拆分fi中的列表

Question

所以我有一个多行的文本文件 每一行都有名字、年级、生日或学生，用分号隔开

我怎样做一个函数，使它对每一行中的所有第二项求和，然后求平均值？你知道吗

例如

mary; 0; 1995
jay; 50; 1995

classAverage = 25

真的很困惑。你知道吗

到目前为止，这是我的代码，它没有给我错误，但是当我打印它时，它说<function classAverage at 0x0000000004C1ADD8>

from kiva.constants import LINES

def process(name):
    f = open(name)
    answer = []
    for line in f:
        answer.append(line.strip())
    return answer
def classAverage(data):
    data = process(filename)
    data.split()
    adding = []
    for line in data:
        adding = adding + data[1]
    return adding/(line)


if __name__ == '__main__':
    filename = "grades.txt"
    data = process(filename)
    for each in data:
        print each
    print classAverage(data)
    #print "Average grade is ", classAverage(data)
    year1 = 1995
    year2 = 1997
    print "Number born from ",year1,"to",year2,"is",
    #print howManyInRange(data, year1, year2)

Answer 1

您应该这样修改函数classAverage：

def classAverage(data):
    # you do not need to re-process the file, just use the data
    adding = []
    for line in data:
        line = line.split(';')
        adding.append(float(line[1].strip()))
    return sum(adding) / len(adding)

Answer 2

def ave(x):
    return sum(x) / len(x)
with open(name, newline='') as csvfile:
    print(ave([float(row[1]) for row in csv.reader(csvfile, dilimeter=';')]))

Answer 3

我在运行该代码时遇到一个错误，但是如果使用“print classAverage”而不是“print classAverage（data）”，则会得到该输出，因此可能您复制的版本与生成该输出的版本略有不同。你知道吗

代码中有几个问题。首先，数据是一个列表，您正在尝试调用它数据.split(). 你也从来没有用“；”分割文本，你的平均公式是错的。我做了一些小小的调整，让它达到我认为你的目的：

def process(name):
f = open(name)
answer = []
for line in f:
    answer.append(line.strip().split(';'))
return answer


def classAverage(data):
    adding = 0.0
    for line in data:
        adding = adding + float(line[1])
    return adding / len(data)


if __name__ == '__main__':
    filename = "grades.txt"
    data = process(filename)
    for each in data:
        print each
    print classAverage(data)
    # print "Average grade is ", classAverage(data)
    year1 = 1995
    year2 = 1997
    print "Number born from ", year1, "to", year2, "is",
    # print howManyInRange(data, year1, year2)

也就是说，pandas非常擅长解析数据文件，然后计算数据的度量。使用pandas解析文件是一行。以下是使用熊猫的等效代码：

import pandas as pd


if __name__ == '__main__':
    df = pd.read_table('grades.txt', sep=';', names=['name', 'score', 'year'])
    print 'Average score = ', df.score.mean()
    year1 = 1995
    year2 = 1997
    print "Number born from ", year1, "to", year2, "is", df[(df.year >= year1) & (df.year <= year2)].name.count()

输出：

Average score =  25.0
Number born from  1995 to 1997 is 2