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I have an array with 8760 values. I want to calculate the average for every 24 values and return the 365 average values as an array. Is this correct or is there a more simple way of doing this?

temps = data['temperature'] #Fetching temperaturedata from dictionary temps_array = np.asarray(temps) #Converting temps list to array averages = daily_mean_temp(temps_array) #Running function that calculates mean def daily_mean_temp(hourly_temp): average_temps = [x.mean() for x in np.array_split( [float(x) for x in hourly_temp], 365)] #This is a list average_temps_array = np.asarray(average_temps) #Converting from list to array return average_temps_array #return array with mean values
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  • What's wrong with sum(mylist)/len(mylist) for computing the average of a list? Commented Mar 14, 2014 at 15:49
  • @Emmet: I think this is a bit more complex. Commented Mar 14, 2014 at 15:50
  • Good answers on this here: stackoverflow.com/questions/13728392/… Commented Mar 14, 2014 at 15:50
  • You should update your previous question instead of asking it again. Commented Mar 14, 2014 at 15:55
  • "Is this correct" - does it give the answer you were expecting? Commented Mar 14, 2014 at 16:05

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There are 24 values for each day. Therefore, you can do something like:

average_temps_array = [sum(map(float, hourly_temp[i:i+24])) / 24 for i in range(0, len(hourly_temp), 24)]
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