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Python代写：COMSW3101 Introduction to Python
saferman
10 1 月, 2023
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Introduction

本次需要代写的Python作业，包含了5个算术问题需要解决。

Problem 1 - Decrypting Government Data

Your job is to summarize this gov data about oil consumation

  • The format of the file is rather bizzare - note that each line has data for two months, in two different years! (Plus I had to hand edit the file to make it parseable)
  • Fortunately, Python is great for untangling and manipulating data.
  • Write a generator that reads from the given url over the network, and produces a summary line for a years data on each next call
  • remember that urllib.request returns bytes arrays, not strings
  • The generator should read the lines of the oil2.txt file in a lazy fashion - it should only read 13 lines for every two years of output. Note a loop can have any number of yield calls in it.
  • Ignore the monthly data, just extract the yearly info
  • Drop the month column
  • In addition to the oil generator function, my solution had a separate helper function, def makeCSV- Line(year, data):

Here is the first two years of data, 2014 and 2013

Year,Quantity,QuantityChange,Unknown,Unknown2,Price,PriceChange2014,2700903,-112867,246409332,-26397845,91.23,-5.722013,2813770,-283638,272807177,-40367786,96.95,-4.152012,3097408,-224509,313174963,-18407090,101.11,1.292011,3321917,-55160,331582053,79421544,99.82,25.152010,3377077,62290,252160509,63448733,74.67,17.742009,3314787,-275841,188711776,-153200712,56.93,-38.292008,3590628,-99940,341912488,104700835,95.22,30.952007,3690568,-43658,237211653,20584322,64.28,6.262006,3734226,-20445,216627331,40871990,58.01,11.202005,3754671,-66308,175755341,44012676,46.81,12.332004,3820979,144974,131742665,32575492,34.48,7.502003,3676005,257983,99167173,21883842,26.98,4.372002,3418022,-53045,77283331,2990437,22.61,1.212001,3471067,71827,74292894,-15583539,21.40,-5.042000,3399240,171148,89876433,38986812,26.44,10.681999,3228092,-14620,50889621,13637399,15.76,4.281998,3242712,173281,37252222,-16973685,11.49,-6.181997,3069431,175785,54225907,-704950,17.67,-1.321996,2893646,126333,54930857,11181204,18.98,3.17

now that we have something that looks like a CVS file, can do all kinds of things

  • could save it to a file then
    • excel, openoffice could read it
    • Python has a CVS Reader
  • with a little juggling, can easily pump the data into a panda DataFrame

Input:

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with open('/tmp/oil.csv', 'w') as f:
  for l in oil(url):
  f.write(l + '\n')

o = oil(url)
ls = list(o)
s = '\n'.join(ls)
import pandas as pd
import io
# we will cover StringIO next week - kind of an 'in-memory' file
df = pd.read_csv(io.StringIO(s))
df

Output:

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    Year Quantity QuantityChange    Unknown   Unknown2   Price PriceChange
0   2014  2700903        -112867  246409332  -26397845   91.23       -5.72
1   2013  2813770        -283638  272807177  -40367786   96.95       -4.15
2   2012  3097408        -224509  313174963  -18407090  101.11        1.29
3   2011  3321917         -55160  331582053   79421544   99.82       25.15
4   2010  3377077          62290  252160509   63448733   74.67       17.74
5   2009  3314787        -275841  188711776 -153200712   56.93      -38.29
6   2008  3590628         -99940  341912488  104700835   95.22       30.95
7   2007  3690568         -43658  237211653   20584322   64.28        6.26
8   2006  3734226         -20445  216627331   40871990   58.01       11.20
9   2005  3754671         -66308  175755341   44012676   46.81       12.33
10  2004  3820979         144974  131742665   32575492   34.48        7.50
11  2003  3676005         257983   99167173   21883842   26.98        4.37
12  2002  3418022         -53045   77283331    2990437   22.61        1.21
13  2001  3471067          71827   74292894  -15583539   21.40       -5.04
14  2000  3399240         171148   89876433   38986812   26.44       10.68
15  1999  3228092         -14620   50889621   13637399   15.76        4.28
16  1998  3242712         173281   37252222  -16973685   11.49       -6.18
17  1997  3069431         175785   54225907    -704950   17.67       -1.32
18  1996  2893646         126333   54930857   11181204   18.98        3.17
19  1995  2767313          63116   43749653    5270236   15.81        1.58
20  1994  2704197         160822   38479417      10041   14.23       -0.90
21  1993  2543375         248805   38469376     -83679   15.13       -1.68

