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# Accessing columns of a 2D NumPy array

schedule Aug 11, 2023
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To access particular columns of a 2D Numpy array, use the `[]` syntax.

Suppose we have the following 2D Numpy array:

``` x = np.array([[1,2,3], [4,5,6]])x array([[1, 2, 3], [4, 5, 6]]) ```

# Accessing the first column

``` x[:,0] array([1, 4]) ```

The code seems cryptic, so let's break it down. The syntax of `[]` is as follows:

``` [* the_rows_you_want *, * the_columns_you_want *] ```

In our code snippet, we used `:` to denote the rows that we want. You can interpret this in the way you interpret Python's slicing syntax for lists; `:` alone without any numbers means "give me all the rows". This means that `x[:,0]` gives us all the rows of the 0th column, which in essence, is just the 0th column.

# Accessing the first two columns

For your reference, we show the our 2D Numpy array `x` here again:

``` array([[1, 2, 3], [4, 5, 6]]) ```

To access the first two columns:

``` x[:,0:2] array([[1, 2], [4, 5]]) ```

Note that the endpoint `2` is exclusive. You could write `:2` instead of `0:2`.

# Accessing the last column

``` x[:,-1] array([3, 6]) ```

# Accessing the last two columns

``` x[:,-2:] array([[2, 3], [5, 6]]) ```
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