IndexError: index 0 is out of bounds for axis 0 with size 0

# IndexError: index 0 is out of bounds for axis 0 with size 0

The Python "IndexError: index 0 is out of bounds for axis 0 with size 0" occurs when we try to access the first item in the first dimension of an empty numpy array.

To solve the error, use a try/except block or check if the array's size is not equal to 0 before accessing it at an index.

Here is an example of how the error occurs.

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import numpy as np

arr = np.array([])

print(arr.shape)  # 👉️ (0,)
print(arr.size)  # 👉️ 0

# ⛔️ IndexError: index 0 is out of bounds for axis 0 with size 0
print(arr[0])

Here is another example of how the error occurs.

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import numpy as np

# 👇️ Array of 0 rows and 0 columns
arr = np.zeros((0, ), int)

print(arr)  # []

# ⛔️ IndexError: index 0 is out of bounds for axis 0 with size 0
print(arr[0])

We tried to access the first element in an empty array which caused the error.

# Using the shape or size properties on the array

You can use the shape property to print the shape of the array - a tuple of the array's dimensions.

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import numpy as np

arr = np.array([1, 2, 3])

print(arr.shape)  # 👉️ (3,)
print(arr.size)  # 👉️ 3

The size property can be used to print the array's size (the number of elements in the array).

Note that NumPy uses zero-based indexing - the first element in an array has an index of 0.

# Checking if the array's size is greater than 0

One way to solve the error is to check if the array's size is greater than 0 before accessing its first item.

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import numpy as np

arr = np.array([])

if arr.size > 0:
    print(arr[0])
else:
    print('The array has a size of 0')

The if block is only run if the size of the array is greater than 0, otherwise, the else block runs.

# Using a try/except statement to handle the error

Alternatively, you can use a try/except statement to handle the error.

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import numpy as np

arr = np.array([])

try:
    print(arr[0])
except IndexError:
    print('The array is empty')

We tried accessing the array element at index 0 which raised an IndexError exception.

You can handle the error or use the pass keyword in the except block.

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import numpy as np

arr = np.array([])

try:
    print(arr[0])
except IndexError:
    pass

The pass statement does nothing and is used when a statement is required syntactically but the program requires no action.

# Make sure the array has the correct dimensions

When declaring a NumPy array, make sure it has the correct dimensions.

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import numpy as np

arr_1 = np.array([1, 2, 3])

print(arr_1.shape)  # 👉️ (3,)
print(arr_1.size)  # 👉️ 3
print(arr_1[0])  # 👉️ 1

# -----------------------------------------

# 👇️ Array with 2 rows and 3 columns
# [[0 0 0]
#  [0 0 0]]
arr_2 = np.zeros((2, 3), dtype=int)
print(arr_2.shape)  # (2, 3)

print(arr_2[0])  # 👉️ [0 0 0]
print(arr_2[0][0])  # 👉️ 0
print(arr_2.size) # 👉️ 6

Axis 0 is the first dimension of an array and the size property can be used to get the number of elements in the array.

# Creating an array with 0 rows and N columns

Make sure you aren't creating an array with 0 rows and N columns.

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import numpy as np

arr = np.zeros((0, 3), dtype=int)
print(arr)  # 👉️ []
print(arr.shape)  # (0, 3)

# ⛔️ IndexError: index 0 is out of bounds for axis 0 with size 0
print(arr[0])

The array in the example has a size 0 for its first dimension, so trying to access any element at index would cause an IndexError.

Instead, specify a non-zero value for the rows.

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import numpy as np

# 👇️ array with 2 rows and 3 columns
arr = np.zeros((2, 3), dtype=int)

# [[0 0 0]
#  [0 0 0]]
print(arr)

print(arr.shape)  # 👉️ (2, 3)

print(arr[0])  # 👉️ [0 0 0]

The code sample creates an array with 2 rows and 3 columns.

# Accessing a non-empty array at an index that doesn't exist

The error also occurs if you access a non-empty array at an index that doesn't exist.

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import numpy as np


arr = np.array([0])

print(arr[0])  # 👉️ 0

print(arr.shape) # 👉️ (1, )
print(arr.size) # 1

# ⛔️ IndexError: index 1 is out of bounds for axis 0 with size 1
print(arr[1])

The array in the example has a single element.

NumPy indices are zero-based, so accessing the array at index 1 causes an error.

The first element in a NumPy array has an index of 0 and the last element has an index of -1 or len(array) - 1.

You can use a try/except statement to handle the error.

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import numpy as np

arr = np.array([0])

try:
    print(arr[1])
except IndexError:
    # 👇️ this runs
    print('The specified index does NOT exist')

If the index doesn't exist, an IndexError is raised and is then handled by the except block.

# Additional Resources

You can learn more about the related topics by checking out the following tutorials:

• IndexError: invalid index to scalar variable in Python
• IndexError: list assignment index out of range in Python
• Only integers, slices (:), ellipsis (...), numpy.newaxis (None) and integer or boolean arrays are valid indices
• IndexError: pop from empty list in Python [Solved]
• Replacement index 1 out of range for positional args tuple
• IndexError: too many indices for array in Python [Solved]
• IndexError: tuple index out of range in Python [Solved]
• IndexError: single positional indexer is out-of-bounds [Fix]