Matplotlib is one of the most powerful Python libraries for data visualization. Whether you’re a beginner or an experienced coder, mastering Matplotlib will help you create stunning charts and graphs.
When you hit shift enter you will see that we have a nice flock right which is telling us that what was the price and in which year so now when we hit shift enter you will see that we have a real data from the yaho finance so this is how you can plot so for that what you will do you will write color is equals to green and when you shift enter you will see that the line for the open prices is now green but if you write here plot. Legend you will see that you have a legend here so it will show you that for the open it is the blue line and for the high it is the red line Hello friends welcome back to day 33 of the 100 days of hell with python Alo trading today we will be starting with the mat BL Li which is an important library for the visualization right so we have multiple libraries to visualize in Python but for now we’ll be covering only matlo lip and if required in the future we will cover the rest of the libraries like the caborn plotly and also this will be the last library before we start the core algo trading and actually.
I was in confusion that whether I should start the time series or the mat plot lip then I came to conclusion that let me first cover the matly and once it is covered then we are only left with the algo trading Concepts like the uh time series and rest of the things right so after that we’ll be done with the Python and the python libraries and like we have covered most of the things for now and I think we are good to start the algo trading you can also let me know in the comments that if you want any library to cover before we start the algo trading the core algo trading Concepts so we will be covering the ma blood lib in the two sessions in the first session we’ll cover the basic charts like the 2D line plot the scatter plot the bar plots the pie chart and the histogram and in the next session we’ll cover the advanced plots so without a further Ado let’s get started so the first plot is the line plot so first we will cover all the theoretical part and then we’ll proceed with the coding part as usual right so definition a line plot is a type of chart which displays information as a series of data points connected by straight line segments it is particularly useful for visualizing data changes over time so we can say the line plot can display the information as a series of data points connected by a straight line segments where and why to use the line plots so we can use the line plots for the trend analysis we can use the line plots for performance tracking and let me tell you something first that generally what.
Happens when we are dealing with the plots we get confused that which kind of plot I should be using for which kind of data so in order to resolve that confusion I have divided all the type of plots in different kind of categories so you can easily identify that where should we use which kind of plot right so generally we have two types of data the one is numerical and another is categorical right so the line plot can be used for numerical data particularly time series data so right after this mat
plot Library we’ll start with the time series in which we will understand the time series analysis and the time series forecasting line blood can be used for the numerical data and also we have three types of analysis the first is univariate the second is bivariate and the third is multivariate so univariate means when we are trying to observe or find the trend or the changes between a single variable or we can say a single column in a data frame by variate means when you’re trying to observe the
changes or the trend between two variables or we can say two columns in a data frame and multivariate means when we are trying to observe a or a change in multiple columns or we can say multiple variables right so that is the basic information so now what we will do we’ll divide all the five plots and we will understand that which kind of plot should be used in which kind of data and which kind of analysis right so this line plot can be used on numerical data and also it can be used on univariate
analysis and the multivariate analysis right next let’s understand few examples so line plot can be used to plot stock price movements over a month which is here right you can see here that it is starting from the 1st of June to 1st of July and these are all the points and these all points are connected with the line so that’s why we call it as a line plot correct and here is the daily closing price for the month of June 23 and it can be also used to track the price or volume of stocks over time this
helps in Trend analysis and moving average based strategy development I hope it’s clear the line plot is very straightforward very easy next we have is the scatter plot so a scatter plot uses dots to represent values obtained for two different variables one plotted along the x-axis and the other plotted along the Y AIS right so we can say the line plot uses the lines and the scatter plot uses the dots right where and why we should be using the scatter plot we can use the scatter plot for the correlation
analysis it is useful for sporting correlation between two variables such as price and volume or Returns on two assets it can be used for outlier detection it can help in identifying outliers or anomalies in financial data now on which kind of data we can use the scatter plot so straightforward we can only use the scatter plot on numerical type of data we cannot use this on categorical data right now the type of analysis so we can use this for the bivariate analysis and for the multivariate analysis right primarily
used to find relationships or correlation between two numerical values each axis represent one variable allowing for observation of pattern or clusters next multivariate analysis it can be extended to multivariate by using Color shape and size of dots to represent additional variables here is example visualizing the correlation between returns of two stocks you can see here stock a and Stock B and these are all the dots right it is ideal for exploring the relationship between the stock price movements of two companies
