How to Graph Data in Python Using the Matplotlib Module!

what's up you guys welcome back to the channel in today's video I'm gonna show you how to create three of the most common most basic types of plot using the matplot lib module in Python we're going to cover how to do a basic plot a scatter plot and a bar graph using matplotlib and some numpy [Music] alright so let's jump right into it um python is an extremely useful programming tool for data analysis you've almost certainly heard that if you're a beginner or intermediate python programmer and two of the most common tools that you will use in Python for data analysis are numpy which is essentially a python numerical computation module that a lot of the other modules build off of including matplotlib which is a really useful mathematical tool for plotting uh different data sets so these are both really useful to know if if you want to get into python for data analysis so let's just start by importing matplotlib dot Pi plot which is going to be the piece that we are actually going to use as our plot for all three of the types of graphs that we're going to cover in here today and we also want to import numpy and you'll most commonly see this abbreviated just as NP it's a really easy way to use the numpy module without typing out numpy but you absolutely could type out numpy if you wanted okay and so real quick you don't have to worry too much about what this means but we are going to use a specific style of plot just a underscore MPL Dash Gallery okay so uh this is kind of one of just a basic command if you really want to look into the different styles that you can use matplotlibs documentation is pretty good online so feel free to look it up if you want to use other styles and then the actual plot has this thing called subplots that has uh its figure size and definition in this first variable and then it stores its axes in a second variable and so again I I'm gonna try to get through three different types of plot and I can maybe do a longer video on a deep dive into matplotlib in the future but basically we want to get this plot dot subplots right here in the beginning because we're going to use this to uh tell our plot later on in our program what the different axes are going to look like so what our X and Y data are going to be made up of and to do that we want to break plot dot subplots into this fig and ax sub parameter okay so these variables and now let's start our basic plot section okay so the code we need just to make our basic plot and I will also throw in here that at the very end you don't want to forget this step or you'll think that your code is not working you always want to make sure you have plot.show at the end because that is what is actually going to display your graph onto the screen but now I don't have specific data prepared for this for this tutorial so let's go ahead and make a set of data that are just going to be a sine wave all right and to to do that I'm going to use the numpy linear spacing so Lin space to basically give me data from 0 to 10 and then I'm going to say how many points I want in between those okay so this is essentially saying give me 100 evenly spaced points between 0 to 10. all right so that is what my X data is going to be and now I'm going to use uh that same set of data to give me a sine wave by just saying y equals and then NP DOT sign and then times x this would sort of be how I would get a generic sine wave now let's go ahead and increase its frequency and amplitude just so it's a little bit more interesting in the span we just defined and so I'm just going to add in some variables like four plus so you should know a normal sine wave will go from 1 to negative one and now we're just increasing the speed which it oscillates here and then we are going to say that actually ours is going to go from seven to one so it's gonna four is going to replace 0 as kind of our uh y you know zero point and then we can go up three or down three so it's just a more interesting um uh set of data so that you can see this but so basically this is y sine wave from one to seven um and then that'll be our data and so what we want to do to use this data is we say that X that axes variable that we already made Dot Plot and then we give it our X set of data our y set of data and then an optional variable because by default it'll give you just one but an optional variable is also to increase the line width so I'm going to go with a line width of 2. and that's actually all the setup that we have to do now we just have to essentially tell the axes set the axes with how to display and then it'll be ready to go so we do that in x dot set and then we are going to say what we want the X limits of our uh graph to be and I want mine to be between 0 and 8. so um I just basically know that I'm going from 0 to 10 and so I'm going to say the range that I want to display is from 0 to 8. these are the X Min and Max limits and then uh just another again this one's optional but the number of ticks that you want to have show up are going to be a range between one and eight okay so uh I'm gonna copy this whole ax dot set in innards so this chunk and I'm just gonna copy and then put on a second row the same thing but for the Y limit and the Y ticks okay so basically I'm making a square here that's going to show me zero to eight in the X and the y direction and give me a tick on my axes every one so one two three four five six seven eight okay and this is actually it this like 18 rungs in most of it is spaces this is pretty much all we need for a basic plot in numpy so let's go ahead and run this and you can see that we get a sine wave and if you hover your mouse over it you can see that the low Point here for the Y's is one and the high point is seven and that the right edge of the graph goes up to eight so you could say you could set your X limit a little bit higher like we could set it to 10 and rerun it and what you'll see now is that you go all the way up to 10. so feel free to read the documentation on matplotlib and start looking at all of the optional parameters four basic plots and every other type of plot we cover here but for now I'm going to comment out the stuff that is just for the basic plot and we're going to move on to a scatter plot I don't want this uh lesson to get super duper long um just in case what you guys are really looking for is a crash course in the three most common in my opinion most common types of plots with matplotlib so let's take a look at a basic scatter plot okay and so to do this you may have noticed that I I commented out the section that was specific to basic plots but I'm actually leaving these last two commands the ax.set plot dot show and my initial setup in here and that's because the code that I didn't just comment out is much more generic and you can use it for all these different styles of plot it's this section in here where you're telling it what kind of plot to use so let's go ahead and take a look at what needs to change for a scatter plot and so let's start by getting some new data um I think first let's get some randomized X and Y data that's kind of the most interesting scatter plot anyways so we'll use a normal random distribution um for our uh X data and we'll just say um that we want it to be centered on zero and then we give it a scale and size of 2 and then 24. and then we'll go ahead and get Y randomized