解决方案

Question

我有这行代码用于一次分配，但是我不知道如何在代码中添加中位数和众数以使其运行而不会出错。

def main():
    filename = input('File name: ')
    num=0
    try:

        infile = open(filename, 'r')
        count = 0
        total = 0.0
        average = 0.0
        maximum = 0
        minimum = 0
        range1 = 0

        for line in infile:
            num = int(line)
            count = count + 1
            total = total + num

            if count == 1:
                maximum = num
                minimum = num
            else:
                if num > maximum:
                    maximum = num
                if num < minimum:
                minimum = num

    if count > 0:
        average = total / count
        range1 = maximum - minimum

Answer 1

我将立即进入并向您显示代码。这是一个非常简单且相当Python化的解决方案。

解决方案

import statistics


def open_file(filename):
    try:
        return open(filename, 'r')
    except OSError as e:
        print(e)
        return None


def main():
    # Read file. Note that we are trusting the user input here without sanitizing.
    fd = open_file(input('File name: '))

    if fd is None:  # Ensure we have a file descriptor
        return

    data = fd.read()  # Read whole file
    if data == '':
        print("No data in file")
        return
    lines = data.split('\n')  # Split the data into a list of strings

    # We need to convert the list of strings to a list of integers
    # I don't know a pythonic way of doing this.
    for number, item in enumerate(lines):
        lines[number] = int(item)

    total_lines = len(lines)
    total_sum = sum(lines)
    maximum = max(lines)
    minimum = min(lines)

    # Here is the python magic, no need to reinvent the wheel!
    mean = statistics.mean(lines)  # mean == average
    median = statistics.median(lines)
    mode = "No mode!"
    try:
        mode = statistics.mode(lines)
    except statistics.StatisticsError as ec:
        pass  # No mode, due to having the same quantity of 2 or more different values 

    print("Total lines: " + str(total_lines))
    print("Sum: " + str(total_sum))
    print("Max: " + str(maximum))
    print("Min: " + str(minimum))
    print("Mean: " + str(mean))
    print("Median: " + str(median))
    print("Mode: " + str(mode))


if __name__ == '__main__':
    main()

说明

通常，在python中，可以安全地假设，如果您想使用众所周知的算法来计算任何平凡的值，那么已经有编写的函数可以做到这一点。无需重新发明轮子！

这些功能通常也不难在网上找到。例如，您可以通过搜索 python计算中位数

找到有关统计资料库的建议

尽管您有解决方案，但我强烈建议您仔细阅读统计资料库的源代码（如下所述），并弄清楚这些功能如何为您自己工作。它将帮助您成长为开发人员和数学家。

statistics.py

平均值

def mean(data):
    """Return the sample arithmetic mean of data.

    >>> mean([1, 2, 3, 4, 4])
    2.8

    >>> from fractions import Fraction as F
    >>> mean([F(3, 7), F(1, 21), F(5, 3), F(1, 3)])
    Fraction(13, 21)

    >>> from decimal import Decimal as D
    >>> mean([D("0.5"), D("0.75"), D("0.625"), D("0.375")])
    Decimal('0.5625')

    If ``data`` is empty, StatisticsError will be raised.
    """
    if iter(data) is data:
        data = list(data)
    n = len(data)
    if n < 1:
        raise StatisticsError('mean requires at least one data point')
    T, total, count = _sum(data)
    assert count == n
    return _convert(total/n, T)

中位数

def median(data):
    """Return the median (middle value) of numeric data.

    When the number of data points is odd, return the middle data point.
    When the number of data points is even, the median is interpolated by
    taking the average of the two middle values:

    >>> median([1, 3, 5])
    3
    >>> median([1, 3, 5, 7])
    4.0

    """
    data = sorted(data)
    n = len(data)
    if n == 0:
        raise StatisticsError("no median for empty data")
    if n%2 == 1:
        return data[n//2]
    else:
        i = n//2
        return (data[i - 1] + data[i])/2

模式

def mode(data):
    """Return the most common data point from discrete or nominal data.

    ``mode`` assumes discrete data, and returns a single value. This is the
    standard treatment of the mode as commonly taught in schools:

    >>> mode([1, 1, 2, 3, 3, 3, 3, 4])
    3

    This also works with nominal (non-numeric) data:

    >>> mode(["red", "blue", "blue", "red", "green", "red", "red"])
    'red'

    If there is not exactly one most common value, ``mode`` will raise
    StatisticsError.
    """
    # Generate a table of sorted (value, frequency) pairs.
    table = _counts(data)
    if len(table) == 1:
        return table[0][0]
    elif table:
        raise StatisticsError(
                'no unique mode; found %d equally common values' % len(table)
                )
    else:
        raise StatisticsError('no mode for empty data')

扩展当前代码以包括中位数和众数

1 个答案:

解决方案

说明