prob140.JointDistribution.conditional_dist

JointDistribution.conditional_dist(label, given='', show_ev=False)

Given the random variable label, finds the conditional distribution of the other variable.

Parameters:

label : String

Variable given.

Returns:

JointDistribution Table

Examples

>>> coins = Table().values('Coin1', ['H', 'T'], 'Coin2', ['H','T']).probability(np.array([0.24, 0.36, 0.16,0.24])).to_joint()
>>> coins.conditional_dist('Coin1', 'Coin2')
                          Coin1=H  Coin1=T  Sum
Dist. of Coin1 | Coin2=H      0.6      0.4  1.0
Dist. of Coin1 | Coin2=T      0.6      0.4  1.0
Marginal of Coin1             0.6      0.4  1.0
>>> coins.conditional_dist('Coin2', 'Coin1')
         Dist. of Coin2 | Coin1=H  Dist. of Coin2 | Coin1=T  Marginal of Coin2
Coin2=H                       0.4                       0.4                0.4
Coin2=T                       0.6                       0.6                0.6
Sum                           1.0                       1.0                1.0