如何根据索引位置将列表列表连接到另一个小列表？

Question

I have to take a list of lists and another list and create a relationship between them. For context, I am not allowed to use pandas or dictionaries or anything like that.

I have opened two files and created two functions, the first function that turns the file with the year and the 12 job creation values assigned to that year making a list of lists. The next file is the name of the presidents and the years they served, for the second function I made the data in that file into a list.

I have to correlate their party and the president's term with the year they served and when I am done with assigning the president with the list of lists, I have to average them.

What I need help doing is somehow merging the lists so that I could have each president with their assigned year and the data for that year in a list. an example of what I need is like: [James Earl Carter, 1979-1981, Democrat, 140990, 14135, etc...] for all the years he served. `

Here is an example of both files:

1979,14090,14135,14152,14191,14221,14239,14288,14328,14422,14484,14532,14559
1980,14624,14747,14754,14795,14827,14784,14861,14870,14824,14900,14903,14946
1981,14969,14981,14987,14985,14971,14963,14993,15007,14971,15028,15073,15075
1982,15056,15056,15050,15075,15132,15207,15299,15328,15403,15463,15515,15538
1983,15611,15671,15731,15797,15834,15852,15901,15891,15819,15858,15894,15911
1984,15937,15947,15956,15977,15990,16045,16150,16229,16128,16136,16173,16180
1985,16201,16226,16296,16583,16454,16441,16418,16410,16330,16386,16391,16373
1986,16360,16346,16292,16260,16198,16159,16175,16110,16031,16069,16078,16073
1987,16041,16011,16024,16010,16003,16016,15890,15930,15923,15956,15977,15981
1988,16023,16004,16005,15990,16005,16020,16011,16016,16042,15986,15997,16008
1989,16010,16025,16030,16075,16103,16127,16172,16224,16255,16274,16311,16282

---

James Earl Carter, 1979-1981, Democrat
Ronald Wilson Reagan, 1981-1989, Republican

And here is the code I have so far:

def avg():
      file = open("government_employment_Windows.txt")
      my_list = []

      for line in file:
          line.strip()
          line = line.split(',')
          line[1] = int(line[1])
          line[2] = int(line[2])
          line[3] = int(line[3])
          line[4] = int(line[4])
          line[5] = int(line[5])
          line[6] = int(line[6])
          line[7] = int(line[7])
          line[8] = int(line[8])
          line[9] = int(line[9])
          line[10] = int(line[10])
          line[11] = int(line[11])
          line[12] = int(line[12])

          my_list.append(line)
    file.close()
    return my_list


def pres(list_of_lists):
    p_file = open("presidents_Windows.txt")
    print(list_of_lists)

    for line in p_file:
        line = line.strip()
        line = line.split(',')
        line[1] = line[1].strip()
        line[2] = line[2].strip()
    print(line)

    for small_list in list_of_lists:
        if line[0] in small_list:
            small_list.append(line[0])
    print(list_of_lists)
list_of_lists = avg()
pres(list_of_lists)

Final result should look like:

Government employement average per month:
    Republican: 18562
    Democrat: 19599


Government Employment by President:
     First Month    Last Month     Difference
Carter: 14090          14946
Reagan: 14969           16008
Bush: 16010             17347
Clinton: 17365          19466
Bush: 19450             21546
Obama: 21538            22266
Trump: 22264            21902

Answer 1

Because this is a homework problem, I will not solve the entire problem for you; however, I will go over how to merge the lists together based on the years a president served. You can take the output below and format it the way you like and take the average quite easily.

To start, let's say you get the jobs and presidents in their respective lists (when you clean the data from the file), like so:

jobs = [
    [1979,14090,14135,14152,14191,14221,14239,14288,14328,14422,14484,14532,14559],
    [1980,14624,14747,14754,14795,14827,14784,14861,14870,14824,14900,14903,14946],
    [1981,14969,14981,14987,14985,14971,14963,14993,15007,14971,15028,15073,15075],
    [1982,15056,15056,15050,15075,15132,15207,15299,15328,15403,15463,15515,15538],
    [1983,15611,15671,15731,15797,15834,15852,15901,15891,15819,15858,15894,15911],
    [1984,15937,15947,15956,15977,15990,16045,16150,16229,16128,16136,16173,16180],
    [1985,16201,16226,16296,16583,16454,16441,16418,16410,16330,16386,16391,16373],
    [1986,16360,16346,16292,16260,16198,16159,16175,16110,16031,16069,16078,16073],
    [1987,16041,16011,16024,16010,16003,16016,15890,15930,15923,15956,15977,15981],
    [1988,16023,16004,16005,15990,16005,16020,16011,16016,16042,15986,15997,16008],
    [1989,16010,16025,16030,16075,16103,16127,16172,16224,16255,16274,16311,16282]
]

pres = [
    ["James Earl Carter", "1979-1981", "Democrat"],
    ["Ronald Wilson Reagan", "1981-1989", "Republican"]
]

For demonstration purposes, let's define carter in a separate variable:

carter = pres[0]

To merge this data, you can define two functions. One for turning the "YYYY-YYYY" into a range of integers that you can use to merge the lists of jobs for each of the years that the president served. The other function will be for actually merging the lists together.

def to_range(years):
    r = [int(i) for i in years.split("-")]
    return [i for i in range(r[0], r[1]+1)]

