0     | 0.626386| 1.52325|----axis=1----->
+------------+---------+--------+
             |         |
             | axis=0  |
             ↓         ↓

The red arrow represents axis=1, which operates along the columns. The green arrow represents axis=0, which operates along the rows.

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