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### array is 1-dimensional but 2 were indexed

This error message suggests that you are trying to access a 2-dimensional array using only one index.

In most programming languages, arrays are indexed using one or more numbers, with each number representing a specific dimension of the array. For example, a 2-dimensional array in Python might be accessed using the syntax `my_array[row_index][column_index]`

, where `row_index`

and `column_index`

are both integers.

If you only provide one index when trying to access a 2-dimensional array, the programming language will not know which dimension you are trying to access. This will result in an error message similar to the one you described.

To fix this error, make sure you provide two indices when accessing a 2-dimensional array, one for each dimension.

### Watch videos related to “array is 1-dimensional but 2 were indexed”

Numpy Array || 1D,2D,3D|| Indexing Slicing

### What is 1 dimensional array and 2 dimensional array?

A one-dimensional array is a collection of elements that are stored in a linear fashion, in which each element is assigned a unique index based on its position in the array. The index of the first element in the array is usually zero, and the index of the last element is (length-1), where “length” represents the number of elements in the array. One-dimensional arrays are commonly used to store lists of values that are of the same data type, such as integers, floats, or strings.

A two-dimensional array is a collection of elements that are stored in a tabular form, in which each element is identified by a pair of indices (row index and column index) that correspond to its position in the table. Two-dimensional arrays are used to store data that is organized into rows and columns, such as matrices, tables, or spreadsheets. The elements in a two-dimensional array can be of any data type, including other arrays, structures, or objects.

### How to convert 1D array to 2D array in Python?

To convert a 1D array to a 2D array in Python, you can use the `reshape()`

method available in the NumPy library. Here’s an example:

python`import numpy as np # create a 1D array with 12 elements arr1d = np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]) # reshape the 1D array to a 2D array with 3 rows and 4 columns arr2d = arr1d.reshape((3, 4)) print(arr2d)`

Output:

lua`[[ 0 1 2 3] [ 4 5 6 7] [ 8 9 10 11]]`

In this example, we imported the NumPy library and created a 1D array with 12 elements. Then, we used the `reshape()`

method to convert it into a 2D array with 3 rows and 4 columns. The resulting 2D array is printed using the `print()`

function.

Note that the size of the original 1D array should match the size of the 2D array (i.e., the product of the number of rows and columns). Otherwise, you will get a `ValueError`

exception.

### How is a 2D array indexed in Python?

A 2D array in Python is typically represented as a list of lists. Each element in the outer list is a list representing a row in the 2D array, and each element in the inner lists represents a column in that row. To index a 2D array in Python, you would use two indices – one for the row and one for the column.

For example, suppose you have a 2D array representing a 3×3 matrix:

lua`matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]`

To access the element in the first row and second column (i.e., the element with value 2), you would use the following indexing:

css`matrix[0][1]`

Here, the first index (0) refers to the first row in the matrix, and the second index (1) refers to the second column in that row.

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### too many indices for array: array is 1-dimensional, but 2 were indexed

This error message usually occurs when you are trying to access an element of an array using too many indices.

For example, if you have a one-dimensional array called `arr`

with 10 elements, you can access any element of the array using only one index, like this:

makefile`arr = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] element = arr[5] # Accessing the 6th element of the array`

However, if you try to access an element using two indices, like this:

css`element = arr[1][2]`

You will get the “too many indices for array” error because `arr`

is only a one-dimensional array and you are trying to access it as if it were a two-dimensional array.

To fix this error, you should check your code and make sure that you are accessing your array with the correct number of indices.

### scikitplot indexerror: too many indices for array array is 1 dimensional but 2 were indexed

The “IndexError: too many indices for array” error occurs when you are trying to access an element of an array using too many indices. Specifically, the error message suggests that you are using two indices to access an element of an array that is only one-dimensional.

This error can occur when using the scikitplot library, which provides tools for visualizing machine learning models. One possible reason for this error is that you are passing an incorrect input to the plotting function.

To resolve this issue, you can check the input you are passing to the function and make sure it is in the correct format. Additionally, you can check the documentation of the scikitplot function you are using to ensure that you are providing the correct inputs.

Here’s an example of how to use the `scikitplot.metrics.plot_confusion_matrix()`

function to plot a confusion matrix:

python`import scikitplot as skplt from sklearn.metrics import confusion_matrix y_true = [0, 1, 0, 1, 0, 1, 0, 1] y_pred = [1, 0, 0, 1, 0, 0, 1, 1] cm = confusion_matrix(y_true, y_pred) skplt.metrics.plot_confusion_matrix(y_true, y_pred)`

Make sure that `y_true`

and `y_pred`

are both 1-dimensional arrays or lists of the same length. In this example, `cm`

is a 2-dimensional confusion matrix, but it is not passed to the plotting function directly.

You can see some more information related to array is 1-dimensional but 2 were indexed here

- python gives array is 1-dimensional, but 2 were indexed error
- IndexError: too many indices for array – Python – STechies
- IndexError: too many indices for array in Python [Solved]
- Difference Between One-Dimensional and Two-Dimensional Array – Byju’s
- Convert a 1D array to a 2D array in numpy – Stack Overflow
- 2D Array in Python – Scaler Topics – Scaler
- How to check if an array is 2D – Stack Overflow
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- Indexing on ndarrays — NumPy v1.25.dev0 Manual

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