1 00:00:04,390 --> 00:00:09,910 This video, we're going to talk about data types and operations in Python to get you started,
2 00:00:09,910 --> 00:00:13,320 more on being able to write some of your own Python code,
3 00:00:13,320 --> 00:00:18,430 are learning outcomes for this video or for you to understand basic python data types of operations,
4 00:00:18,430 --> 00:00:24,880 to be able to work with python variables, storing objects in them, to write some simple python code,
5 00:00:24,880 --> 00:00:31,210 to do arithmetic and perform basic operations with lists and dictionaries. Also, this slide deck is a notebook.
6 00:00:31,210 --> 00:00:38,200 And so rather than the little embedded slides widget like we have for a lot of the videos, for this one, there will be a link to the notebooks.
7 00:00:38,200 --> 00:00:40,810 You can download it and run the code yourself.
8 00:00:40,810 --> 00:00:46,480 There's also going to be more resources linked in the class notes that I'll talk about briefly at the end of this video.
9 00:00:46,480 --> 00:00:51,760 Python supports couple primary types of numbers. First, we can write integers just by writing the number.
10 00:00:51,760 --> 00:00:56,860 There's no decimal point in there. And if we run, that is just a it's a python line.
11 00:00:56,860 --> 00:01:02,590 So a python line is called a statement. A statement can have something like an F or something like that.
12 00:01:02,590 --> 00:01:10,990 Or it can just be what we call an expression. And an expression is a set of operations that results in a value.
13 00:01:10,990 --> 00:01:16,420 And so a number just writing the number itself is an expression. So we can we can write an integer.
14 00:01:16,420 --> 00:01:21,340 We can write a floating point number with a decimal point. These are stored in floating point format.
15 00:01:21,340 --> 00:01:27,250 There are a couple of nuances about that. We'll talk about when we talk more in detail about different types of data.
16 00:01:27,250 --> 00:01:30,490 We can also use scientific notation with the E notations,
17 00:01:30,490 --> 00:01:41,840 the six point O to each of the twenty three Avogadro's number a mole and we write E twenty three and that means times ten to twenty third power.
18 00:01:41,840 --> 00:01:53,000 So we can also do arithmetic on these numbers, so the usual arithmetic operations, addition, subtraction, etc., they work as we would expect.
19 00:01:53,000 --> 00:01:54,570 They were just like they do.
20 00:01:54,570 --> 00:02:00,770 And when you're writing them in math, when they work in other programing languages, we can add five in to order of operation disrespected.
21 00:02:00,770 --> 00:02:04,820 So three times six at plus two.
22 00:02:04,820 --> 00:02:13,250 We can also then use parentheses to change the groupings so we can add two and three before multiplying by six.
23 00:02:13,250 --> 00:02:17,300 It works like you would expect from almost any other programing language.
24 00:02:17,300 --> 00:02:23,420 No surprises here if you're familiar with Java or Perl or something else.
25 00:02:23,420 --> 00:02:25,850 Those are our basic arithmetic operations.
26 00:02:25,850 --> 00:02:32,480 If we want to raise something to a power, the star star operator is what Python uses to raise something to a power.
27 00:02:32,480 --> 00:02:35,990 So two to the fifth power is two star star five.
28 00:02:35,990 --> 00:02:43,610 We can also get a number of other mathematical operations from two different python modules math and num pi num.
29 00:02:43,610 --> 00:02:48,230 Pi has duplicates of most of the math ones, so I usually just work with num pi.
30 00:02:48,230 --> 00:02:56,240 You have to import a module before you can use its function. So I'm going to import the num pi module here and I want to give it a shorter alias enpi.
31 00:02:56,240 --> 00:03:01,670 This is very common in Jupiter notebook's that we that we import num pi S&P so then
32 00:03:01,670 --> 00:03:09,020 we can just write n.p. dot log to compute the natural logarithm of the number twenty.
33 00:03:09,020 --> 00:03:12,320 We can also store values in variables.
34 00:03:12,320 --> 00:03:20,810 Let's just give them a name so X equals seven stores, the value seven in the variable X, there is no declaration necessary, unlike an JARBOE.
35 00:03:20,810 --> 00:03:24,230 Just assign the value to a variable. Then we can use it.
36 00:03:24,230 --> 00:03:31,130 So X is plus five is going to return a 12 because X currently stores the value seven.
37 00:03:31,130 --> 00:03:35,670 Now if we change the variable, so we say X equals two.
38 00:03:35,670 --> 00:03:43,510 OK. It's changed the variable. Python. So the variables are all stored in a commons memory space.
