Python - 在計算之前從文件中過濾行

Question

下一個代碼計算輸入文件中每列的平均值。它一直運行，直到文件有nan的值扭曲平均值。

這裏是我的代碼：

with open(biasfile, 'r') as f: 
    data = [map(float, line.split()) for line in f] 

num_rows = len(data) 
num_cols = len(data[0]) 

totals = num_cols * [0.0] 

for line in data: 
    for index in xrange(num_cols): 
     totals[index] += line[index] 

averages = [total/num_rows for total in totals] 
print averages 

這是文件的一部分：

22.7061 5.4303 
32.2040 5.4364 
22.9982 5.4426 
nan 5.4487 
nan 5.4548 
nan 5.4610 

這是輸出：

[nan, 3.1446607421875] 

我想忽略nan值和計算其餘值的平均值。我怎麼能這樣做？

Answer 1

你可以使用Python列表解析來過濾數據：

with open('file.txt') as file: 
    data = [line.split() for line in file] 
    data = [item for item in data if 'nan' not in item] 
    data = [map(float, item) for item in data] 

totals = len(data[0]) * [0.0] 

for item in data: 
    for k, n in enumerate(item): 
     totals[k] += n 

print([total/len(data) for total in totals]) 

另一種方法：

with open('file.txt') as file: 
    data = [line.split() for line in file] 
    data = [item for item in data if 'nan' not in item] 
    data = [map(float, item) for item in data] 

print([sum(d[k] for d in data)/len(data) for k in range(len(data[0]))]) 

Answer 2

不能使用數據幀API和做類似：

dataFrame.map(x => if (!x.isNaN) x).avg