On the call yesterday, the topic of mutability came up in the vaex demo.

The short version is that it may be difficult or impossible for some systems to implement inplace mutation of dataframes. For example, I believe that neither vaex nor Dask implement the following:

In [8]: df = pd.DataFrame({"A": [1, 2]})

In [9]: df
Out[9]:
   A
0  1
1  2

In [10]: df.loc[0, 'A'] = 0

In [11]: df
Out[11]:
   A
0  0
1  2

I think in the name of simplicity, the API standard should just not define any methods that mutate existing data inplace.

There is one mutation-adjacent area that might be considered: using DataFrame.__setitem__ to add an additional column

In [12]: df['B'] = [1, 2]

In [13]: df
Out[13]:
   A  B
0  0  1
1  2  2

Or perhaps to update the contents of an entire column

In [14]: df['B'] = [3, 4]

In [15]: df
Out[15]:
   A  B
0  0  3
1  2  4

In these case, no values are actually being mutated inplace. Is that acceptable?