The above function will take a string as input and expects it in the "YYYY-YYYY" form. For example, if we want the years that Carter served, we can say:

to_range(carter[1])

which outputs:

[1979, 1980, 1981]

Now that we have all of the years that Carter served, we can move on to the second function. If you want a one-liner, you can do so with this rather ugly and long list comprehension:

def get_all_jobs(year_range, jobs):
    return [n[i] for n in jobs if n[0] in year_range for i in range(1, len(n))]

If you're looking for a "prettier" alternative, using extend will also work:

def get_all_jobs(year_range, jobs):
    all_jobs = []
    for n in jobs:
        if n[0] in year_range:
            all_jobs.extend(n[1:])
    return all_jobs

The above function creates one merged list. If we call the function like this, passing in Carter's range:

carter_jobs = get_all_jobs(carter_years, jobs)

we get:

[14090, 14135, 14152, 14191, 14221, 14239, 14288, 14328, 14422, 14484, 14532, 14559, 14624, 14747, 14754, 14795, 14827, 14784, 14861, 14870, 14824, 14900, 14903, 14946, 14969, 14981, 14987, 14985, 14971, 14963, 14993, 15007, 14971, 15028, 15073, 15075]

Answer 2

Here's an example to get you started:

from io import StringIO

# sample data, these behave like a file,
# as if you did government_employment = open('filename.txt')
f_government_employment = StringIO("""1979,14090,14135,14152,14191,14221,14239,14288,14328,14422,14484,14532,14559
1980,14624,14747,14754,14795,14827,14784,14861,14870,14824,14900,14903,14946
1981,14969,14981,14987,14985,14971,14963,14993,15007,14971,15028,15073,15075
1982,15056,15056,15050,15075,15132,15207,15299,15328,15403,15463,15515,15538
1983,15611,15671,15731,15797,15834,15852,15901,15891,15819,15858,15894,15911
1984,15937,15947,15956,15977,15990,16045,16150,16229,16128,16136,16173,16180
1985,16201,16226,16296,16583,16454,16441,16418,16410,16330,16386,16391,16373
1986,16360,16346,16292,16260,16198,16159,16175,16110,16031,16069,16078,16073
1987,16041,16011,16024,16010,16003,16016,15890,15930,15923,15956,15977,15981
1988,16023,16004,16005,15990,16005,16020,16011,16016,16042,15986,15997,16008
1989,16010,16025,16030,16075,16103,16127,16172,16224,16255,16274,16311,16282""")

f_presidents = StringIO("""James Earl Carter, 1979-1981, Democrat
Ronald Wilson Reagan, 1981-1989, Republican""")


# ideally, you'd use classes for something like this, but since the exercise appears
# to be about doing it with basic data structures, just using functions and lists:

def read_employment(f):
    # reads the employment 'file' into a list of lists that pairs up a year and a
    # list of months of employment
    for line in f:
        line = [int(x) for x in line.strip().split(',')]
        # you'd use tuples, but since you want lists only
        yield [line[0], line[1:]]


def get_employment(employment, year, month):
    # given an iterable (like a list) created from the read_employment generator,
    # gets the employment for a specific year and month combo
    for e in employment:
        if e[0] == year:
            # month-1, to have months from 1-12
            return e[1][month-1]


def read_presidents(f):
    for line in f:
        line = line.split(',')
        term = [int(x) for x in list(line[1].strip().split('-'))]
        yield [line[0].strip(), term, line[2].strip()]


def get_term_months(presidents, president):
    for p in presidents:
        if president in p[0]:
            for year in range(p[1][0], p[1][1]):
                for month in range(1, 13):
                    # skip January of the first year, the previous president still going
                    if month != 1 or year != p[1][0]:
                        yield year, month
            # only January of the list year
            yield [p[1][1], 1]


def main():
    government_employment = list(read_employment(f_government_employment))
    # for example, showing the government employment for March, 1981
    print(get_employment(government_employment, 1981, 3))

    presidents = list(read_presidents(f_presidents))
    # for example, showing all the months for Carter
    print(list(get_term_months(presidents, 'Carter')))

    # now, you can do things like compute the average government employment
    # during the Carter presidency
    values = [
        get_employment(government_employment, year_month[0], year_month[1])
        for year_month in get_term_months(presidents, 'Carter')
    ]
    print(f'Average government employment during the Carter presidency: {sum(values)/len(values)}')


if __name__ == '__main__':
    main()

Mind you, there's some ugly parts in here still. For example, if you didn't use just lists, but also tuples, something like this:

    values = [
        get_employment(government_employment, year_month[0], year_month[1])
        for year_month in get_term_months(presidents, 'Carter')
    ]

Would look like this (assuming get_term_months would now return a tuple):

    values = [
        get_employment(government_employment, year, month)
        for year, month in get_term_months(presidents, 'Carter')
    ]

Well beyond the scope of your question, but to give you a sense, using classes would allow you to put stuff together in an even nicer way. For example, this is what the employment stuff starts to look like:

class Employment:
    def __init__(f):
        self.data = [int(x) for x in line.strip().split(',') for line in f]

    def get_employment(employment, year, month):
        for e in self.data:
            if e[0] == year:
                return e[month]


government_employment = Employment(f_government_employment)