Question

我需要创建一个函数来计算数据文件（.csv）中每行数字的平均值，然后将该函数作为列表返回。

我已设法获取加在一起的数字的值，但我无法弄清楚如何除以每行数据的长度，然后将结果提供给要返回的列表。

def line_averages(filename):
    """ compute the average value for every line, and return the average
    values in a list in the file "filename" """
    infile = open(filename, "r")
    all_input = infile.read()
    infile.close()
    lines = all_input.split('\n')       # remove lines
    for one_line in lines:
        values = one_line.split(',')    # remove commas
        line_sum = 0 
        print(values)
        for j in values:
            line_sum = line_sum + float(j)

更新：

根据以下建议之一，这是我的新代码：

def line_averages(filename):
""" compute the average value for every line, and return the average
values in a list in the file "filename" """
f = open(filename, "r")
x = f.read()
f.close()
no_lines = x.split('\n')       # remove lines
means = []
for i in no_lines:
    no_commas = i.split(',')    # remove commas
    average = sum(no_commas) / len(no_commas)
    means.append(average)
return means

我收到此错误：

In [22]: line_averages("data.csv")
Traceback (most recent call last):

File "<ipython-input-29-e2e3fddb5de5>", line 1, in <module>
line_averages("data.csv")

File "E:/Google Drive/python_files/training4.py", line 19, in line_averages
average = sum(no_commas) / len(no_commas)

TypeError: unsupported operand type(s) for +: 'int' and 'str'

不确定出了什么问题？！

Answer 1

return_list = []
...
    average = sum(values) / len(values)
    return_list.append(average)

此外，请使用描述性变量名称。单字母变量适用于丢失指数，但不适用于具有持久意义的任何内容。

扰流警报

# If you have the statistics package, use "mean" from that, instead.
def mean(coll):
    return float(sum(coll)) / max(len(coll), 1)

def line_averages(filename):
    """ compute the average value for every line, and return the average
    values in a list in the file "filename" """

    return [mean([int(values) for values in line.split(',')]) for line in open(filename)]

Answer 2

根据您的代码，可以使用len(c)找到每行上的元素数量。使用当前代码将这些添加到列表的最简单方法是在for循环之前初始化一个空列表：

means = []

然后append每个计算平均值到此列表：

means.append(s / len(c))

一般来说，有更有效的方法可以做到这一点（搜索'list comprehension'），但这应该是让你前进的最快方法。

数据文件中行的平均值

2 个答案: