# Sort a Numpy Array by a Specific Column

In this tutorial, we will look at how to sort a numpy array by a column with the help of some examples.

To sort a numpy array by a given column, use the following steps –

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1. Get the column index, i. For example, if you want to sort the array by values in the second column, i will be 1 (rows and columns and indexed starting from 0).
2. Get the index array of the rows after sorting by the above column using the `argsort()` method.
3. Use the above index array to reorder the rows.

The following is the syntax –

```# sort 2d numpy array by the column with index i
sorted_arr = arr[arr[:, i].argsort()]```

The above code sorts the array by the values in the column with the index `i` in ascending order. To sort in descending order, reverse the values resulting from the `argsort()` function.

Let’s now look at some examples of using the above syntax –

## Example 1 – Sort 2d array by a column in ascending order

```import numpy as np

# create a numpy array
arr = np.array([
[1, 7, 1],
[2, 5, 0],
[3, 9, 0]
])

# sort the above array by the second column, i=1
sorted_arr = sorted_arr = arr[arr[:, 1].argsort()]
print(sorted_arr)```

Output:

```[[2 5 0]
[1 7 1]
[3 9 0]]```

You can see that the resulting array is sorted by the second column in ascending order.

## Example 2 – Sort 2d array by a column in descending order

We can similarly sort a 2d array (by a specific column) in descending order. To do this, reverse the row indices obtained from the `argsort()` method. This will give the array of row indices when sorted in descending order.

Let’s take the same example as above.

```import numpy as np

# create a numpy array
arr = np.array([
[1, 7, 1],
[2, 5, 0],
[3, 9, 0]
])

# sort the above array in descending order by the second column, i=1
sorted_arr = sorted_arr = arr[arr[:, 1].argsort()[::-1]]
print(sorted_arr)```

Output:

```[[3 9 0]
[1 7 1]
[2 5 0]]```

The resulting array is sorted in descending order by the second column.

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