39 00:03:43,510 --> 00:03:47,650 And the Jupiter notebook runs the cells in the order we ran them.
40 00:03:47,650 --> 00:03:59,150 And it shows us here that number. But in in. Is the order in which that cell was run nine, 10, 11, if we so we've changed the value of of X here.
41 00:03:59,150 --> 00:04:05,240 If we go back up and rerun this cell, it's going to use the new value of X.
42 00:04:05,240 --> 00:04:11,720 This is important to keep in mind, and it's an easy way to get your notebook very confused if you've been running cells out of order.
43 00:04:11,720 --> 00:04:17,750 When we're developing a notebook we're working on, a data analysis will often run things out of order, try things out.
44 00:04:17,750 --> 00:04:28,520 But it's important to keep things clear and consistent in your notebook so that if you were to rerun the notebook from top to bottom,
45 00:04:28,520 --> 00:04:33,050 it runs and produces the correct results. You can do experiments, but before you go,
46 00:04:33,050 --> 00:04:44,150 say to submit your notebook to me in an assignment or before you go to to submit it to your client or use it for your final analysis.
47 00:04:44,150 --> 00:04:46,880 Make sure that if you rerun it from top to bottom,
48 00:04:46,880 --> 00:04:51,410 you get the right results so that you can be confident that you're actually computing the results you want.
49 00:04:51,410 --> 00:04:56,840 And there's not something that's just an artifact of the order in which you happened to run the cells.
50 00:04:56,840 --> 00:05:02,900 So we've seen numbers do seem variables that we can also write strings.
51 00:05:02,900 --> 00:05:06,500 We can put them in quotes. Python takes both double and single quotes.
52 00:05:06,500 --> 00:05:10,660 There's no difference between them. The backslash is an escape character.
53 00:05:10,660 --> 00:05:20,740 So if we want to have double quotes and a double coded string, we can we can do that with by by prefixing them with a backslash.
54 00:05:20,740 --> 00:05:25,870 We can one of the fundamental string operations is to contaminate two strings, and if you have strings,
55 00:05:25,870 --> 00:05:32,130 the plus operator, it's the same operator we use for additions and with numbers, it can cat Nates the two strings.
56 00:05:32,130 --> 00:05:37,120 So hello. Plus world is Hello World. There's a bunch of other operations.
57 00:05:37,120 --> 00:05:41,080 For example, split separates a string into a list by default.
58 00:05:41,080 --> 00:05:45,550 If you don't tell it how to split it, it uses whitespace. So this is going to split the string.
59 00:05:45,550 --> 00:05:49,330 Hello Space World into a list of two items.
60 00:05:49,330 --> 00:05:57,710 Hello and world. So Python is strict about types, every object, every value has a type.
61 00:05:57,710 --> 00:06:07,640 And it won't auto convert them. So if you've programed in Perl or JavaScript or P HP and you take a string and a number and you can cabinet them,
62 00:06:07,640 --> 00:06:11,630 it tries to convert the number to a string. Python won't do that.
63 00:06:11,630 --> 00:06:19,670 So if we do this, we try to add a number to a string. It's going to give us a type error and a type error and tells us what's going on.
64 00:06:19,670 --> 00:06:24,890 One of the skills you're going to need to develop in this class is the ability to read error messages.
65 00:06:24,890 --> 00:06:30,830 And this error message tells us a cup, a few important things. It tells us that the error is a type error.
66 00:06:30,830 --> 00:06:36,100 Other errors you're going to see are value errors, index errors, key errors, et cetera.
67 00:06:36,100 --> 00:06:42,570 But this is telling us a type error, which means that we're trying to do something with the wrong type of data.
68 00:06:42,570 --> 00:06:46,470 It then tells us two other things. It gives us this trace back of the code.
69 00:06:46,470 --> 00:06:53,730 So it shows us where in the code it went wrong. The only thing we're doing here, we're not calling in many library functions or anything like that.
70 00:06:53,730 --> 00:07:01,620 We're just trying to add a string in a number. We have our line of code. So it's showing us that it happened on line one, Maroon plus five,
71 00:07:01,620 --> 00:07:07,890 and then it tells us a little bit more about the error can only concatenate stir, not end to stir.
72 00:07:07,890 --> 00:07:12,720 So what this is telling us is that and Cat Nation only works on strings.
73 00:07:12,720 --> 00:07:18,670 You can't concatenate things that aren't strings to a string.
74 00:07:18,670 --> 00:07:21,890 And what we have here, we have a string and we have a number.
75 00:07:21,890 --> 00:07:33,170 So if we want to if we want to to put five at the end of our our string, we can convert it with the Sturr function.
