# Python – ksone Distribution in Statistics

scipy.stats.ksone() is a General Kolmogorov-Smirnov one-sided test that is defined with a standard format and some shape parameters to complete its specification. It is a statistical test for the finite sample size n.

Parameters :

q : lower and upper tail probability
x : quantiles
loc : [optional]location parameter. Default = 0
scale : [optional]scale parameter. Default = 1
size : [tuple of ints, optional] shape or random variates.
moments : [optional] composed of letters [‘mvsk’]; ‘m’ = mean, ‘v’ = variance, ‘s’ = Fisher’s skew and ‘k’ = Fisher’s kurtosis. (default = ‘mv’).

Results : ksone continuous random variable

Code #1 : Creating ksone continuous random variable

 `# importing library ` ` `  `from` `scipy.stats ``import` `ksone   ` `   `  `numargs ``=` `ksone.numargs  ` `a, b ``=` `4.32``, ``3.18` `rv ``=` `ksone(a, b)  ` `   `  `print` `(``"RV : \n"``, rv)   `

Output :

```RV :
scipy.stats._distn_infrastructure.rv_frozen object at 0x000002A9D530AB48
```

Code #2 : Ksone continuous variates and probability distribution

 `import` `numpy as np  ` `quantile ``=` `np.arange (``0.01``, ``1``, ``0.1``)  ` ` `  `# Random Variates  ` `R ``=` `ksone.rvs(a, b, scale ``=` `2``, size ``=` `10``)  ` `print` `(``"Random Variates : \n"``, R)  `

Output :

```Random Variates :
[3.88510141 3.48394857 3.66124797 3.88484201 3.86533511 3.21176073
4.10238585 3.42397866 3.85111721 4.36433596]
```

Code #3 : Graphical Representation.

 `import` `numpy as np  ` `import` `matplotlib.pyplot as plt  ` `    `  `distribution ``=` `np.linspace(``0``, np.minimum(rv.dist.b, ``3``))  ` `print``(``"Distribution : \n"``, distribution)  ` `    `  `plot ``=` `plt.plot(distribution, rv.pdf(distribution))  `

Output :

```Distribution :
[0.         0.02040816 0.04081633 0.06122449 0.08163265 0.10204082
0.12244898 0.14285714 0.16326531 0.18367347 0.20408163 0.2244898
0.24489796 0.26530612 0.28571429 0.30612245 0.32653061 0.34693878
0.36734694 0.3877551  0.40816327 0.42857143 0.44897959 0.46938776
0.48979592 0.51020408 0.53061224 0.55102041 0.57142857 0.59183673
0.6122449  0.63265306 0.65306122 0.67346939 0.69387755 0.71428571
0.73469388 0.75510204 0.7755102  0.79591837 0.81632653 0.83673469
0.85714286 0.87755102 0.89795918 0.91836735 0.93877551 0.95918367
0.97959184 1.        ]
```

Code #4 : Varying Positional Arguments

 `import` `matplotlib.pyplot as plt  ` `import` `numpy as np  ` `    `  `x ``=` `np.linspace(``0``, ``5``, ``100``)  ` `    `  `# Varying positional arguments  ` `y1 ``=` `ksone.pdf(x, ``1``, ``3``)  ` `y2 ``=` `ksone.pdf(x, ``1``, ``4``)  ` `plt.plot(x, y1, ``"*"``, x, y2, ``"r--"``)  `

Output :

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