# How to access a NumPy array by column

Last Updated : 23 Apr, 2023

Accessing a NumPy-based array by a specific Column index can be achieved by indexing. NumPy follows standard 0-based indexing in Python.

### Example:

```Given array: 1 13 6
9  4 7
19 16 2

Input: print(NumPy_array_name[ :,2])
Output: [6 7 2]
Explanation: printing 3rd column```

## Access ith column of a 2D Numpy Array in Python

Printing 1st row and 2nd column.

```For column : numpy_Array_name[  : ,column]
For row : numpy_Array_name[ row, :  ]```

## Python3

 `import` `numpy as np`   `array ``=` `[[``1``, ``13``, ``6``], [``9``, ``4``, ``7``], [``19``, ``16``, ``2``]]`   `# defining array` `arr ``=` `np.array(array)`   `print``(``'printing 0th row'``)` `print``(arr[``0``, :])`   `print``(``'printing 2nd column'``)` `print``(arr[:, ``2``])`   `# multiple columns or rows can be selected as well` `print``(``'selecting 0th and 1st row simultaneously'``)` `print``(arr[:,[``0``,``1``]])`

Output :

```printing 0th row
[ 1 13  6]

printing 2nd column
[6 7 2]

selecting 0th and 1st row simultaneously
[[ 1 13]
[ 9  4]
[19 16]]```

## Access the ith column of a Numpy array using transpose

Transpose of the given array using the .T property and pass the index as a slicing index to print the array.

## Python3

 `import` `numpy as np`   `arr ``=` `np.array([[``1``, ``13``, ``6``], [``9``, ``4``, ``7``], [``19``, ``16``, ``2``]])`   `# Access the ith column of a 2D NumPy array` `column_i ``=` `arr.T[``2``]`   `#printing the column` `print``(column_i)`

Output:

`[6 7 2]`

## Access the ith column of a Numpy array using list comprehension

Here, we access the ith element of the row and append it to a list using the list comprehension and printed the col.

## Python3

 `import` `numpy as np`   `arr ``=` `np.array([[``1``, ``13``, ``6``], [``9``, ``4``, ``7``], [``19``, ``16``, ``2``]])`   `# Access the ith column of a 2D NumPy array` `col ``=` `[row[``1``] ``for` `row ``in` `arr]`   `# printing the column` `print``(col)`

Output:

`[13, 4, 16]`

## Access the ith column of a Numpy array using Ellipsis

Pass the ith index along with the ellipsis to print the returned array column.

```For column : numpy_Array_name[...,column]
For row : numpy_Array_name[row,...]
where '...' represents no of elements in the given row or column ```

Note: This is not a very practical method but one must know as much as one can.

## Python3

 `import` `numpy as np`   `# defining array` `array ``=` `[[``1``, ``13``, ``6``], [``9``, ``4``, ``7``], [``19``, ``16``, ``2``]]`   `# converting to numpy array` `arr ``=` `np.array(array)`   `print``(``'selecting 0th column'``)` `print``(arr[..., ``0``])`   `print``(``'selecting 1st row'``)` `print``(arr[``1``, ...])`

Output:

```selecting 0th column
[ 1  9 19]

selecting 1st row
[9 4 7]```

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