Hourly frequency count with Python

I have this Hourly csv datas sorted like this day by day for hundreds days:

2011.05.16,00:00,1.40893
2011.05.16,01:00,1.40760
2011.05.16,02:00,1.40750
2011.05.16,03:00,1.40649

I want to make a count of how many times per hour the daily maximum value has been set, so if on 00:00 i had the maximum value of 2011.05.16 day i add 1 to 00:00 and so on. To do this i used a loop to count hours like indexes in this way:

def graph():    
Date, Time,  High = np.genfromtxt(myPath, delimiter=",",
                                  unpack = True,  converters={0:date_converter})                                                                           
numList = [""] * 24
index=0
hour=0    
count = [0] * 24

for eachHour in Time:        
    numList[hour] += str(High[index])        
    index += 1
    hour +=1        

    if hour == 24:           
        higher = (numList.index(max(numList)))
        count[higher] += 1            
        hour = 0            
        numList = [""] * 24

The problem is that in my datas often there's a gap with some hours missing, but the loop can't recognize it and continue putting values in the next hour index. I've searched everywhere, but i'm new to programming and this is my first "complex" work so i need more specific answers to my case for understand how it works. So how do you make an hourly frequency count like explained? The final result should be like:

00:00 n time max of the day   
01:00 n time max of the day   
02:00 n time max of the day  
etc