I have a pandas dataframe like this:

```
column1 | column2  | column3
1       | 4        |   10.4  
4       | 7        |   11.1
3       | 3        |   3.3

```

How could I calculate the sum of the squared values for the entire column (I am trying something like `deviation = df[columnName].pow(2).sum()` in a loop, but ideas are very welcome!) but also afterwards identifying the column that has the smallest of those sums and the actual smallest sum?

Edit: Adding desired output

Desired output in this case would be:

```
Minimum sum of squared values: 26
Column containing minimum sum of squared values: column1

```