To identify potential pairs trading opportunities we’ll be using this a lot in the machine learning part but now you get the idea right the bar plot a bar plot or a bar chart represents data with rectangular bars with length proportional to the values that they represent where and why to use so in line plot we connect the dots with the lines in scatter plot we have the dots and in the bar plot we have the rectangular bars right and the length is proportional to the values that they represent we can use bar plot for the
comparative analysis we can use bar plot for the quantitative metrix right now on which type of data we can use the bar plots so we can use on the categorical and numerical data categorical data labels each bar and numerical data determines the bar’s height or length and also we can perform both the univariate and bivariate Analysis on this so let me show you you can see here we are comparing the monthly trading volumes this is the months from Jan April and this is the trading volume in thousands and also we can use it to
compare the performance of different assets or to show the frequency of Trades by category example long versus short positions we’ll be also using this a lot in the upcoming videos pie chart a pie chart is a circular statistical graphic which is divided into slices to illustrate numerical proportion right you can see here this is the pie chart where and why to use we can use the pie chart for the portfolio composition we can use the pie chart for the simplistic representation and also we can use the pie chart on the
categorical data where each category represents a part of a hole and also the type of analysis we can use it for the univariate analysis right so let’s look at some examples so you can see here it is the composition of a trading portfolio in which the stocks is 50% the Futures the options the bonds right so generally it is used on a single column of a pie chart now the last one for today’s session is the histogram I’m sure that you have seen histogram a lot of times if you trade right so let me show you
what it is so a histogram is a type of bar plot that represents the distribution of numerical data by dividing the data into bins or intervals helps to give an idea of where values are concentrated variation and outliers so what it does it helps to represents the distribution of data by dividing the data into bins or intervals right so where and why to use the histogram so we can use histogram for the distribution analysis right and we can also use it for the outli detection right which we will learn in the future we can also use
histogram for the volatility measurement and the type of data on which we can use the histogram is the only numerical data the pie chart is only for the categorical data while the histogram is only for the numerical data right and the type of analysis we can perform is the only univariate analysis now let’s see some examples so it is quite useful to analyze the distribution of daily returns of a stock to understand its volatility and risk profile you can see here this this is the daily returns and
this is the frequency it has divided the data into bins you can see here the bins and then we can easily have an idea of the frequency of the data so this was the theoretical part and now let’s understand some coding examples right okay so first of all we have to import the library so for that what you will do you will first import the pandas as usual import along with panda always import the numai as NP and for the M plotly you have the library import Mt plot Li right so here we are importing on the PIP plot for now
as PLT right so when you shift enter it says no module name because it is pandas so yeah we have seen that the line plot is for the by variate analysis right it can can be used on categorical and numerical so basically it is used for the time series data so let me show you something simple so what we will do let’s say we have a list of prices so prices from let’s say 2,000 3,000 4,000 5,000 okay again we have ear so for that let’s let’s from 2020 to 2021 2022 20 23 24 from 2020 to 2024 right now let me
plot this simple chart so PLT Dot Plot and first you have to pass the time on the xaxis right so it is here and on the Y you have the prices right so when when you H shift enter you will get a simple straight line right because we have given the straight line so let’s say if you change it something let’s say from 5 to again it came to 1,000 and back to 3,000 back to 2500 back to 6,000 and again dropped to 4,000 correct and you can give here again the time so 204 okay to 5 6 7 8 let me change the
values 5 6 7 and 8 okay uh okay actually we need to add another year here and when you hit shift enter you will see that we have a nice plot right a beautiful plot which is telling us that what was the price and in which year so on X we have the time and on the Y we have the prices right and here on the screen you can see some text R numbers so for that what you can do you can simply write plot PLT do show and it will be gone you can see that it is gone actually when you are writing this code on like Pam on or any other code editor
You have to use the PLT do show otherwise it will not plot right so in the Jupiter environment it is okay to run the code without the pl do show but if you’re running this code on any other uh ID you have to use the PLT Dosh show right okay now let’s understand the line plot on a real world data set so what we’ll do we’ll import some CSV here from our previous sessions so I’ll just go and let check where we have a CSV so I guess on like day 32 we had so let me copy and paste this here and check whether it works or not the name of CSV is constituents Financial CSV so I’ll just go here and import the CSV file so pd. read CSV and the name of file that is constituents financials when I ship enter I’ll get the values so what we will do actually there is no time in this it will be not a good example to for the line plot so for that what I will do I let let me check some other we have Exchange Trade data so it is the perfect example so let me copy and paste it here Exchange Trade data okay now.
