One error you may encounter when using Python is:

TypeError: only integer scalar arrays can be converted to a scalar index

This error usually occurs for one of two reasons:

**1.** You attempted to perform array indexing on a list.

**2.** You attempted to concatenate two matrices using incorrect syntax.

The following examples shows how to avoid these errors in both scenarios.

**Example 1: You attempted to perform array indexing on a list.**

Suppose we attempt to use the following code to create a line chart in matplotlib with a legend and labels:

**import numpy as np
#create a list of values
data = [3, 5, 5, 7, 8, 10, 12, 14]
#choose 3 random values from list
random_values = np.random.choice(range(len(data)), size=2)
#attempt to use indexing to access elements in list
random_vals = data[random_values.astype(int)]
#view results
random_vals
TypeError: only integer scalar arrays can be converted to a scalar index
**

We receive an error because we attempted to use array indexing on a list.

To avoid this error, we must first convert the list to a NumPy array by using **np.array()** as follows:

**import numpy as np
#create a list of values
data = [3, 5, 5, 7, 8, 10, 12, 14]
#choose 3 random values from list
random_values = np.random.choice(range(len(data)), size=2)
#attempt to use indexing to access elements in list
random_vals = np.array(data)[random_values.astype(int)]
#view results
random_vals
array([5, 7])
**

This time we’re able to randomly select two values from the list without any errors since we first converted the list to a NumPy array.

**Example 2: You attempted to concatenate two matrices using incorrect syntax.**

Suppose we attempt to use the following code to concatenate two NumPy matrices together:

**import numpy as np
#create twoNumPy matrices
mat1 = np.matrix([[3, 5], [5, 7]])
mat2 = np.matrix([[2, 4], [1, 8]])
#attempt to concatenate both matrices
np.concatenate(mat1, mat2)
TypeError: only integer scalar arrays can be converted to a scalar index
**

We receive an error because we failed to supply the matrices in the form of a tuple to the **concatenate()** function.

To avoid this error, we must use double parenthesis to supply the matrices in the form of a tuple to the **concatenate()** function as follows:

**import numpy as np
#create twoNumPy matrices
mat1 = np.matrix([[3, 5], [5, 7]])
mat2 = np.matrix([[2, 4], [1, 8]])
#attempt to concatenate both matrices
np.concatenate((mat1, mat2))
matrix([[3, 5],
[5, 7],
[2, 4],
[1, 8]])
**

This time we’re able to concatenate the two matrices without any error.

**Additional Resources**

The following tutorials explain how to fix other common errors in Python:

How to Fix KeyError in Pandas

How to Fix: ValueError: cannot convert float NaN to integer

How to Fix: ValueError: operands could not be broadcast together with shapes