python – 存储最后3个分数并删除旧分数并计算平均值?

我正在制作一个打开并读取csv文件的程序,并按以下方式排序:

>按字母顺序排列,每位学生得分最高.
>以最高分,从最高到最低.
>平均得分,从最高到最低.

该计划应存储每个学生的最后3个分数.这是我坚持并需要帮助的部分.按字母顺序对文件进行排序时,程序需要查看每个学生最近3个最近的分数并选择最高分数.目前,我的代码只按字母顺序对文件进行排序.它会查看最近的3个分数并选择最高分.这是我需要帮助的地方.

我的代码已经将分数从最高到最低排序,但是它打印出每个学生获得的所有分数,而不是从他们最近的3分中打出最高分.

Andrew 1
Andrew 2
Andrew 3
Andrew 4
Andrew 5

最后,我需要帮助计算每个学生的平均分数.我猜它应该做的方式是,加上安德鲁的最后3分,分别是5分,4分和3分,除以3分.

这是我的代码:

import csv, operator

selected_class = input("Pick a class file, (5, 6 or 7)? ")

print("1. Alphabetical order.")
print("2. Highest to lowest.")
print("3. Average score.")

selected_sorting = input("Pick an option 1, 2, or 3: ")

class_file = "Class " + selected_class + ".csv"
open_file = open(class_file)
csv_file = csv.reader(open_file)

if selected_sorting == "1":
    sorted_name = sorted(csv_file, key=operator.itemgetter(0))
    for i in sorted_name:
        print(i)

elif selected_sorting == "2":
    sorted_results = sorted(csv_file, key=lambda row: int(row[1]), reverse=True)
    for i in sorted_results:
        print(i)

elif selected_sorting == "3":

最佳答案 我将给出一些演示代码:

# -*- coding: utf-8 -*-
import csv
from collections import defaultdict
from statistics import mean

class_file = 'scores.csv'
open_file = open(class_file)
csv_file = csv.reader(open_file)


def main():
    # First, use student name to group by all scores, this will
    # generate structure like this:
    # {
    #     'Andrew': [1, 2, 3, 4, 5]),
    #     'Luck': [10, 20]),
    # }
    score_groups = defaultdict(list)
    for name, score in csv_file:
        score_groups[name].append(int(score))

    # Secondary, use the 3 latest socres only 
    l3_score_groups = [(key, value[-3:]) for key, value in score_groups.items()]

    print('1. Alphabetical order with each students highest score.')
    l3_highest_score_groups = [(key, max(values)) for key, values in l3_score_groups]
    for name, score in sorted(l3_highest_score_groups, key=lambda x: x[0]):
        print(name, score)

    print('2. By the highest score, highest to lowest.')
    l3_highest_score_groups = [(key, max(values)) for key, values in l3_score_groups]
    for name, score in sorted(l3_highest_score_groups, key=lambda x: x[1], reverse=True):
        print(name, score)

    print('3. Average score, highest to lowest.')
    l3_aver_score_groups = [(key, mean(values)) for key, values in l3_score_groups]
    for name, score in sorted(l3_aver_score_groups, key=lambda x: x[1], reverse=True):
        print(name, score)


if __name__ == '__main__':
    main()

以下是上面使用的技术:

> collections.defaultdict:进行数据分组工作时有用的数据结构.
> list-comprehensions:用于更改/过滤可迭代数据的强大工具.
> statistics.mean:计算列表的平均值.

希望能帮助到你.

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