Pandas DataFrame.ndim

Pandas DataFrame.ndim

The DataFrame.ndim property in pandas returns the number of dimensions of the DataFrame. Since a pandas DataFrame is inherently two-dimensional, this property always returns 2.

Syntax

The syntax for accessing the ndim property is:

DataFrame.ndim

Here, DataFrame refers to the pandas DataFrame whose dimensionality is being accessed.

Returns

An integer indicating the number of dimensions of the DataFrame. For all DataFrames, this value is always 2.

Examples

Basic Usage of DataFrame.ndim

Use the ndim property to check the number of dimensions of a DataFrame.

Python Program

import pandas as pd

# Create a DataFrame
data = {
    'Name': ['Arjun', 'Ram', 'Suresh'],
    'Age': [25, 30, 35],
    'Salary': [70000.5, 80000.0, 90000.0]
}
df = pd.DataFrame(data)

# Access the ndim property
print("Number of Dimensions:")
print(df.ndim)

Output

Number of Dimensions:
2

Using ndim with an Empty DataFrame

The ndim property also applies to empty DataFrames, and it will still return 2.

Python Program

import pandas as pd

# Create an empty DataFrame
empty_df = pd.DataFrame()

# Access the ndim property
print("Number of Dimensions of an Empty DataFrame:")
print(empty_df.ndim)

Output

Number of Dimensions of an Empty DataFrame:
2

Comparison with Other Pandas Objects

The ndim property can be used to check the dimensions of different pandas objects like Series or DataFrame.

Python Program

import pandas as pd

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

# Create a Series
series = pd.Series([10, 20, 30])

# Access the ndim property for both
print("Number of Dimensions in DataFrame:")
print(df.ndim)

print("Number of Dimensions in Series:")
print(series.ndim)

Output

Number of Dimensions in DataFrame:
2
Number of Dimensions in Series:
1

Summary

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

  • The ndim property returns the number of dimensions of a DataFrame, which is always 2.
  • It applies to both regular and empty DataFrames.
  • The ndim property can be used to compare dimensions across different pandas objects like Series and DataFrame.

The DataFrame.ndim property is a simple yet effective way to verify the dimensionality of a DataFrame.

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