How to Fix ValueError: all the input arrays must have same number of dimensions

Numpy arrays can be created with different dimensions, such as 2×3, 2×1, and more. When you are concatenating two numpy arrays with different dimensions, you will encounter ValueError: all the input arrays must have same number of dimensions. In this guide, we will discuss this error and provide three different solutions to resolve it. In Python, a ValueError occurs when an incorrect value is provided to the object.

Reproducing the Error

Create two numpy arrays: day1_budget with two dimensions (2×2) and day2-budget with one dimension. Try to concatenate both of them using the concatenate() function.

Output

You can see that an error is encountered.

Create two numpy arrays: day1_budget with 2×3 dimensions and day2-budget with 2×2 dimensions. Try to concatenate both of them using the concatenate() function.

Output

You can see that an error is encountered, which is similar to the above error that we are discussing in this guide.

Solution 1: Check the Dimensions Manually

This is the manual scenario where the developer has to create numpy arrays and check if their dimensions are equal. If both dimensions are the same, concatenate the arrays.

Let’s create two numpy arrays, day1_budget and day2_budget, both with 2×2 dimensions. Use the concatenate() function to concatenate day1_budget and day2_budget.

Output

You can see that both arrays have been concatenated.

Solution 2: Using numpy.column_stack()

If you want to join arrays with different dimensions, you can use numpy.column_stack() function which will stack the one-dimensional arrays as columns into a two-dimensional array.

Syntax

It takes a tuple of arrays as the parameter.

Example 1

Let’s create two numpy arrays: day1_budget with 2×3 dimensions and day2_budget with 2×2 dimensions. Use the numpy.column_stack() function to concatenate both of them.

Output

You can see that the second array has been concatenated to the first array as two new columns.

Example 2

Let’s create three numpy arrays: day1_budget with 2×3 dimensions, day2_budget with 2×2 dimensions, and day3_budget with 2×1 dimension. Use the numpy.column_stack() function to concatenate all of them.

Output

You can see that all the arrays have been concatenated.

Solution 3: Using numpy.c_()

Use numpy.c_() to concatenate the numpy array along the second axis.

Syntax

It does not take any parameters, as it is not a function. It returns the concatenated array.

Example

Let’s create two numpy arrays: day1_budget with 2×3 dimensions and day2_budget with 2×2 dimensions. Use numpy.c_() to concatenate both of them.

Output

You can see that the second array has been concatenated to the first array, adding two new columns.

Conclusion

Now you are able to fix the issue while concatenating the numpy arrays with different dimensions. If the arrays have different dimensions, use either the numpy.column_stack() function or numpy.c_() to concatenate them along the columns. Otherwise, make the dimensions equal for both the arrays and concatenate them.