# NumPy array creation: linspace() function

## numpy.linspace() function

The linspace() function returns evenly spaced numbers over a specified interval [start, stop].
The endpoint of the interval can optionally be excluded.

Syntax:

`numpy.linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None)`

Version: 1.15.0

Parameter:

Name Description Required /
Optional
start The starting value of the sequence. Required
stop The end value of the sequence, unless endpoint is set to False. In that case, the sequence consists of all but the last of num + 1 evenly spaced samples, so that stop is excluded. Note that the step size changes when endpoint is False. Required
num Number of samples to generate. Default is 50. Must be non-negative. Optional
endpoint If True, stop is the last sample. Otherwise, it is not included. Default is True. Optional
retstep If True, return (samples, step), where step is the spacing between samples. Optional
dtype The type of the output array. If dtype is not given, infer the data type from the other input arguments.
New in version 1.9.0.
Optional

Return value:

ndarray - There are num equally spaced samples in the closed interval [start, stop] or the half-open interval [start, stop) (depending on whether endpoint is True or False).

step : float, optional - Only returned if retstep is True
Size of spacing between samples.

Example-1: NumPy.linspace() method

``````>>> import numpy as np
>>> np.linspace(3.0, 4.0, num=7)
array([ 3.        ,  3.16666667,  3.33333333,  3.5       ,  3.66666667,
3.83333333,  4.        ])
>>> np.linspace(3.0,4.0, num=7, endpoint=False)
array([ 3.        ,  3.14285714,  3.28571429,  3.42857143,  3.57142857,
3.71428571,  3.85714286])
>>> np.linspace(3.0,4.0, num=7, retstep=True)
(array([ 3.        ,  3.16666667,  3.33333333,  3.5       ,  3.66666667,
3.83333333,  4.        ]), 0.16666666666666666)
``````

Pictorial Presentation:

Example-2: NumPy.linspace() method

``````>>> import numpy as np
>>> import matplotlib.pyplot as plt
>>> A = 5
>>> x = np.zeros(A)
>>> a1 = np.linspace(0, 10, A, endpoint=True)
>>> a2 = np.linspace(0, 10, A, endpoint=False)
>>> plt.plot(a1, x, 'o')
[<matplotlib.lines.Line2D object at 0x7f3d13a48080>]
>>> plt.plot(a2, x + 0.5, 'o')
[<matplotlib.lines.Line2D object at 0x7f3d1b582438>]
>>> plt.ylim([-5.0, 1])
(-5.0, 1)
>>> plt.show()
``````

numpy.linspace.plot show

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