Python NumPy: How to Fix "IndexError: index 0 is out of bounds for axis 0 with size 0"

The IndexError: index 0 is out of bounds for axis 0 with size 0 is a common error when working with NumPy arrays, particularly when dealing with arrays that are unexpectedly empty or have an empty first dimension. This error message specifically indicates that you're trying to access the first element (at index 0) along the first axis (axis 0) of an array that has a size of 0 along that very axis—meaning it's empty in that dimension.

This guide will thoroughly explain why this IndexError occurs due to attempting to index an empty dimension, demonstrate common scenarios that lead to it (like operating on empty arrays or arrays initialized with a zero-sized first dimension), and provide robust solutions, including checking array size/shape before access or using try-except blocks for graceful error handling.

Understanding the Error: Indexing an Empty Axis

NumPy arrays are indexed using zero-based integer positions. For an axis to be indexable at position 0, it must have at least one element, meaning its size along that axis must be 1 or greater.

• Axis 0: Refers to the first dimension of the array (rows in a 2D array, elements in a 1D array).
• Size 0: Indicates that the array has no elements along that specific axis.

The error IndexError: index 0 is out of bounds for axis 0 with size 0 means you're trying to get array[0] (or array[0, ...] for multi-dimensional arrays) when axis 0 is empty. Since there's no element at index 0 (because the size is 0), NumPy raises an IndexError.

Reproducing the Error

Accessing an Element in a Completely Empty 1D Array

import numpy as np

# Create an empty 1D array
empty_1d_array = np.array([])
print(f"Empty 1D array: {empty_1d_array}")  # []
print(f"Shape: {empty_1d_array.shape}")     # (0,)
print(f"Size: {empty_1d_array.size}")       # 0

try:
    # ⛔️ Incorrect: Trying to access the first element (index 0) of an empty array
    first_element_error = empty_1d_array[0]
    print(first_element_error)
except IndexError as e:
    print(f"Error: {e}")

Output:

Empty 1D array: []
Shape: (0,)
Size: 0
Error: index 0 is out of bounds for axis 0 with size 0

Accessing an Element in an Array with Zero Rows (e.g., shape (0, N))

This commonly occurs if you initialize an array to have columns but no rows.

import numpy as np

# Create a 2D array with 0 rows and 3 columns
array_zero_rows = np.zeros((0, 3), dtype=int) # Shape is (0, 3)
print(f"Array with zero rows:\n{array_zero_rows}")      # []
print(f"Shape: {array_zero_rows.shape}")                # (0, 3)
print(f"Size along axis 0: {array_zero_rows.shape[0]}") # 0

try:
    # ⛔️ Incorrect: Trying to access the first row (index 0 along axis 0)
    # when axis 0 has size 0.
    first_row_error = array_zero_rows[0] # or array_zero_rows[0, :]
    print(first_row_error)
except IndexError as e:
    print(f"Error: {e}")

Output:

Array with zero rows:
[]
Shape: (0, 3)
Size along axis 0: 0
Error: index 0 is out of bounds for axis 0 with size 0

Solution 1: Check Array size or shape Before Indexing (Recommended)

Before attempting to access an element by index, always check if the array (or the specific axis) is non-empty.

• array.size: Total number of elements in the array. If array.size == 0, the array is completely empty.
• array.shape[0]: Number of elements along the first axis (number of rows for a 2D array).

import numpy as np

# Case 1: Potentially empty 1D array
arr1 = np.array([])
# arr1 = np.array([10, 20]) # Uncomment to test with non-empty

if arr1.size > 0: # Check if the array has any elements
    print(f"First element of arr1: {arr1[0]}")
else:
    print("arr1 is empty, can not access element at index 0.")

# Case 2: Potentially 2D array with zero rows
arr2 = np.zeros((0, 5)) # Shape (0, 5)
# arr2 = np.zeros((2, 5)) # Uncomment to test with non-empty rows

if arr2.shape[0] > 0: # Check if there's at least one row
    print(f"First row of arr2:\n{arr2[0]}")
else:
    print("arr2 has 0 rows, can not access row at index 0.")