Input:

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[df['Price'].mean(), df['Price'].min(), df['Price'].max()]

Output:

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[46.63681818181818, 11.49, 101.11]

Problem 2

  • suppose we want to convert between C(Celsius) and F(Fahrenheit), using the equation 9C = 5 (F-32)
  • could write functions c2f and f2c
  • do all computation in floating point for this problem

Input:

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def c2f(c):
  return((9. * c + 5. * 32.) / 5.)
def f2c(f):
  return(5. * (f - 32) / 9.)
[c2f(0), c2f(100), f2c(32), f2c(212)]

Output:

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[32.0, 212.0, 0.0, 100.0]

  • to write f2c, we solved the equation for C, and made a function out of the other side of the equation
  • to write c2f, we solved for F, . . .
  • there is another way to think about this
  • rearrange the equation into a symmetric form 9 * C - 5 * F = -32 * 5
  • you can think of the equation above as a constraint between F and C. if you specify one variable, the others value is determined by the equation. in general, if we have c0 * x0 + c1 * x1 + cN * xN = total
  • cI are fixed coefficients
  • specifying any N of the (N + 1) xs will determine the remaining x variable
  • define a class, Constaint that will do constraint satisfaction
  • you may find dotnone to be helpful

Input:

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# regular dot product, except that if or both values in a pair is 'None',
# that term is defined to contribute 0 to the sum
def dotnone(l1, l2):
  '''another dot product variant'''
  sum = 0
  for e1,e2 in zip(l1,l2):
    if not (e1 is None or e2 is None):
      sum += e1 * e2
  return(sum)
[dotnone([1,2,3], [4,5,6]), dotnone([1,None,3], [4,5,6]), dotnone([None,1], [2,None])]

Output:

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[32, 22, 0]

Input:

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# setup constraint btw C and F
# 1st arg is var names,
# 2nd arg is coefficients
# 3rd arg is total
c = Constraint('C F', [9, -5], -5 * 32)
# 1st arg - variable index or name
# 2nd arg - variable value
# setvar will fire when there is only one unset variable remaining
# it will print the variable values, return them in a list, and
# clear all variable values
c.setvar(0, 100)
C = 100.0
F = 212.0

Output:

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[100.0, 212.0]

Problem 3 - Hamlet

  • Python is very popular in digital humanities
  • MIT has the complete works of Shakespeare in a simple html format
  • You will do a simple analysis of Hamlet by reading the html file, one line at a time(usual iteration scheme) and doing pattern matching
  • The goal is to return a list of the linecnt, total number of speeches(look at the file format), and a dict showing the number of speeches each character gives
  • Your program should read directly from the url given, but you may want to download a copy to examine the structure of the file.
  • remember that usrlib.request returns byte arrays, not strings
  • heres a short sample of the file
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<A NAME=speech25><b>HORATIO</b></a>
<blockquote>
<A NAME=1.1.37>Tush, tush, 'twill not appear.</A><br>
</blockquote>

<A NAME=speech26><b>BERNARDO</b></a>
<blockquote>
<A NAME=1.1.38>Sit down awhile;</A><br>
<A NAME=1.1.39>And let us once again assail your ears,</A><br>
<A NAME=1.1.40>That are so fortified against our story</A><br>
<A NAME=1.1.41>What we have two nights seen.</A><br>
</blockquote>

<A NAME=speech27><b>HORATIO</b></a>
<blockquote>
<A NAME=1.1.42>Well, sit we down,</A><br>
<A NAME=1.1.43>And let us hear Bernardo speak of this.</A><br>
</blockquote>

