Finding an average but ignoring any zero in a list [Python]

Question

I have a text file of temperature data that looks like this:

3438012868.0    0.0 21.7    22.6    22.5    22.5    21.2
3438012875.0    0.0 21.6    22.6    22.5    22.5    21.2
3438012881.9    0.0 21.7    22.5    22.5    22.5    21.2
3438012888.9    0.0 21.6    22.6    22.5    22.5    21.2
3438012895.8    0.0 21.6    22.5    22.6    22.5    21.3
3438012902.8    0.0 21.6    22.5    22.5    22.5    21.2
3438012909.7    0.0 21.6    22.5    22.5    22.5    21.2
3438012916.6    0.0 21.6    22.5    22.5    22.5    21.2
3438012923.6    0.0 21.6    22.6    22.5    22.5    21.2
3438012930.5    0.0 21.6    22.5    22.5    22.5    21.2
3438012937.5    0.0 21.7    22.5    22.5    22.5    21.2
3438012944.5    0.0 21.6    22.5    22.5    22.5    21.3
3438012951.4    0.0 21.6    22.5    22.5    22.5    21.2
3438012958.4    0.0 21.6    22.5    22.5    22.5    21.3
3438012965.3    0.0 21.6    22.6    22.5    22.5    21.2
3438012972.3    0.0 21.6    22.5    22.5    22.5    21.3
3438012979.2    0.0 21.6    22.6    22.5    22.5    21.2
3438012986.1    0.0 21.6    22.5    22.5    22.5    21.3
3438012993.1    0.0 21.6    22.5    22.6    22.5    21.2
3438013000.0    0.0 21.6    0.0     22.5    22.5    21.3
3438013006.9    0.0 21.6    22.6    22.5    22.5    21.2
3438013014.4    0.0 21.6    22.5    22.5    22.5    21.3
3438013021.9    0.0 21.6    22.5    22.5    22.5    21.3
3438013029.9    0.0 21.6    22.5    22.5    22.5    21.2
3438013036.9    0.0 21.6    22.6    22.5    22.5    21.2
3438013044.6    0.0 21.6    22.5    22.5    22.5    21.2

but the entire file is much longer, this is the first few lines. The first column is a timestamp and the next 6 columns are temperature recordings. I need to write a loop that will find the average of the 6 measurements but will ignore measurement of 0.0 because this just means the sensor wasn't turned on. Later in the measurements, the first column does have a measurement. Is there a way for me to write an if statement or another way to only find averages of the non-zero numbers in a list? Right now, I have:

time = []
t1 = []
t2 = []
t3 = []
t4 = []
t5 = []
t6 = []
newdate = []

temps = open('file_path','r')
sepfile = temps.read().replace('\n','').split('\r')
temps.close()

for plotpair in sepfile:
    data = plotpair.split('\t')
    time.append(float(data[0]))
    t1.append(float(data[1]))
    t2.append(float(data[2]))
    t3.append(float(data[3]))
    t4.append(float(data[4]))
    t5.append(float(data[5]))
    t6.append(float(data[6]))

for data_seconds in time:
    date = datetime(1904,1,1,5,26,02)
    delta = timedelta(seconds=data_seconds)
    newdate.append(date+delta)

for datapoint in t2,t3,t4,t5,t6:
    temperatures = np.array([t2,t3,t4,t5,t6]).mean(0).tolist()

which only finds the average for the last 5 measurements. I'm hoping to find a better method that will ignore 0.0's and include the first column when it is a non-0.

Answer 1

Prior questions show you have NumPy installed. So using NumPy, you could set the zeros to NaN and then call np.nanmean to take the mean, ignoring NaNs:

import numpy as np

data = np.genfromtxt('data')
data[data == 0] = np.nan
means = np.nanmean(data[:, 1:], axis=1)

yields

array([ 22.1  ,  22.08 ,  22.08 ,  22.08 ,  22.1  ,  22.06 ,  22.06 ,
        22.06 ,  22.08 ,  22.06 ,  22.08 ,  22.08 ,  22.06 ,  22.08 ,
        22.08 ,  22.08 ,  22.08 ,  22.08 ,  22.08 ,  21.975,  22.08 ,
        22.08 ,  22.08 ,  22.06 ,  22.08 ,  22.06 ])

Answer 2

You can make an truncated/trimmed mean using scipy.stats.tmean

Or you can check if float(data[X]) is equal to 0, before appending it to the corresponding list