I am very new to pymc3 and trying to get my feet wet with it. If I have a basic dataset, like:

```
import pandas as pd
import pymc3 as pm
df = pd.DataFrame({
'labels': list('aabbcc'),
'values': [0,1,1,1,0,0]
})
with pm.Model() as model:
mu_a = pm.Beta('mu_a', 1, 3)
mu_b = pm.Beta('mu_b', 1, 3)
mu_c = pm.Beta('mu_c', 1, 3)
likelihood_a = pm.Binomial('likelihood_a', p=mu_a, observed=df[df['labels'] == 'a'][‘values’])
likelihood_b = pm.Binomial('likelihood_b', p=mu_b, observed=df[df['labels'] == 'b'][‘values’])
likelihood_c = pm.Binomial('likelihood_c', p=mu_c, observed=df[df['labels'] == 'c'][‘values’])
diff_a_b = pm.Deterministic('diff_a_b', mu_a - mu_b)
diff_a_c = pm.Deterministic('diff_a_c', mu_a - mu_c )
diff_b_c = pm.Deterministic('diff_a_c', mu_b - mu_c)
```

I feel like I am doing something very wrong, and there has to be an easier way to define the probabilities and calculate the differences.