Please solve as soon as possible, nee help with computer science project

Definitions

CSV file

: This is a file containing plain text where each line in the file represents one record of

information, and each piece of info in the record is separated by a single comma. Luckily the

values

won't ever contain commas

themselves for this project. But they might start or end with

non visible characters (e.g. space, tab). Thus, you

must remove

the leading and trailing spaces

when you store the data in a dictionary in memory. The very first line is the

header

row, which

names the columns but is

not

part of the data, and therefore should

not

be loaded into

memory.

Note

: the filename extension you use has no effect on the contents; you can edit it and

give it any extension you want without changing the ability of your program. In this project well

be using two kinds of CSV files:

votes.csv

file:

It contains records of votes in the following format:

state, candidate, party, popular_votes, electoral_votes

AL, Johnson, IND, 44467, 0

AL, Stein, IND, 9391, 0

AK, Trump, REP, 163387, 9

VA, Clinton, DEM, 1981473, 13

Note:

the total number of electoral votes in the file is 531 instead of 538 because 7 votes of the

electoral college were not given as promised!

abbreviations.csv

file:

It contains abbreviations of strings in the following format:

abbreviation, full_string

AL, Alabama

AK, Alaska

VA, Virginia

Johnson, Gary Johnson

Stein, Jill Stein

IND, Independent

REP, Republican

DEM, Democratic

For storage efficiency all files contain string abbreviations. When we load the files into memory

we will also be using the same abbreviations for memory efficiency. But when we present results

as output of the program we will be using the full strings.

Candidate

: we will use the following representation for a

candidate

inside our program: a

tuple containing these values in this order. Note that

name

and

party

are string abbreviations,

and

popular_votes

and

electoral_votes

are

integers.

candidate = (name, party, popular_votes, electoral_votes)

Database1

: a database of votes can store all candidates votes for each State. Obviously, a

candidates name may get reused in different States, but never in the same State. Not all

candidate names appear in every State.

Our database

must be a dictionary

whose

keys are

States

, and whose

values are lists of candidate values

. Only candidates with

positive number

of

popular_votes

may be present in a State. Empty lists are

not allowed

as values. Candidates in the

same State must be stored

alphabetically

by their abbreviated name (hint: use

insert

instead of

append

when adding items to the list because you cant use sorting functions).

votes_db = {

AL: [(Johnson, IND, 44467, 0), (Stein, IND, 9391, 0)],

AK: [(

Trump, REP, 163387, 9

)],

VA: [(

Clinton, DEM, 1981473, 13

)]

...

...

...

}

Database2

: a database of abbreviations will store all abbreviations as a dictionary whose

keys are the abbreviated strings and whose values are the equivalent full strings, like in the

following sample:

abbr_db = {

AL: Alabama,

AK: Alaska,

DEM:

Democratic,

REP: Republican,

Trump: Donald Trump

...

...

...

}

Functions

read_votes(filename)

Description

: It reads votes from a file and creates in memory a dictionary of

database1

type

Parameters

: a filename of

a

CSV formated votes file

a

s described above

Return value

: the dictionary object created or False for any kind of error

Examples

:

db = read_votes(votes.csv)

db is a database1 dictionary

db = read_votes(file_with_wrong_format)

db = False

write_votes(db, filename)

Description

: It writes the contents of a

database1

dictionary back to a CSV file in the same format

as it was the original input file

Parameters

: a

database1

and a filename

Return value

: True for success or False for any kind of error

Examples

:

write_votes(db, new_votes.csv)

True (if db is a database1 dictionary)

write_votes(db, new_votes.csv)

False (if db is an empty dictionary or another type of variable)

read_abbreviations(filename)

Description

: It reads abbreviations from a file and creates in memory a dictionary of

database2

type

Parameters

:

a filename of

a

CSV formated abbreviations file

a

s described above

Return value

:

the dictionary object created or False for any kind of error

Examples

:

db = read_abbreviations(abbreviations.csv)

db is a databse2 dictionary

db = read_abbreviations(file_with_wrong_format)

db = False

add_candidate(db, state, name, party, popular_votes, electoral_votes)

Description

: It accepts an existing database and a candidate name along with the relevant info. If

the candidate and/or the State already exist, it updates their info, otherwise it adds a new record

for the candidate and/or the State. The function assumes the length of the input and the types

are correct, no need for this kind of checks.

Parameters

:

database1

and details for a candidate

Return value

:

None

Examples

:

add_candidate(db, VA, Clinton, DEM, 1234567, 10)

None

add_candidate(db, TX, Trump, REP, 2345678, 23)

None

remove_candidate(db, name, state=None)

Description

: It removes a candidate from either one or all the States. Keep in mind that after

removal dictionary keys cannot point to empty lists.

Parameters

:

database1

, the abbreviated name of a candidate and the abbreviated name of a

State. If

state

is not provided it will remove the candidate from all States.

