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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]])
```

Published by Isshin Inada

Edited by 0 others

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