How to Check Shape of Data in Python Easily

To check the shape of data in Python, use .shape for NumPy arrays and pandas DataFrames, which returns the dimensions as a tuple. For lists, use len() for length or nested loops to find dimensions.

Syntax

Here are common ways to check the shape of data in Python:

• array.shape: Returns a tuple with the size of each dimension for NumPy arrays or pandas DataFrames.
• len(list): Returns the length of a list (number of elements).

python

import numpy as np
import pandas as pd

# NumPy array shape
array = np.array([[1, 2, 3], [4, 5, 6]])
print(array.shape)  # (2, 3)

# pandas DataFrame shape
df = pd.DataFrame({'A': [1, 2], 'B': [3, 4]})
print(df.shape)  # (2, 2)

# List length
lst = [1, 2, 3, 4]
print(len(lst))  # 4

Output

(2, 3)
(2, 2)
4

Example

This example shows how to check the shape of a NumPy array, a pandas DataFrame, and a nested list.

python

import numpy as np
import pandas as pd

# Create a 3x4 NumPy array
np_array = np.arange(12).reshape(3, 4)
print('NumPy array shape:', np_array.shape)

# Create a pandas DataFrame with 3 rows and 2 columns
df = pd.DataFrame({'X': [10, 20, 30], 'Y': [40, 50, 60]})
print('DataFrame shape:', df.shape)

# Nested list (3 rows, 4 columns)
nested_list = [[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]]
print('List length:', len(nested_list))
print('Length of first inner list:', len(nested_list[0]))

Output

NumPy array shape: (3, 4)
DataFrame shape: (3, 2)
List length: 3
Length of first inner list: 4

Common Pitfalls

Some common mistakes when checking data shape include:

• Using len() on nested lists only gives the outer list size, not full dimensions.
• Trying to use .shape on plain Python lists causes errors because lists don't have this attribute.
• Confusing rows and columns order in the shape tuple.

python

lst = [[1, 2], [3, 4]]

# Wrong: This will cause an error
# print(lst.shape)  # AttributeError: 'list' object has no attribute 'shape'

# Right: Use len() for outer and inner lists
print(len(lst))       # 2 (number of rows)
print(len(lst[0]))    # 2 (number of columns)

Output

2
2

Quick Reference

Summary of how to check shape or size of data in Python:

Data Type	How to Check Shape/Size	Returns
NumPy array	array.shape	Tuple of dimensions (rows, columns, ...)
pandas DataFrame	df.shape	Tuple of (rows, columns)
Python list	len(list)	Length of outer list
Nested list	len(list) and len(list[0])	Outer and inner list lengths

Key Takeaways

Use .shape to get dimensions of NumPy arrays and pandas DataFrames.

For plain Python lists, use len() to find length; nested lists need checking inner lists separately.

Trying .shape on lists causes errors because lists don't have this attribute.

The shape tuple shows (rows, columns) order for 2D data structures.

Always verify data type before checking shape to avoid mistakes.