How do I subset rows 11 - 13?

I have a pandas dataframe with some hacked together data and I'm having the hardest time subsetting rows 11, 12, and 13. Essentially, I want to separate rows that start with "**dunntest**" and have **TRUE** in column 5 then put them into a new dataframe.

```
          Group         CL          CL1                 CL2        CL3  
0           Min      100.1        100.8               100.9      103.1   
1   1stquartile      100.5        101.1               101.4      103.3   
2        Median      101.6        101.4               101.6      103.4   
3          Mean      101.6        101.7               101.8      103.4   
4   3rdquartile      102.5        102.2               102.1      103.6   
5           Max      103.3        102.9               103.0      103.8   
6            CL        CL1          CL2                 CL3      CLDNA   
7     0.4165119  0.6244998    0.4415880           0.3500000  0.6489307   
8      dunntest       none     CL - CL1   0.469096846266772      FALSE   
9      dunntest       none     CL - CL2   0.378810361841698      FALSE   
10     dunntest       none    CL1 - CL2   0.429085199653927      FALSE   
11     dunntest       none     CL - CL3  0.0173616506762375       TRUE   
12     dunntest       none    CL1 - CL3  0.0382663620796246       TRUE   
13     dunntest       none    CL2 - CL3  0.0436908956580823       TRUE   
14     dunntest       none   CL - CLDNA   0.116215240987058      FALSE   

```

If I do `print(df.loc[:, "Group"])` 
I get the first column of the entire data frame. 

and when I do `print(df.loc[:, "Group" == "dunntest"])`

I get a KeyError: `KeyError: 'the label [False] is not in the [columns]'`

\*Edit Using the column names is not reliable because they will always be different.