<A NAME=speech28><b>BERNARDO</b></a>
<blockquote>
<A NAME=1.1.44>Last night of all,</A><br>
<A NAME=1.1.45>When yond same star that's westward from the pole</A><br>
<A NAME=1.1.46>Had made his course to illume that part of heaven</A><br>
<A NAME=1.1.47>Where now it burns, Marcellus and myself,</A><br>
<A NAME=1.1.48>The bell then beating one,--</A><br>
<p><i>Enter Ghost</i></p>
</blockquote>

<A NAME=speech29><b>MARCELLUS</b></a>
<blockquote>
<A NAME=1.1.49>Peace, break thee off; look, where it comes again!</A><br>
</blockquote>

<A NAME=speech30><b>BERNARDO</b></a>
<blockquote>
<A NAME=1.1.50>In the same figure, like the king that's dead.</A><br>
</blockquote>

Input:

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hamlet(url)

Output:

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[8881,
 1150,
 defaultdict(int,
            {'All': 4,
             'BERNARDO': 23,
             'CORNELIUS': 1,
             'Captain': 7,
             'Danes': 3,
             'FRANCISCO': 8,
             'First Ambassador': 1,
             'First Clown': 33,
             'First Player': 8,
             'First Priest': 2,
             'First Sailor': 2,
             'GUILDENSTERN': 33,
             'Gentleman': 3,
             'Ghost': 14,
             'HAMLET': 359,
             'HORATIO': 112,
             'KING CLAUDIUS': 102,
             'LAERTES': 62,
             'LORD POLONIUS': 86,
             'LUCIANUS': 1,
             'Lord': 3,
             'MARCELLUS': 36,
             'Messenger': 2,
             'OPHELIA': 58,
             'OSRIC': 25,
             'PRINCE FORTINBRAS': 6,
             'Player King': 4,
             'Player Queen': 5,
             'Prologue': 1,
             'QUEEN GERTRUDE': 69,
             'REYNALDO': 13,
             'ROSENCRANTZ': 49,
             'Second Clown': 12,
             'Servant': 1,
             'VOLTIMAND': 2})]

Problem 4

  • in class, we discussed two different ways to represent a polynomial
    • polylist, a dense represenation, that hold the coefficients in a list
    • polydict, a sparse representation, that holds (exponent, coefficent) pairs in a dict
  • add a method, topolydict() to class polylist, that converts the polylist into a polydict
  • add a method, topolylist() to class polydict, that converts the polydict into a polylist
  • note that polylist->polydict will always work, but polydict->polylist can fail, because a polylist cannot represent negative exponents. in this case, raise a ValueError
  • just to tell them apart, polylist prints with a leading +

Input:

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pl1 = polylist([1, 2, 3])
pl2 = polylist([0, 10, 5])
pd1 = polydict({2:3, 1:2, 0:1})
pd2 = polydict({1:10, 2:5})
pd3 = polydict({-1:10, 2:5})
[pl1, pl2, pd1, pd2, pd3]

Output:

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[+ 3 * X ** 2 + 2 * X + 1,
 + 5 * X ** 2 + 10 * x,
 3 * X ** 2 + 2 * X + 1,
 5 * X ** 2 + 10 * X,
 5 * X ** 2 + 10 * X ** -1]

Input:

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[pl1.topolydict(), pl2.topolydict(), pd1.topolylist(), pd2.topolylist()]

Output:

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[3 * X ** 2 + 2 * X + 1, 5 * X ** 2 + 10 * X, + 3 * X ** 2 + 2 * X + 1, + 5 * X ** 2 + 10 * X]

Problem 5

define the __mul__ method for polydict
Input:

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[pd1, pd2, pd3, pd1 * pd2, pd1 * pd3, pd2 * pd3]

Output:

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[+ 3 * X ** 2 + 2 * X + 1,
 + 5 * X ** 2 + 10 * x,
 3 * X ** 2 + 2 * X + 1,
 5 * X ** 2 + 10 * X,
 5 * X ** 2 + 10 * X ** -1,
 15 * X ** 4 + 40 * X ** 3 + 25 * X ** 2 + 10 * X,
 15 * X ** 4 + 10 * X ** 3 + 5 * X ** 2 + 30 * X + 20 * X ** -1,
 25 * X ** 4 + 50 * X ** 3 + 50 * X + 100]

]]>
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