On 2020-02-23 15:58, Aaron Hall via Python-ideas wrote:
(Apologies for the html email, it was poorly formatted, making my example very
difficult to follow. So let me try to give better examples.)
With sympy we would be able to create meaningful behavior for:
```
from sympy import symbols
y, x1, x2 = symbols('y x1 x2')
model = y ~ x1 + x2
model.is_linear() # -> True/False? (just an example!)
```
or
```
from sympy import symbols
theta, N, mu, sigma = symbols('theta N mu sigma')
distribution = theta ~ N(mu, sigma)
distribution.sample() # -> a symbolic sampling from the normal distribution
```
and for dataframes, arrays, or matrices, we could do something like:
```
model = df.y ~ df.x1 + df.x2
model.fit()
test_predictions = model.predict(df_test)
```
The thing is that you can already do that. You just can't do it with
the specific character ~ for your operation. But that's not really a
big deal is it? You could define this proposed behavior right now,
using some other operator like `<<` and then make it so you can do
model = (df.y << df.x1) + df.x2
and so on. Also, since there's typically only one dependent variable,
you could just define types that have a method `.depends_on` or
`.modeled_by` or whatever, and an accessor attribute .term or something
that so that you do
model = df.y.modeled_by(df.x1.term + df.x2)
I don't think think this is really much worse than R. In fact, I'd
rather see something like "modeled_by" rather than the tilde. The
problem, again, is not really the lack of the tilde, but the need to
repeatedly specify `df`. I'm curious why you see the tilde as the crux
of this issue, because it seems to me that the behavior you envision
could already be implemented with another operator; it wouldn't look
exactly like it does in R, but it could function pretty similarly.
--
Brendan Barnwell
"Do not follow where the path may lead. Go, instead, where there is no
path, and leave a trail."
--author unknown
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