Return value

:

False if state doesnt exist in dictionary, None otherwise

Examples

:

remove_candidate(db, Clinton)

None

remove_candidate(db, Trump, TX)

None

remove_candidate(db, Trump, VR)

False

incorporate_precinct(db, name, state, popular_votes_increment)

Description

: It increases the number of popular votes for a certain candidate in a specific State.

Parameters

:

database1

, name of candidate, State, increment of popular votes

Return value

:

False if state and/or candidate dont exist in dictionary, None otherwise

Examples

:

incorporate_precinct(db, Stein, VA, 1000)

None

incorporate_precinct(db, Stein, VR, 1000)

False

incorporate_precinct(db, Socrates, VA, 1000)

False

merge_votes(db, name1,name2, new_name, new_party, state=None)

Description

: It merges the votes of two candidates in a given State. If

state

is not provided it will

merge the two candidates in all States. If only one of the two candidates is present in a certain

State, the renaming will still take place. The function assumes the inputs and the types are

correct, no need for this kind of checks.

Parameters

:

database1

, the abbreviated names of two candidates, the new name after merging,

the new party name, and the abbreviated State name

Return value

:

None

Examples

:

merge_votes(db, Johnson, Stein, Other, IND, RI)

None

merge_votes(db, Johnson, Stein, Other, IND)

None

number_of_votes(db, name, category=popular, numbering=tally, state=None)

Description

: It counts the number of votes for a certain candidate in one or all the States

Parameters

:

database1

, the name of the candidate, optional category is popular or electoral

(default: popular), optional numbering is tally or percent (default: tally). Parameter state is

optional, if omitted the counting is over the whole country. All parameters

must be checked

for

correctness, do not assume the arguments are correct.

Return value

:

integer if numbering is tally, float rounded to 2 decimals if numbering is percent.

False if error (e.g. wrong name or name thats not included in this State, or numbering is an

invalid string, etc.)

Examples

:

number_of_votes(db, Trump, popular, tally, VA)

1769443

number_of_votes(db, Clinton, electoral)

227

number_of_votes(db, Johnson, popular, percent)

3.28

number_of_votes(db, Johnson, POPULAR, percent)

False

number_of_votes(db, McMullin)

731991

number_of_votes(db, Trump, popular, tally, VR)

False

number_of_votes(db, Johnson, popular, Percent)

False

popular_votes_performance(db, name, numbering, order=max)

Description

: It finds the State where the candidate got the maximum (or the minimum) number

of popular votes, either by tally or percent. You dont have to consider the case of a tie between

two States.

Parameters

:

database1

, the name of the candidate, numbering is tally or percent, optional

order is max or min (default: max)

Return value

:

full name

of State, False if error (e.g. candidate doesnt exist or order has an

invalid value)

Examples

:

popular_votes_performance(db, Trump, percent, min)

District of Columbia

popular_votes_performance(db, Trump, percent, best)

False

popular_votes_performance(db, Clinton, tally, min)

Wyoming

candidates_difference(db, name1, name2, order=smallest)

Description

: It finds the State where the two candidates had the smallest or largest difference

in popular_vote as percentage of State votes. States that dont contain both names dont count,

but if the two candidates did not compete in

any

State, thats an error.

Parameters

:

database1

, the names of the two candidates, optional order is smallest or largest

(default: smallest)

Return value

:

full name of State, False if error (e.g. order has invalid value, the two candidates do

not compete in any State)

Examples

:

candidates_difference(db, McMullin, Johnson, largest)

Utah

candidates_difference(db, McMullin, Johnson, best)

False

candidates_difference(db, Trump, Clinton)

Michigan

Extra Credit

reverse_result(db, name, winner=Trump)

Description

: It finds the minimum set of States (in ascending order of the percentage difference

of the popular vote) in which the

name

should have added the winners electoral votes in order

to reverse the overall elections outcome and be the winner. The name of the winner is a default

parameter (=Trump), you dont have to compute it. Argument

name

can be any valid name of a

candidate except the winner. The function is

not allowed

to modify the dictionary

db

.

Parameters

:

database1

, the name of the candidate

Return value

:

a list of States with full names, False if error (e.g. invalid name)

Examples

:

reverse_result(db, Clinton)

['Michigan', 'Pennsylvania', 'Wisconsin']

reverse_result(db, Socrates)

False

reverse_result(db, Trump)

False

reverse_result(db, Johnson, Trump)

['Maine', 'Utah', 'Wisconsin', 'Michigan', 'Arizona', 'Alaska', 'Pennsylvania', 'Florida',

'North Carolina', 'Iowa', 'Georgia', 'Ohio', 'Texas', 'Montana', 'Kansas', 'Indiana', 'South Carolina', 'Missouri', 'Nebraska', 'Idaho',

'South Dakota', 'Louisiana', 'North Dakota', 'Mississippi', 'Tennessee', 'Arkansas']