Python numpy sum() function is used to get the sum of array elements over a given axis.

## Python numpy sum() function syntax

Python NumPy sum() method syntax is:

```
sum(array, axis, dtype, out, keepdims, initial)
```

- The
**array**elements are used to calculate the sum. - If the
**axis**is not provided, the sum of all the elements is returned. If the axis is a tuple of ints, the sum of all the elements in the given axes is returned. - We can specify
**dtype**to specify the returned output data type. - The
**out**variable is used to specify the array to place the result. It’s an optional parameter. - The
**keepdims**is a boolean parameter. If this is set to True, the axes which are reduced are left in the result as dimensions with size one. - The
**initial**parameter specifies the starting value for the sum.

## Python numpy sum() Examples

Let’s look at some of the examples of numpy sum() function.

### 1. Sum of All the Elements in the Array

If we pass only the array in the sum() function, it’s flattened and the sum of all the elements is returned.

```
import numpy as np
array1 = np.array(
[[1, 2],
[3, 4],
[5, 6]])
total = np.sum(array1)
print(f'Sum of all the elements is {total}')
```

**Output**: `Sum of all the elements is 21`

### 2. Sum of Array Elements Along the Axis

If we specify the axis value, the sum of elements along that axis is returned. If the array shape is (X, Y) then the sum along 0-axis will be of shape (1, Y). The sum along 1-axis will be of shape (1, X).

```
import numpy as np
array1 = np.array(
[[1, 2],
[3, 4],
[5, 6]])
total_0_axis = np.sum(array1, axis=0)
print(f'Sum of elements at 0-axis is {total_0_axis}')
total_1_axis = np.sum(array1, axis=1)
print(f'Sum of elements at 1-axis is {total_1_axis}')
```

Output:

```
Sum of elements at 0-axis is [ 9 12]
Sum of elements at 1-axis is [ 3 7 11]
```

### 3. Specifying Output Data Type of Sum

```
import numpy as np
array1 = np.array(
[[1, 2],
[3, 4]])
total_1_axis = np.sum(array1, axis=1, dtype=float)
print(f'Sum of elements at 1-axis is {total_1_axis}')
```

**Output**: `Sum of elements at 1-axis is [3. 7.]`

### 4. Initial Value for the Sum

```
import numpy as np
array1 = np.array(
[[1, 2],
[3, 4]])
total_1_axis = np.sum(array1, axis=1, initial=10)
print(f'Sum of elements at 1-axis is {total_1_axis}')
```

**Output**: `Sum of elements at 1-axis is [13 17]`

**Reference**: API Doc

Dear Pankaj,

I only want to sum some of the values not all. what should I do in that case?

Imagine that It is an array including 0 and 1s and I would like to sum 1s before each zero not to sum all the 1s.

I appreciate if you could help me.

Hi Pankaj

What mean when use “axis=-1” in sum function

Thanks..