#python2
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# coding=utf-8 # 讓python轉型成utf-8，支援中文 # Set應用，查詢快、不重複 print "---Set應用---" s = set() s.add(1) s.add(2) s.add(2) x = len(s) y = 2 in s z = 3 in s print "x = " + str(x) # 2 print "y = " + str(y) # True print "z = " + str(z) # False |
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stopwords_list = ["a","an","at"] + ["yet", "you"] + ["yet", "you"] # list 可用來比對每一個值 print "zip in stopwords_list = "+str(zip in stopwords_list) stopwords_set = set(stopwords_list) # Set 速度較快，若要測驗裡面有沒有，用set比較快 print "zip in stopwords_set = "+str(zip in stopwords_set) |
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print "---list與Set個數不同---" item_list = [1, 2, 3, 1, 2, 3] num_items = len(item_list) # 6 item_set = set(item_list) # {1, 2, 3} num_distinct_items = len(item_set) # 3 distinct_item_list = list(item_set) # [1, 2, 3] print "num_items = "+str(num_items) # 用list個數為6個 print "item_set = "+str(item_set) print "num_distinct_items = " + str(num_distinct_items) # Set個數為3個，因為set不重復 print "distinct_item_list = " + str(distinct_item_list) |
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# Control Flow print "---判斷機偶數，if寫法---" x=2 parity = "even" if x % 2 == 0 else "odd" print "x =" +str(x)+", and parity = "+parity |
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# while。倘若說網路連線、email等等，建議不要用，會占用CPU # 假如跑資料迴圈可以，因為會在記憶體中執行 print "---while迴圈---" x = 0 while x < 10: print x, "is less than 10" x += 1 |
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print "---for迴圈---" for x in range(10): print x, "is less than 10" |
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# sorted 或 sort基本上依樣，但sorted(x) x內容不會改變，x.sort()才會改變 print "---sorted排序---" x = [4,1,2,3] print x y = sorted(x) # is [1,2,3,4], x is unchanged x.sort() # now x is [1,2,3,4] print y |
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# list應用 print "---list應用---" even_numbers = [x for x in range(5) if x % 2 == 0] # [0, 2, 4] squares = [x * x for x in range(5)] # [0, 1, 4, 9, 16] even_squares = [x * x for x in even_numbers] # [0, 4, 16] print even_numbers,",",squares,",",even_squares |
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square_dict = { x : x * x for x in range(5) } # { 0:0, 1:1, 2:4, 3:9, 4:16 } square_set = { x * x for x in [1, -1] } # { 1 } print square_dict,",",square_set |
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# Generators 產生器 print "---Generators and Iterators---" import time def lazy_range(n): i = 0 while i < n: time.sleep(i/2) yield i i += 1 for i in lazy_range(10): print (i) |
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# 亂數應用 print "---random亂數---" import random four_uniform_randoms = [random.random() for _ in range(4)] print four_uniform_randoms |
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# 用日期給予seed值，讓亂數每次跑的都不一樣 print "---亂數seed種子---" import datetime random.seed(datetime.datetime.now()) print random.random() random.seed(10) print random.random() |
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# 用randrange固定亂數的範圍 print "---randrange固定亂數---" print random.randrange(10) |
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# 用shuffle讓他跑出不重複的亂數值 print "---shuffle不重複的亂數值---" up_to_ten = range(5,11) random.shuffle(up_to_ten) print up_to_ten |
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print "---choice---" my_lunch = random.choice(["7-11","KFC","Macdonald"]) print my_lunch |
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print "---rand取多個---" lottery_numbers = range(60) winning_numbers = random.sample(lottery_numbers, 6) print winning_numbers |
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print "---取多個，但會重複---" four_with_replacement = [random.choice(range(10)) for _ in range(4)] print four_with_replacement |