76 00:07:33,170 --> 00:07:40,580 So Sturr is a function that takes an object and returns a string representation of that object intended for human consumption.
77 00:07:40,580 --> 00:07:48,580 So if we do this, then we get our strength, then that will concatenate correctly and we get the string Maroon five.
78 00:07:48,580 --> 00:07:55,480 So we've now seen three different kinds of operations that we can perform on python values.
79 00:07:55,480 --> 00:08:03,400 We've seen an operator like Plasty Duck, the binary operators that go between their two operands so we can say six plus seven.
80 00:08:03,400 --> 00:08:10,600 There's quite a few of these operators. We've seen a function which in this case, the function comes from a module.
81 00:08:10,600 --> 00:08:15,010 So ENPI dialog and a function takes a value in return some other values.
82 00:08:15,010 --> 00:08:21,370 We can compute the natural log of 10. And we've seen a method which is a function that's attached to an object.
83 00:08:21,370 --> 00:08:24,820 So speed up. So the log function isn't attached to any particular object.
84 00:08:24,820 --> 00:08:28,990 It's just a function hanging around. But the method. Hello.
85 00:08:28,990 --> 00:08:36,630 So split is going to work on the hello world. String and.
86 00:08:36,630 --> 00:08:48,290 And split it. So we've seen a method. If you're familiar with Java, they're like methods in Java and they operate on a particular.
87 00:08:48,290 --> 00:08:55,590 They operate on a particular object. The Java equivalent of a python function would be a static method.
88 00:08:55,590 --> 00:09:02,240 We've seen these three different kinds of operations in this class. We're going to learn how to write functions.
89 00:09:02,240 --> 00:09:07,880 Eventually, we're going to learn how to write our own methods. But we aren't going to need that for the vast majority of this class.
90 00:09:07,880 --> 00:09:14,150 You can also define how operators work on custom, on custom data types in Python.
91 00:09:14,150 --> 00:09:19,310 We're not going to do that. It's learning to do that is outside the scope of this class.
92 00:09:19,310 --> 00:09:25,520 But it is how some of the libraries that we're gonna be using work on the inside.
93 00:09:25,520 --> 00:09:29,570 So we've got these different kinds of operations. There's a few other things that we can do.
94 00:09:29,570 --> 00:09:35,840 So a few other data types you can work with. So now that split method, it returns a list.
95 00:09:35,840 --> 00:09:41,780 Hello, World. And in Python, we write lists with square brackets and commas separating the values and we can write them.
96 00:09:41,780 --> 00:09:46,870 So I can make a list that consists of these three values. Martin Cross and Grip's.
97 00:09:46,870 --> 00:09:50,530 I can also save a list of variables. Now I have the variable Rowdy three.
98 00:09:50,530 --> 00:09:55,420 That contains a list of these three names. We can then, though, add to the list.
99 00:09:55,420 --> 00:10:03,400 So if too rowdy three that append Vogul. And we're going to now have a list that contains Martin Cross scripts and vocal.
100 00:10:03,400 --> 00:10:09,790 Now, notice that in this code I did Rowdy three at a pen and then I just wrote Rowdy three.
101 00:10:09,790 --> 00:10:21,480 That's because if you remember from the previous video. Jupiter shows the value of the last expression in your cell.
102 00:10:21,480 --> 00:10:24,960 Rowdy three A doesn't return anything. The list append method.
103 00:10:24,960 --> 00:10:29,250 Add something to the end of a list and actually it modifies that particular list.
104 00:10:29,250 --> 00:10:36,130 We don't have a new list here. It modified our list object and and stuck Voegele at the end of it.
105 00:10:36,130 --> 00:10:37,890 And it doesn't return anything.
106 00:10:37,890 --> 00:10:45,600 So instead, what we're gonna do, what I often like to do when I do an operation like this is then at the end of the cell,
107 00:10:45,600 --> 00:10:51,150 I just put the variable that I've been modifying so that it'll then show me what's currently in the variable.
108 00:10:51,150 --> 00:11:02,190 So we can see that after we appended Voegele to the list stored in the variable Rowdy three, that list now consists of four items.
109 00:11:02,190 --> 00:11:09,010 And yet the list now consists of four items and includes our new entry at the end.
110 00:11:09,010 --> 00:11:13,960 So lists are indexed, starting with zero so rowdy, three of zero gives us Martin.
111 00:11:13,960 --> 00:11:21,820 We can index backwards from the end, rowdy three negative one gives us voegele a slice, takes multiple elements from a list.
112 00:11:21,820 --> 00:11:27,610 So rowdy three one Colen three gives us element the element that one and two.
