Is there a way to group data by value in one column to produce a sum of contents in other column in pandas?

I'm sorry if this is a repeat, I can't find anything that gives me an answer...

I have a dataframe containing pixel values and the number of pixels of that value. It looks something like this:

Value    Count 
0.1457   900  
0.1458   1800
0.1459   900
0.2144   1800  
0.4357   2700
0.5764   900
0.7891   1800
0.7892   900
nan      0
nan      0

In this case each instance of nan indicates a single pixel with no data.

I'd like to group these values into 4 classes as follows...:

Low: <0.2
Mid: 0.2 - 0.6
High: >0.6
No Data: nan

...and then produce a sum for each class, like so using the above example data:

Class    Count
Lo       3600
Mid      6300
Hi       2700
ND       2

I appreciate there are likely to be several steps to this, but does anyone have any pointers?

Solution

import pandas as pd
import numpy as np

df = pd.DataFrame({"Value":[i*0.01 for i in range(1000)]+[np.nan,np.nan],"Count ":list(range(1000))+[np.nan,1]})
df['Class'] = ["Lo" if v < 0.2 else "Mid" if v > 0.2 and v < 0.6 else "ND" if np.isnan(v) else "Hi" for v in df.Value]

df.groupby(['Class']).sum()

Output:

Class	Value	Count
Hi	4977.5	497750
Lo	1.9	190
Mid	15.6	1560
ND	0	1