In this short guide, you’ll see how to get started with **NumPy**.

First, install NumPy using the command:

pip install numpy

## Import numpy as np

To use the NumpPy package, you’ll need to type “**import numpy as np**” at the top of your code.

You’ll then be able to use NumPy functions and objects by prefixing them with np., like **np.array()** to create a NumPy array.

Here’s an example that demonstrates how to “**import numpy as** **np**” and then use it to create a simple 1D NumPy array:

import numpy as np # Create a 1D NumPy array arr = np.array([1, 2, 3, 4, 5]) # Print the array print(arr)

The resulted 1D array:

`[1 2 3 4 5]`

Here is an example of 2D NumPy array:

import numpy as np # Create a 2D NumPy array arr = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) # Print the array print(arr)

The resulted 2D array:

```
[[1 2 3]
[4 5 6]
[7 8 9]]
```

### Calculate the sum of each column

To calculate the sum of each column (**axis=0**) using **np.sum()**:

import numpy as np # Create a 2D NumPy array arr = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) # Calculate the sum of each column col_sum = np.sum(arr, axis=0) print(col_sum)

The result:

`[12 15 18]`

Where the calculation of the sum of each column goes as follows:

**12**= 1 + 4 + 7**15**= 2 + 5 + 8**18**= 3 + 6 + 9

### Calculate the mean of each row

To calculate the mean of each row (**axis=1**) using **np.mean()**:

import numpy as np # Create a 2D NumPy array arr = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) # Calculate the mean of each row row_mean = np.mean(arr, axis=1) print(row_mean)

The result:

`[2. 5. 8.]`

Where the calculation of the mean of each row is:

**2**= (1 + 2 + 3) / 3**5**= (4 + 5 + 6) / 3**8**= (7 + 8 + 9) / 3