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Maria Elijah

**NumPy** is a Python library that allows us to work with numeric data. Numeric data can be created and stored in a data structure called a **NumPy array**.
NumPy has various functions to perform calculations on the arrays of numeric data. One of these is the `std()`

function.

The ** numpy. std() function** finds the standard deviation of a given NumPy array along the specified axis.

```
numpy.std(
arr,
axis=None,
out=None,
overwrite_input=False,
dtype=data-type
)
```

: This represents the input array.`arr`

: This represents the axis on which we want to calculate the standard deviation. If the axis is`axis`

`0`

, the direction is down the row. If it is`1`

, the direction is down the column.: This is an optional parameter that saves the NumPy result.`out`

: This is an optional parameter that specifies the type to use when computing the standard deviation.`dtype`

The following code shows how to use the `NumPy.std()`

function in Python:

# import numpy import numpy as np # create a list my_list = [24,8,3,4,86,42,56,34,8] # convert the list to numpy array np_list = np.array(my_list) # compute the std and store it np_list_std = np.std(np_list) print(f"The standard deviation is {np_list_std}")

- Line 2: We import the
`numpy`

library. - Line 4: We create a list called
`my_list`

. - Line 6: We convert the list to the NumPy array and store it in a variable
`np_list`

. - Line 8: We use the
`np.std()`

function to compute the standard deviation for the`np_list`

. - Line 10: We display the result.

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python3

python programming

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