Output:

arr1 is empty, can not access element at index 0.
arr2 has 0 rows, can not access row at index 0.

This pre-emptive check is the most robust way to avoid the IndexError.

Solution 2: Using a try-except IndexError Block for Error Handling

If you anticipate that an array might be empty in some situations and want to handle it gracefully without stopping your program, you can use a try-except block to catch the IndexError.

import numpy as np

empty_array_for_try = np.array([])

try:
    # Attempt to access the element
    val = empty_array_for_try[0]
    print(f"Value: {val}")
except IndexError:
    # This block executes if the IndexError occurs
    print("Caught IndexError: The array is empty or index is out of bounds.")
    # Handle the situation, e.g., assign a default value, log, or skip processing
    val = None # Example: assign a default

# You can also use 'pass' if you want to silently ignore the error (use with caution)
try:
    _ = empty_array_for_try[0]
except IndexError:
    pass # Silently ignore the error if the array is empty

Output:

Caught IndexError: The array is empty or index is out of bounds.

Common Pitfall: Incorrect Array Initialization Leading to Empty Dimensions

Sometimes, the error arises because an array was unintentionally initialized with a zero-sized dimension.

Example: np.zeros((0, N))

If you initialize an array like arr = np.zeros((0, 3), dtype=int), you are explicitly creating an array with 0 rows and 3 columns. Axis 0 has size 0.

import numpy as np

array_explicit_zero_rows = np.zeros((0, 3), dtype=int)
print(f"Array with explicit zero rows: {array_explicit_zero_rows}") # []
print(f"Shape: {array_explicit_zero_rows.shape}")                   # (0, 3)

Output:

Array with explicit zero rows: []
Shape: (0, 3)

warning

Accessing array_explicit_zero_rows[0] will cause the error!

Solution: Ensure Non-Zero Dimensions During Initialization

If you intend for the array to have rows, make sure to specify a non-zero number for the first dimension during creation.

import numpy as np

# ✅ Initialize with 2 rows and 3 columns
array_non_empty_rows = np.zeros((2, 3), dtype=int)
print(f"\nArray with non-zero rows:\n{array_non_empty_rows}")
print(f"Shape: {array_non_empty_rows.shape}")   # (2, 3)

# Now accessing the first row is valid
print(f"First row: {array_non_empty_rows[0]}")  # [0 0 0]

Output:

Array with non-zero rows:
[[0 0 0]
 [0 0 0]]
Shape: (2, 3)
First row: [0 0 0]

Related Scenario: Indexing a Non-Empty Array at an Out-of-Bounds Position

While the error message "index 0 is out of bounds for axis 0 with size 0" is specific to empty first dimensions, a more general IndexError like "index X is out of bounds for axis 0 with size Y" occurs if you try to access an index X that is greater than or equal to the size Y of that axis, even if Y is not zero.

import numpy as np

non_empty_array = np.array([10, 20]) # Size 2, valid indices are 0, 1
print(f"Non-empty array: {non_empty_array}, size: {non_empty_array.size}")

try:
    # ⛔️ Incorrect: Trying to access index 2, but valid indices are 0, 1
    val_error = non_empty_array[2]
    print(val_error)
except IndexError as e:
    print(f"Error indexing non-empty array: {e}")

Output:

Non-empty array: [10 20], size: 2
Error indexing non-empty array: index 2 is out of bounds for axis 0 with size 2

note

The solution is the same: ensure your index is within the valid range 0 to size-1.

Conclusion

The NumPy IndexError: index 0 is out of bounds for axis 0 with size 0 specifically means you are attempting to access the first element (index 0) of an array dimension that is empty (has a size of 0).

1. The most robust way to prevent this error is to check the array's size or specific axis length (shape[0]) before attempting to index it: if arr.size > 0: or if arr.shape[0] > 0:.
2. Alternatively, use a try-except IndexError: block to gracefully handle cases where an array might be empty.
3. Double-check your array initialization logic to ensure you are not unintentionally creating arrays with zero-sized dimensions (e.g., np.array([]), np.zeros((0, N))) if you intend to access elements from them later.

By ensuring that an array or its relevant axis is non-empty before indexing, you can avoid this common IndexError.