113 00:11:27,610 --> 00:11:31,630 What it does is it gives you it starts at the first index of the slice and gives
114 00:11:31,630 --> 00:11:36,940 you all of the elements up to but not including the last element to the slice.
115 00:11:36,940 --> 00:11:42,130 So. Zero is the first item, one is the second item.
116 00:11:42,130 --> 00:11:46,120 So it's giving us items one and two and then three is one past the end.
117 00:11:46,120 --> 00:11:52,810 These kinds of half open intervals. We call this a half open interval because it includes the left side and not the right side.
118 00:11:52,810 --> 00:12:01,510 They're very, very common when we're using zero based indexing in a data structure because it's a very convenient way to express a range.
119 00:12:01,510 --> 00:12:08,240 Also, the length of the range is. The end, minus the beginning, three, minus one.
120 00:12:08,240 --> 00:12:17,920 It's going to give us a list of length to. One more thing we can do here is the land function.
121 00:12:17,920 --> 00:12:23,740 Is a standard python function that will give you the length of anything that has a length like a list.
122 00:12:23,740 --> 00:12:29,680 A number of other data structures have links. Most data structures that can contain other data structures will have a length.
123 00:12:29,680 --> 00:12:34,210 It will also work on a string. But the length of rowdy three is currently four.
124 00:12:34,210 --> 00:12:41,950 So we can also loop over a list. So this list, this loop here is going to loop for each person in the list.
125 00:12:41,950 --> 00:12:45,960 Stored and rowdy three. It's going to print the person. So we get our four people.
126 00:12:45,960 --> 00:12:52,530 Martin Cross scripts and vocal. What if we want to know the position of each item in the list as we go through the loop?
127 00:12:52,530 --> 00:13:02,910 The enumerate function wraps a list and returns the list, but also the position in the list as we go through the loop.
128 00:13:02,910 --> 00:13:07,530 And then this string here, this. That's prefixed with an F. We call this an F string.
129 00:13:07,530 --> 00:13:10,290 And when you put a F right before the opening quote of a string,
130 00:13:10,290 --> 00:13:15,810 you can then use squiggly braces and variable names to include variable values in the string.
131 00:13:15,810 --> 00:13:21,000 It's one of the ways that Python lets you easily build up strings that contain additional data.
132 00:13:21,000 --> 00:13:25,740 And so we're going to we're going to run this loop.
133 00:13:25,740 --> 00:13:31,500 And now we see each. Each person is now prefixed with their member number.
134 00:13:31,500 --> 00:13:35,490 And it's starting from zero because as we saw before, Python always starts from zero.
135 00:13:35,490 --> 00:13:43,700 So the first one is members zero. And this enumerate function is just giving us the positions along with each item.
136 00:13:43,700 --> 00:13:50,670 Python for loops operate over what what it calls iterable, something that iterable just feeds an object that you can use in a for loop.
137 00:13:50,670 --> 00:13:55,770 Lists are iterable, but if you want to loop over a sequence of numbers like you might in Java.
138 00:13:55,770 --> 00:14:00,780 So you want to go from zero one and two, you use a range.
139 00:14:00,780 --> 00:14:09,750 So this is going to print zero one and two, because, again, the python does not include upper bounds of ranges and slices by default.
140 00:14:09,750 --> 00:14:16,950 So we're going to go zero, one and two. So a tuple is another container.
141 00:14:16,950 --> 00:14:21,990 It's like a list, except its size can't be changed. It's used for representing things like pairs.
142 00:14:21,990 --> 00:14:28,470 So I'm going to create a variable called coords and I'm going to store the tuple three five in it coords.
143 00:14:28,470 --> 00:14:34,020 Sub-Zero, then, is the first element of the tuple three chords.
144 00:14:34,020 --> 00:14:46,170 One is five. If we did the Len of this tuple, we would we would get would get to a tuple can be unpacked by unpacking the tuple we take it.
145 00:14:46,170 --> 00:14:55,500 So this tuple has two elements and we can say X, comma, Y to unpack the tuple into two different variables and then X is going to be three.
146 00:14:55,500 --> 00:15:03,300 So the parentheses with the comma packs the tuple and assigning it to variable separated with a comma unpacks the tuple.
147 00:15:03,300 --> 00:15:11,670 The tuple size has to match. So if we say X, Y, Z of coords and try to run that, it's going to tell us not enough values to unpack.
148 00:15:11,670 --> 00:15:18,790 It expects three values X, Y and Z. But coords only has two values.
149 00:15:18,790 --> 00:15:25,960 A dictionary is another data structure that maps, keys, often strings, but not always you can.