data as well that will be uh and I say centered on zero because we're adding 4 to it so really the values that you'll see are centered on 4 4 but our random data that we're grabbing is centered around zero plus or minus two so now we're going to do the same thing for y random normal and then zero two and then here uh one thing that's nice to make sure you get two lists of the same length is that you can use length of X instead of just 24 and this is just a smarter way of doing it because if you were to ever decide you wanted a larger or smaller sample size now they would grow together or Shrink together so that is a good idea to do and I'll just throw in here that the three variables we're giving it are the location which is also known as Center and then uh scale and then size and again numpy super common and well documented so I'm trying to cover a lot of content this video in a pretty short time frame if you have any specific questions feel free to drop them in the comments below now two things that we'll do to our scatter plot that make it a little bit more interesting is we'll do sizes and colors uh randomized as well so for our sizes list we'll go ahead and do NP dot random and then this one will do uniform instead um again feel free look up the difference but basically we're going to give it a low point a high point and then a total size and since we want uh all of our lists to have the same number of points we're going to use length of X again for sizes and we'll do something very similar for our colors list NP dot random dot uniform and we'll go from 15 to 80 and we'll make it length of X okay so I think I have an extra set of parameters around that length of X I did yeah but now I don't um and so again just to reiterate the arguments that we're giving it here are low High and then size okay those are the three things that we put in those uh NP dot random dot uniform now let's actually create the plot and for this we need to give it the X and Y arrays of data and then the sizes and colors are optional but we made the list so we may as well use them and then the data range for color map is going to be something that we pass in as well because we are generating a color mapping with that colors list so for this it's x dot scatter instead of X Dot Plot and then it is going to be X data Y data and then you need to use S equals sizes and C equals colors and then the color mapping minimum and maximum so that is vmin zero in Vmax uh to a hundred so that's where this 15 to 80 comes into play we're saying all right our lightest color would be zero our darkest color would be a hundred so let's make all of our data somewhere in between like 15 and 80. so they'll all be pretty easy to uh see but also distributed all over the map okay so I know this has gotten a little bit trickier to read especially because I've commented out plot code there in the middle but hopefully you're taking away that this stuff here is scatter plot specific creating our X set of data our y set of data the data sizes and colors and then this x dot scatter plugging the information in there we can leave our x dot set as is and our plot.show as is let's run it now and take a look at what we get okay and so hopefully you can see we get this interesting uh distribution of points it actually looks very spread out when I make it full screen um but you can see on here they're varying in colors and sizes because of that randomizer function that we set up um but they're all over the map and uh if you don't believe that it's random you can just run it again and you'll get a totally different graph the second time okay so that obviously looks a lot different than the second one um now that is all I'm gonna say about scattered plots for now again leave comments uh below if you have them I'm sure there are things that you might wonder about that we haven't covered in here but let's take a look at the third and final for this tutorial which we're gonna do is the bar graph so start the bar graph section okay and so first let's go ahead and make the data again and I'm just gonna say uh let's make this X from a half and then plus numpy dot arrange uh range a range of eight okay so it's just gonna give us a nice ordered list going up from 0.5 now let's make our Y data random and then we'll use that uniform again excuse me and we'll do two seven and length of X just again to make sure that we are getting um two lists of the same size so uh let's just make it clear here that what we did in here was um low high and then total size so our values should be between two and seven we're going to have a bar for each of them of uh of uh we're gonna have eight total bars is what I was trying to say poorly there and now let's go ahead and take a look at plot the bar graph so that's all we're going to do for the bar graph in terms of data is just to arrange our X data nice and orderly and then get some random y values um obviously I'm not pulling from real data sets here because I'm just showing you how to make the graphs if you have any questions how to apply your data set over top of it throw a comment down below and I'll get back to you as soon as I can all right but for a bar graph all we need are the X and Y arrays of data and then we'll establish an edge an edge color and a line width just to show you some of the stylistic things that you can do okay and so instead of x dot scatter or X Dot Plot we're going to go with x dot bar and then X and Y and then width of we'll just say one feel free to play around with that if you want the edge color I will make white and you'll see that when we boot it up and then the line width uh will be equal to one so width is how wide you actually want the bars to be and then line width is going to be how many pixels wide you want the edges around your bars to be okay so those are really the only things that you need to know I will say that Lim is the axis range to show and that ticks is where to start and how many to show I have that comment in my notes uh to put it down here but I guess I never threw it down so basically limit X Y Lim and xlim and ylim and I do think I talked about it just didn't leave a good comment is saying the range our axis is going to show and then ticks is uh is the range of of yeah ticks that we're going to show on The X and Y axis okay so let's boot this up and take a look at what we just created with a bar graph all right and so uh hopefully what you can see is we have eight total bars and the reason I guess I didn't touch on this but the reason we used X at 0.5 is because that is the center point of each bar so if we make them one wide centered on a half and then we do eight of them it's going to be centered on 0.5 1.5 2.5 3.5 but it's going to go half of a bar in each Direction so and then you can see our y values are random between uh two and seven so that seemed to work pretty good hopefully you understand how to basically replace my X and Y lists of just sort of quickly thrown together data with more useful data that applies to your situation um but so that is all I want to say about this super quick crash course in some of the most basic matplot lib graphs of course if you have any questions about what you saw in this video or would like to see some specific stuff on the channel in the future just let me know about in the comments below as always thank you guys so much for watching and until next time bye