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print "---Regular Expressions正規表達式---" import re print all([ # all of these are true, because not re.match("a", "cat"), # * 'cat' doesn't start with 'a' re.search("a", "cat"), # * 'cat' has an 'a' in it not re.search("c", "dog"), # * 'dog' doesn't have a 'c' in it 3 == len(re.split("[ab]", "carbs")), # a,b做切割['c','r','s'] "R-D-" == re.sub("[0-9]", "*", "R2D2") # 做取代 ]) # prints True |
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print "---Line Chart---" from matplotlib import pyplot as plt years = [1950, 1960, 1970, 1980, 1990, 2000, 2010] gdp = [300.2, 543.3, 1075.9, 2862.5, 5979.6, 10289.7, 14958.3] # create a line chart, years on x-axis, gdp on y-axis plt.plot(years, gdp, color='green', marker='o', linestyle='solid') # add a title plt.title("Nominal GDP") # add a label to the y-axis plt.ylabel("Billions of $") plt.show() |
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print "---Bar Chart---" movies = ["Annie Hall", "Ben-Hur", "Casablanca", "Gandhi", "West Side Story"] num_oscars = [5, 11, 3, 8, 10] # bars are by default width 0.8, so we'll add 0.1 to the left coordinates # so that each bar is centered xs = [i + 0.1 for i, _ in enumerate(movies)] # plot bars with left x-coordinates [xs], heights [num_oscars] plt.bar(xs, num_oscars) plt.ylabel("# of Academy Awards") plt.title("My Favorite Movies") # label x-axis with movie names at bar centers plt.xticks([i + 0.5 for i, _ in enumerate(movies)], movies) plt.show() |
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print "---Bar Chart---" from collections import Counter grades = [83,95,91,87,70,0,85,82,100,67,73,77,0] decile = lambda grade: grade // 10 * 10 histogram = Counter(decile(grade) for grade in grades) plt.bar([x for x in histogram.keys()], # shift each bar to the left by 4 histogram.values(), # give each bar its correct height 8) # give each bar a width of 8 plt.axis([-5, 105, 0, 5]) # x-axis from -5 to 105, # y-axis from 0 to 5 plt.xticks([10 * i for i in range(11)]) # x-axis labels at 0, 10, ..., 100 plt.xlabel("Decile") plt.ylabel("# of Students") plt.title("Distribution of Exam 1 Grades") plt.show() |
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print "---Bar Chart---" mentions = [500, 505] years = [2013, 2014] plt.bar(years, mentions, 0.8) plt.xticks(years) plt.ylabel("# of times I heard someone say 'data science'") # if you don't do this, matplotlib will label the x-axis 0, 1 # and then add a +2.013e3 off in the corner (bad matplotlib!) plt.ticklabel_format(useOffset=False) # misleading y-axis only shows the part above 500 plt.axis([2012.5,2014.5,499,506]) # 刻度要設小一點才看得比較明顯 plt.title("Look at the 'Huge' Increase!") plt.show() |
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print "---Line Chart---" variance = [1, 2, 4, 8, 16, 32, 64, 128, 256] bias_squared = [256, 128, 64, 32, 16, 8, 4, 2, 1] total_error = [x + y for x, y in zip(variance, bias_squared)] xs = [i for i, _ in enumerate(variance)] # we can make multiple calls to plt.plot # to show multiple series on the same chart plt.plot(xs, variance, 'g-', label='variance') # green solid line plt.plot(xs, bias_squared, 'r-.', label='bias^2') # red dot-dashed line plt.plot(xs, total_error, 'b:', label='total error') # blue dotted line # because we've assigned labels to each series # we can get a legend for free # loc=9 means "top center" plt.legend(loc=9) plt.xlabel("model complexity") plt.title("The Bias-Variance Tradeoff") plt.show() |
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print "---Scatterplots散點圖---" friends = [ 70, 65, 72, 63, 71, 64, 60, 64, 67] minutes = [175, 170, 205, 120, 220, 130, 105, 145, 190] labels = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i'] plt.scatter(friends, minutes) # label each point for label, friend_count, minute_count in zip(labels, friends, minutes): plt.annotate(label, xy=(friend_count, minute_count), # put the label with its point xytext=(5, -5), # but slightly offset textcoords='offset points') plt.title("Daily Minutes vs. Number of Friends") plt.xlabel("# of friends") plt.ylabel("daily minutes spent on the site") #plt.axis('equal') # 轉橫式 plt.show() |
備註：2017/03/16 計算方法分析與設計-課程筆記