Sorting an array by the nth column using NumPy is a common task in data analysis and scientific computing. It involves *rearranging the rows of the array based on the values in a specific column. The nth column refers to the column at index n-1, where n is the position of the column in the array.*

NumPy provides a lot of different convenient functionalities, which are listed below:

#### 1. Using “np.lexsort()”:

The code creates a 2D NumPy array called “arr”. It then sorts the array based on the second column (index 1) using `np.lexsort()`

. The resulting sorted array is stored in “sorted_arr”, and it is printed to the console. The column to sort by is defined using the variable “n”.

- You can also use
`np.lexsort()`

and**sort the array by multiple columns**. The example below creates a 2D NumPy array called “arr”. It then sorts the array based on the second column (index 1), and then by the first column (index 0) using`np.lexsort()`

. The resulting sorted array is stored in “sorted_arr”, and it is printed to the console.

**Example**:

#### 2. Using “np.argsort()” with descending order:

The code creates a 2D NumPy array called “arr”. It then sorts the array based on the second column (index 1) in descending order using `np.argsort(-arr[:,1])`

. The resulting sorted array is stored in “sorted_arr”, and it is printed to the console. Note that `np.argsort()`

sorts the array in ascending order by default. If you want to sort in descending order, you can use negative indexing.