150 00:15:25,960 --> 00:15:34,600 You can use numbers, tuples, any data structure that can't be changed, you can use as the key for a string or for a dictionary.
151 00:15:34,600 --> 00:15:38,710 And so we're going to map some different animals to what they eat here. We created a variable.
152 00:15:38,710 --> 00:15:44,590 Assigning to a variable doesn't return a value, so there's nothing to print here.
153 00:15:44,590 --> 00:15:49,690 And then we can look up a value by its key. So we say Dietze of rabbit equals plants.
154 00:15:49,690 --> 00:15:57,550 And that gives there like lists, except we can look them up by any key we want instead of having to look them up by a position.
155 00:15:57,550 --> 00:16:02,150 So everything in Python is an object which has a type. We saw this when we saw the type error.
156 00:16:02,150 --> 00:16:06,320 We try to to try to add the number five to the string maroon.
157 00:16:06,320 --> 00:16:11,950 The Sipes we've seen in this video are integers, strings, lists, tuples and dictionaries.
158 00:16:11,950 --> 00:16:13,570 There's a lot more to do with these.
159 00:16:13,570 --> 00:16:21,100 I refer to you to the readings and also we're going to be introducing a various features of them as we go throughout the class.
160 00:16:21,100 --> 00:16:27,100 Now, another thing that's important to understand is that in Python variables, store references to objects.
161 00:16:27,100 --> 00:16:31,210 This is how Java works as well. But this matters, particularly for mutable objects.
162 00:16:31,210 --> 00:16:42,100 So we have our list. Rowdy three. Now, if we assign the list to another variable, rowdy five and then we add Amanda and we print routing.
163 00:16:42,100 --> 00:16:47,980 We show the result of rowdy five. OK. We have our list. Now we've added Amanda to the end of it.
164 00:16:47,980 --> 00:16:52,660 The rowdy five and rowdy three variables are references to the same list objects.
165 00:16:52,660 --> 00:16:59,110 We only look at Rowdy three. It's now going to show five elements, including Amanda.
166 00:16:59,110 --> 00:17:05,050 Because when we assign the variable, it doesn't make a copy of the list.
167 00:17:05,050 --> 00:17:09,140 All it does is it creates another variable that also refers to the list, too.
168 00:17:09,140 --> 00:17:15,220 We modify this list, object and append modifies the object, what we call in place.
169 00:17:15,220 --> 00:17:21,050 That means it modifies the object itself. It does not return a new object.
170 00:17:21,050 --> 00:17:30,200 It the object changes and any variable that's referring to that object gets the change of this in-place
171 00:17:30,200 --> 00:17:34,700 distinction is going to be important throughout the semester because some of the libraries we use,
172 00:17:34,700 --> 00:17:46,350 they they offer options to whether you want to modify something in place or whether you want to return a new object that has the new data.
173 00:17:46,350 --> 00:17:50,010 So there's a variety of ways. Resources to learn Python.
174 00:17:50,010 --> 00:17:57,270 I'm going to be making some videos, but we're not going to have time in the videos to go into every piece of python you might need.
175 00:17:57,270 --> 00:18:04,300 The tech chapters two, and I'm going to be writing some resources, chapters two and three in the text book are going to.
176 00:18:04,300 --> 00:18:10,380 They talk about basic python operations and data structures. There's the Python tutorial that I'm providing you a link to.
177 00:18:10,380 --> 00:18:16,920 That's a relatively comprehensive tutorial from the Python developers about the key Python language features.
178 00:18:16,920 --> 00:18:22,740 If you really want to dove in depth, there's a book, Learn Python the Hard Way, which is quite comprehensive.
179 00:18:22,740 --> 00:18:30,510 I'm also going to be providing in the resources section of the class site some additional notebook's that walk
180 00:18:30,510 --> 00:18:36,600 through and demonstrate different Python features and give you information about the different operations.
181 00:18:36,600 --> 00:18:42,240 For example, I'm planning on one such notebook that goes over a bunch of different things you
182 00:18:42,240 --> 00:18:48,540 can do with lists more than I've had a chance to get into in in this video.
183 00:18:48,540 --> 00:18:55,680 So to wrap up, Python supports many different data types. Everything's that object and variable store references to objects.
184 00:18:55,680 --> 00:19:03,180 If you do an operation that modifies an object, all variables that refer to the same object are going to get are going to see the change.
185 00:19:03,180 --> 00:19:07,920 You can perform a number of standard arithmetic operations on python variables.
186 00:19:07,920 --> 00:19:17,333 And there's many, many more operations that we're going to be seeing as we go throughout the semester.