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Onyejiaku Theophilus Chidalu

Grokking Modern System Design Interview for Engineers & Managers

Ace your System Design Interview and take your career to the next level. Learn to handle the design of applications like Netflix, Quora, Facebook, Uber, and many more in a 45-min interview. Learn the RESHADED framework for architecting web-scale applications by determining requirements, constraints, and assumptions before diving into a step-by-step design process.

The ** numpy.cumsum()** function in NumPy is used to compute the cumulative sum of elements in a given input array over a given axis.

```
numpy.cumsum(a, axis=None, dtype=None, out=None)
```

The `numpy.cumsum()`

function takes the following parameter values:

`a`

(required): The input array containing numbers is to be computed.`axis`

(optional): The axis along which the product is determined.`dtype`

(optional): The data type of the output array.`out`

(optional): The alternate array where the result is placed.

The `numpy.cumsum()`

function returns an output array holding the result.

import numpy as np# creating an arrayx = np.array([1, 2, 3])# Implementing the numpy.cumsum() functionmyarray = np.cumsum(x, axis=0)print(x)print(myarray)

Implementing the numpy.cumsum() function

Here is a line-by-line explanation of the above code:

- Line 1: We import the
`numpy`

module. - Line 4: We create an array,
`x`

, using the`array()`

method. - Line 7: We implement the
`np.cumsum()`

function on the array. The result is assigned to a variable,`myarray`

. - Line 9: We print the input array
`x`

. - Line 10: We print the variable
`myarray`

.

RELATED TAGS

function

numpy

python

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Onyejiaku Theophilus Chidalu

Grokking Modern System Design Interview for Engineers & Managers

Ace your System Design Interview and take your career to the next level. Learn to handle the design of applications like Netflix, Quora, Facebook, Uber, and many more in a 45-min interview. Learn the RESHADED framework for architecting web-scale applications by determining requirements, constraints, and assumptions before diving into a step-by-step design process.

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