Copy on Write via weakrefs
Aims to eventually close #10954 , alternative to #10973 

In the interest of advancing the discussion on this, here's a skeleton of a different copy on write implementation. 

**Currently**

When setting on a view, converts to copy. 

```
 df = pd.DataFrame({'col1':[1,2], 'col2':[3,4]})
 intermediate = df.loc[1:1,]
 intermediate['col1'] = -99


intermediate

Out[8]: 
   col1  col2
1   -99     4

df

Out[9]: 
   col1  col2
0     1     3
1     2     4
```

Chained-indexing will ALWAYS fail. 

```
df = pd.DataFrame({'col1':[1,2], 'col2':[3,4]})
df.loc[1:1,]['col1'] = -99
df

Out[11]: 
   col1  col2
1     2     4
```

`SettingWithCopy` warning disabled, thought not fully removed (figure this is too early stage to really chase that down). 

Forward Protection for `loc` setting (proof of concept, added oct 2):

```
 df = pd.DataFrame({'col1':[1,2], 'col2':[3,4]})
 intermediate = df.loc[1:1,]

 df.loc[1,'col1'] = -99
 intermediate

  Out[11]: 
   col1  col2
0     1     3
1     2     4
```

**Goals / Places I'd love help**
- We've discussed keeps full-column slices as views, since we can guarantee these will always be views. I created an attribute called `_is_column_view` that can be set to `True` when a slice is a full column (e.g. `new = df['col1']`, but I'm not sure how to actually figure out if a slice is a full column, so right now it's initialized as `False` and just stays that way. 
- This has no protection against forward propagation -- situations where one sets values on a Frame and they propagate to views of that Frame. There IS a framework to address it, but it's incomplete. As it stands:
  - Frames now have a `_children` list attribute to keep references to their child `views`.
  - Before setting, there's a call to a function to try and convert the children from `views` to `copies`. 
    But as it stand, I don't know how to really manage those references (i.e. how to put references to children in that `_children` list). 

@jreback 
@shoyer 
@JanSchulz 
@TomAugspurger 

u need to have tests

doesn't matter if it's a demo or not

these are the first things u should write to demonstrate the API 
 @jreback ok, added!
 Added an example of forward protection. NOT generalizable or at all robust, just illustrative for one setting. 
 This might work in a reasonably efficient way if you make `_children` a `WeakValueDictionary` (keyed by object id?). Certainly seems better than using garbage collection in totally ad-hoc ways...
 @shoyer would you mind explaining a little more? You mean just a floating global dictionary as opposed to an object attribute?

Main problem I'm having now (love suggestions @jreback @shoyer ): where to place `_convert_children()` call. Is there a single function that's _always_ called when data is changed where I can put it? Or a short list of functions where it should be put? 
 The problem with making `_children` a list is that you can't efficiently remove items from a list. Putting children in the values of dictionary solves that problem, and `WeakValueDictionary` even solves the cleanup for you automatically, because it removes items when they are garbage collected.
 oh, oh, I see. Great! 
 this list of `_children` would only be a very small number of items, so it won't make much difference
 I'm still a fan of using WeakValuesDictionary rather than rolling our own
solution. Either way weak refs are a more viable approach than hijacking
the garbage collector.

On Fri, Oct 2, 2015 at 2:52 PM, Jeff Reback notifications@github.com
wrote:

> this list of _children would only be a very small number of items, so it
> won't make much difference
> 
> —
> Reply to this email directly or view it on GitHub
> https://github.com/pydata/pandas/pull/11207#issuecomment-145164341.
 well if you get it to work, all ears.

if you do

```
a = df['foo']
```

you don't have a ref, so not really sure what you are trying to track
 That's the one case we wanted to stay as a view (full column slices) right?
So that might be a feature not a bug...
On Fri, Oct 2, 2015 at 3:06 PM Jeff Reback notifications@github.com wrote:

> well if you get it to work, all ears.
> 
> if you do
> 
> a = df['foo']
> 
> you don't have a ref, so not really sure what you are trying to track
> 
> —
> Reply to this email directly or view it on GitHub
> https://github.com/pydata/pandas/pull/11207#issuecomment-145167299.
 Also: I don't yet understand the internals well enough to know where all I
need to put self._children.append() and _convert_children() -- this is just
an attempt to figure out the machinery in one specific case of subsetting
and setting. Guidance on bottlenecks for where to put those calls to cover
all cases would be much appreciated.
On Fri, Oct 2, 2015 at 3:10 PM Nick Eubank nickeubank@gmail.com wrote:

> That's the one case we wanted to stay as a view (full column slices)
> right? So that might be a feature not a bug...
> On Fri, Oct 2, 2015 at 3:06 PM Jeff Reback notifications@github.com
> wrote:
> 
> > well if you get it to work, all ears.
> > 
> > if you do
> > 
> > a = df['foo']
> > 
> > you don't have a ref, so not really sure what you are trying to track
> > 
> > —
> > Reply to this email directly or view it on GitHub
> > https://github.com/pydata/pandas/pull/11207#issuecomment-145167299.
 @jreback @shoyer OK, I think this is getting close to working... Will keep working on this, but if anyone has any input or sees problems, input appreciated!

Still trying to figure out columns... (i.e. to keep df['col1'] as a view). 
 @shoyer @jreback OK, now keeps dictionary-like column slices (v = df['col1']) as views as our one special case. 
 Moving to new thread: 
