So I’ve got columns of data in a numpy dataframe, and something like this does *not* work

```
VA = pm.Deterministic('VA', data.A * (1.0 / (1.0+pm.math.exp(logk)*data.DA)**s))
```

if I convert that into np arrays, then it works

```
VA = pm.Deterministic('VA', np.array(data.A) * (1.0 / (1.0+pm.math.exp(logk)*np.array(data.DA))**s))
```

and if I convert the data frame to a dict of np.array beforehand, then this will work

```
VA = pm.Deterministic('VA', data['A'] * (1.0 / (1.0+pm.math.exp(logk)*data['DA'])**s))
```

Providing data as data frames (top example) seems the most natural thing to do, but just wondering why it doesn’t work.

Note: this only seems to be a problem for deterministic nodes… having data from data frames in stochastic nodes has not been a problem.