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This python cheat sheet covers the basics of data types (integers, floats, strings), lists, and dictionaries, as well as control flow structures (if statements and for loops). Learn how to create, index, slice, and manipulate these data structures.
Typology: Schemes and Mind Maps
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by Elizabeth de Sa e Silva, Tamara Nelson-Fromm, Wade Fagen-Ulmschneider
Integers are whole numbers int1 = 8 int2 = - 5 int3 = 0 int4 = int(4.0) Floats have a decimal point float1 = 5.5 float2 = 0. float3 = 1e6 float4 = float(2) Strings A string literal has quotes: ‘CS101’, ‘CS107’, ‘5.67’ (it’s literally the exact characters of the string) A variable name does not: course_name, stat107, my_string A string can be indexed the same way as a list Example my_string = ‘literal’ #’literal’ is the literal print(‘my_string’) #prints “my_string” print(my_string) #prints “literal” print(literal) #ERROR
Strings, lists, and other iterable data types (data with many elements) can be indexed over a range of values, or sliced Replace any [i] with a range to select many elements at once: [start:stop:step] Selects position start through position stop, not including stop, but only elements step positions apart; start defaults to zero, so [ :10:7 ] starts at 0 stop defaults to one past the last index, so [ 10: :2 ] selects through the end of the data step defaults to one, so [ 1:5 ] steps by 1 (a negative step will count backwards) Examples my_string = ‘abcdefghijk’ my_string[2:4] == ‘cd’ my_string[:5] == ‘abcde’ my_string[5:] == ‘fghijk’ my_string[:] == ‘abcdefghijk’ my_string[2:8:2] == ‘ceg’ my_string[8:2:-2] == ‘ige’
Creating a new list empty_list = [] my_list =[1,2,3] Adding to a list (appending) list_name.append(v) #adds just the #element v to #list_name list_name += [v1,v2] #adds v1 and v #to the end of #list_name Indexing list[i] is equal to the element in list at zero-based index i Negative index values count from the end of the data list[-i] is equal to list[ len(list) - i ] Changing a list #changes the element list[i] = v #in list at position #i to the value v Example my_list = [1 0 ,2 0 ,3 0 ] #my_list is declared as [1 0 ,2 0 ,3 0 ] my_list.append(4 0 ) #my_list becomes [1 0 ,2 0 ,3 0 ,4 0 ] my_list += [50,60] #my_list becomes [1 0 ,2 0 ,3 0 ,4 0 ,50,60] my_list[2] == 3 0 # True my_list[4] = “fifty” #my_list becomes [1,2,3,4,”fifty”,60] my_list[-1] == “fifty” # True my_list[60] #ERROR
Booleans are True or False values x == y Is True if x is equal to y x in y is True if x is an element of y not x == y Is True is x is not equal to y And True and True = True True and False = False False and False = False Or True or True = True True or False = True False or False = False
Creating a new dictionary my_dict = {key1:value1, key2:value2, …, keyn:valuen} empty_dict = {} #keys and values can be any data type Adding to a dictionary (appending) dict_name[key] = value #adds key:value to dict_name Indexing dict[key] is equal to the value in dict with key key Changing a dictionary dict_name[key] = value #changes key’s value to v so dict_name
Getting Keys and Values dict_name.keys() #returns a list of keys in dict_name dict_name.values() #returns a list of values in dict_name Example my_dict = {‘a’:5, ‘b’: 6 } #my_dict is declared as {‘a’:5,’b’:6} my_dict[‘c’] = ‘ 4 ’ #my_dict becomes {‘a’:5, 6:’b’, ‘c’:’ 4 ’} my_dict[‘a’] == 5 # True my_dict[‘b’] = ‘a’ #my_dict becomes {‘a’:5,‘b’:’a’,‘c’:’4’} my_dict[5] #ERROR my_dict.keys() #equal to [‘a’, ‘b’, ‘c’]
if Indicates a block of code that only runs if its boolean condition is True elif Short for “else if”, this block is associated with an if block and has a condition; it only runs if its condition is true and the original if block condition was false else This block has no condition and runs only if the associated if statement and any of its elif blocks did not run Example if x < 5: #this indented code only runs if x is less than 5 elif x < 10: #this only runs if x is greater than 5 and less than 10 elif x == 13: #this only runs if x is equal to 13 else: #this only runs if x is greater than 10 and is not 13
for i in iterable: #code block to repeat Repeats a block of code for every element of an iterable data type Does not require you to advance the variable i Example : List list = [‘CS101’,‘CS 107 ’,‘ILL’] for item in list: #loops over every element #of list print(item) This code prints: CS CS ILL Example: Range for i in range(2, 8 ,2): #loops over every other #integer starting at 2 #and less than 8 print(i ** 2) This code prints: 4 16 36 range(start, stop, step) Generates a list of all integers from start to stop, jumping by step start The very first integer of the sequence. This defaults to 0 if not specified stop The boundary for the end of the sequence. This number is not included in the actual sequence of number. Has no default value and must always be specified. step The spacing between numbers included in the sequence. This defaults to 1
while this_is_true: #code block to repeat Repeats a block of code while some condition is true Often requires you to change the variables the condition relies on in the code block to get the loop to ever stop Example: Factorial #This code calculates 5! n = 5 result = 1 while n > 0: result = result * n n = n - 1 Example: Infinite Loop #This code runs forever n = 5 result = 1 while n > 0: result = result * n #leaving out n = n – 1 #makes this loop run #forever
Example: Sum Suppose I have a list of weights of some packages and I want to know how heavy it will be to carry all of them at once package_weights = [2, 6.5, 1, 10] total = 0 for weight in package_weights: total += weight print(total) #after this code runs the total weight is printed Example: Pandas Suppose I want to simulate flipping a coin 50 times and put the data into a dataframe data = [] for i in range(50): coin = randint(0,1) #simulate one coin flip as 0 or 1 d = {‘coin’ : coin} #create the row of data data.append(d) df = pandas.DataFrame(data) #creates a dataframe from data