Allow the other direction of df.drop
As mentioned here:
https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.drop.html

```
>>> df = pd.DataFrame(np.arange(12).reshape(3,4),
...                   columns=['A', 'B', 'C', 'D'])
>>> df
   A  B   C   D
0  0  1   2   3
1  4  5   6   7
2  8  9  10  11
```

panda allows to remove columns if specifying their names.

```
>>> df.drop(['B', 'C'], axis=1)
   A   D
0  0   3
1  4   7
2  8  11

```
Meaning the requested feature is:

```

>>> df.dropelse(['B', 'C'], axis=1)`
     B   C   
0   1   2   
1   5   6   
2   9  10 

```


I found out that for many approaches the opposite was is preferred - meaning specifying the columns that should stay and remove everything not on the list. This extremely helpful when you know the columns that you want but you have no idea what are the other column names. 
