Pandas DataFrame.axes

Pandas DataFrame.axes

The DataFrame.axes property in pandas is used to return a list of row and column axis labels for the DataFrame. This is a convenient way to inspect the structure of the DataFrame by accessing the index (rows) and columns.

Syntax

The syntax for accessing the axes property is:

DataFrame.axes

Here, DataFrame refers to the pandas DataFrame whose axes (row and column labels) are being accessed.

Returns

A list containing two elements:

  • Index: Row axis labels (index).
  • Index: Column axis labels (columns).

Examples

Accessing Axes Labels

You can use the axes property to access the row and column labels of a DataFrame.

Python Program

import pandas as pd

# Create a DataFrame
data = {
    'Name': ['Arjun', 'Ram', 'Suresh'],
    'Age': [25, 30, 35],
    'Salary': [70000, 80000, 90000]
}
df = pd.DataFrame(data)

# Access the axes of the DataFrame
print("Row and Column Axes:")
print(df.axes)

Output

Row and Column Axes:
[RangeIndex(start=0, stop=3, step=1), Index(['Name', 'Age', 'Salary'], dtype='object')]

Accessing Row Axis (Index)

You can access only the row axis labels (index) by selecting the first element of the axes list.

Python Program

import pandas as pd

# Create a DataFrame
data = {
    'Name': ['Arjun', 'Ram', 'Suresh'],
    'Age': [25, 30, 35],
    'Salary': [70000, 80000, 90000]
}
df = pd.DataFrame(data)

# Access the row axis labels
print("Row Axis (Index):")
print(df.axes[0])

Output

Row Axis (Index):
RangeIndex(start=0, stop=3, step=1)

Accessing Column Axis (Columns)

You can access only the column axis labels by selecting the second element of the axes list.

Python Program

import pandas as pd

# Create a DataFrame
data = {
    'Name': ['Arjun', 'Ram', 'Suresh'],
    'Age': [25, 30, 35],
    'Salary': [70000, 80000, 90000]
}
df = pd.DataFrame(data)

# Access the column axis labels
print("Column Axis (Columns):")
print(df.axes[1])

Output

Column Axis (Columns):
Index(['Name', 'Age', 'Salary'], dtype='object')

Using Axes in Operations

You can use the axes property in operations, such as renaming or iterating over row and column labels.

Python Program

import pandas as pd

# Create a DataFrame
data = {
    'Name': ['Arjun', 'Ram', 'Suresh'],
    'Age': [25, 30, 35],
    'Salary': [70000, 80000, 90000]
}
df = pd.DataFrame(data)

# Rename columns using the column axis labels
new_columns = [col.upper() for col in df.axes[1]]
df.columns = new_columns

print("DataFrame with Renamed Columns:")
print(df)

Output

DataFrame with Renamed Columns:
     NAME  AGE  SALARY
0   Arjun   25  70000
1     Ram   30  80000
2   Suresh   35  90000

Summary

In this tutorial, we explored the DataFrame.axes property in pandas. Key points include:

  • Using axes to access row and column labels
  • Accessing the row axis (index) and column axis separately
  • Using axes in operations like renaming columns

The DataFrame.axes property is a simple yet powerful tool for inspecting the structure of a DataFrame and performing label-based operations.

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