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# Sympy stats.JointRV() in Python

• Last Updated : 08 Jun, 2020

With the help of `sympy.stats.JointRV()` method, we can get the continuous joint random variable which represents the Von Mises distribution.

Syntax : `sympy.stats.JointRV(name, pdf)`
Return : Return the continuous joint random variable.

Example #1 :
In this example we can see that by using `sympy.stats.JointRV()` method, we are able to get the continuous joint random variable representing JointRV distribution by using this method.

 `# Import sympy and JointRV``from` `sympy.stats ``import` `JointRV, density``from` `sympy ``import` `Symbol, pprint`` ` `z ``=` `Symbol(``"z"``)``pdf ``=` `2` `*` `pi ``*` `z`` ` `# Using sympy.stats.JointRV() method``X ``=` `JointRV(``"x"``, pdf)``gfg ``=` `density(X)`` ` `pprint(gfg)`

Output :

 `# Import sympy and JointRV``from` `sympy.stats ``import` `JointRV, density``from` `sympy ``import` `Symbol, pprint`` ` `z ``=` `3``pdf ``=` `2` `*` `pi ``*` `z`` ` `# Using sympy.stats.JointRV() method``X ``=` `JointRV(``"x"``, pdf)``gfg ``=` `density(X)`` ` `pprint(gfg)`