查找平均值但忽略列表中的任何零[Python]

Question

我有一个温度数据的文本文件,如下所示:

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

但整个文件要长得多,这是前几行.第一列是时间戳,接下来的6列是温度记录.我需要编写一个循环,它将找到6个测量值的平均值,但会忽略0.0的测量值,因为这只意味着传感器没有打开.在测量的后期,第一列确实有测量.有没有办法让我写一个if语句或其他方法来只找到列表中非零数字的平均值？现在,我有:

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()

它只能找到最后5次测量的平均值.我希望找到一个更好的方法,它将忽略0.0并包含第一列,当它是非0时.

Answer 1

先前的问题表明您已安装NumPy.所以使用NumPy,你可以将零设置为NaN,然后​​调用np.nanmean取平均值,忽略NaN:

import numpy as np

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

产量

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 ])