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# scipy stats.beta () | python

Parameters:
q: lower and upper tail probability
a, b: shape parameters
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: beta continuous random variable

Code # 1: Generate beta continuous random variable values ​​

 ` # scipy import ` ` from ` ` scipy.stats ` ` import ` ` beta `   ` numargs ` ` = ` ` beta.numargs ` ` [a, b] ` ` = ` ` [` ` 0.6 ` `,] ` ` * ` ` numargs ` ` rv ` ` = ` ` beta (a, b) ` ` `  ` print ` ` (` `" RV : "` `, rv) `

Output:

` RV: "scipy.stats._distn_infrastructure.rv_frozen object at 0x0000029482FCC438" `

Code # 2: beta random variations and probability distribution function.

` `

` import numpy as np quantile = np.arange ( 0.01 , 1 , 0.1 )   # Random Variants R = beta.rvs (a, b, scale = 2 , size = 10 ) p rint ( "Random Variates:" , R)   # PDF R = beta.pdf (quantile, a, b, loc = 0 , scale = 1 ) print ( "Probability Distribution:" , R) `

Output:

` Random Variates: [1.47189604 1.47284574 1.84692416 1.0686604 0.32709236 1.96857076 0.00639731 1.97093898 1.34811881 0.34269426] Probability Distribution: [2.62281037 1.04883674 0.84934164 0.76724957 0.73040985 0.72096547 0.73529768 0.779037 62 0.8752367 1.1264383] `

Code # 3: Graphic representation.

 ` import ` ` numpy as np ` ` import ` ` matplotlib.pyplot as plt `   ` distribution ` ` = ` ` np.linspace (` ` 0 ` `, np.maximum (rv.dist.b , ` ` 5 ` `)) ` ` plot ` ` = ` ` plt.plot (distribution, rv.pdf (distribution)) `

Output:

Code # 4: Various Positional Arguments

Output:

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 ` from ` ` scipy.stats ` ` import ` ` arcsine ` ` import ` ` matplotlib.pyplot as plt ` ` import ` ` numpy as np `   ` x ` ` = ` ` np.linspace (` ` 0 ` `, ` ` 1.0 ` `, ` ` 100 ` `) `   ` # Various positional arguments ` ` y1 ` ` = ` ` beta.pdf (x, ` ` 2.75 ` `, ` ` 2.75 ` `) ` ` y2 ` ` = ` ` beta.pdf (x, ` ` 3.25 ` `, ` ` 3.25 ` `) ` ` plt.plot (x, y1, ` ` "*" ` `, x, y2, ` ` "r--" ` `) `