Let’s perform this so I’ll just remove this for now if required we’ll use this again so okay now it’s pd. read CSV and Exchange Trade data CSV now we have time stem in prices so for that what I’ll do let’s quickly perform some operations on this so what I’ll do and from the column I want is from 0 1 2 to rest it says okay we have to provide the I lock here now it’s okay actually we have missed the date also we wanted right the time stamp so 01 so we have to use the one from one to okay now it’s fine I guess so I’ll reassign this to the data frame and now let’s check it we can do one more thing we can set the time stem as the index so set index and time St and let me make in place is equals to True right so yeah it’s done I guess now let me add another cell and let’s check the DF okay now it’s good I guess so let’s take only 60 rows right so 21 data so what I’ll do now I’ll take from 0 to 60 I’ll use iog here again yeah for now
I’ll just use this only so DF now we can plot this so what we can do I can simply use the price here right and how you can PLO this you can simply write PLT plot and this series here and when you hit shift enter now what happened here it is plotting for all the tickers but we need only for few tickers and actually I also seen that this is the synthetic data and it will not give us the good results for that I copied a code from the previous session and we will import data from the yaho finance so let me quickly do that so instead of this I’ll just remove this code for now and and we will import the data from the yo Finance you can check from my previous sessions we have used this code so here uh I’ll just remove everything so you will get this data right or you can for now you can just take a data for only apple right and it’s enough for now okay we are good to go so now what we’ll do we’ll block for only let’s say open so open let’s run this so yeah actually for a simple thing we get to do a lot of hiden fils but I wanted to show you the real data right so that’s why it took a lot of time so now when we hit shift enter you will see that.
We have a real data from the yaho finance so this is how you can plot and if you want to remove this uh stuff you can simply do show and it will be gone right let me remove this it will be gone correct now let me tell you few important things I would say so now let’s say if if you also want to plot the close prices on the same plot so for that what you can do you can simply go here and copy and paste this again and you just need to give here the close prices and you will see that you have another plot of the close price right sometime what happens you want to check the high and low right along with the open or close price so for that what I’ll do I’ll remove the close and I’ll change it to high and hit shift enter and you’ll see that we have the high prices and also we can plot the close prices means in a single plot you can have multiple values but how do we differentiate right now we do not have any information right that what is happening here so for that we have to give few more details right okay so for that what you can do you can add another line and you can say title right so this is the price of Apple you can say open high and low price comparison it can be anything just for the sake of example right so when you hit shift enter you will see that you have a title here and now it is more expressive correct you can also mention that what is at the AIS and what is at the Y AIS so for that you have to write plot dot X Lael and here.
You can give let’s say time right and when you hit shift enter you will see a time here and similarly you can also to give here on the y axis it is the prices so just copy and paste here and change from time to price and here it is the Y label so now time price and the title correct so I’ll just copy and paste it here this was for the label title now you can also change the color if you’re not liking the color now let’s say you want to change color of any line here so let me first remove any one line here it is becoming so confusing so I’ll just remove the close and we’ll keep only two lines here now it’s fine let’s say you want to change the color of the the open line so for that what you will do you’ll write color is equals to green and when you H shift enter you will see that the line for the open prices is now green similarly for the high also you can change and let me copy and paste it here again and let’s make it red right so red so now the line for the high price is become the red line again if you want any other color you can give here the hex code and you can find the hex code from the web right and let me show you how you can just search on Google Hex code finder and let me show you on the screen you can take anything here.
Let’s say this W3 schools and here you want any color so let’s say you want this blue color so for blue color you have this hex code just copy and paste in your code here so let’s say for open we have this hex code so when weit shift enter it says it is not valid because you have to add a hash here and now it’s fine right so that’s how you can use the color and okay now let’s say you want to change the line style so for that what you can do you can simply go here and write line style and you can give here let’s say dashed so you will see that actually we have M typed here line style not stpe so now you can see that we have the open prices as the dash line right similarly uh you can also have doted style also like you have multiple things here so for that so now you can see that we have the doted line for the uh high prices so you can go through the documentation and you can find more options there are multiple options I’m just showing you very few right now let’s say you want to change the the line width so for now I’ll just make it default so I’ll just remove or let’s uh place it here this code here and I’ll remove this line style from here okay now let’s say you want to change the line width also right so for that also you have the option here so line width and you can give any value let’s say three you will see that the line of the open prices is the width is increased right and similarly you can give here also if you want you can give here the width
Let’s say one and it will be also changed to one right so actually until this time stamp my mic was away so it might possible that there might a little bit less sound we’ll try to enhance this but still there might be a voice progam before this now it will fine don’t worry okay now if you want to change the Legends or the marker here we can do that also so for that I’ll again copy it and paste it here and for now I’ll remove this from here this also and let’s say you want the marker as d right for the open prices and you will see that it has changed to d right you can change it to like something different Also let’s say a big O big is not here you have to type as small o I guess yeah small o is there and like d is for the diamond okay and here you can type the marker let’s say so for the high you can have a marker as let’s say a diamond right and you will see that it has changed and also you can change the marker size so you can go here and you can write marker size and you can reduce it to let’s say three and here also you can reduce it let’s say to one so it will change to smaller size right so you have many options here use as for your requirements you can also display the Legends so let me show you you have the option plot.
Legend and when you shift enter you will see that it is here in the right so here like we do not have the multiple values so if I want it here data do index and here also data index now you have also the option to display the Legends here so for that what you can do you can simply go here and you can write label and it is for the open prices right so you’ll write open and this is for the high prices so you will write label as the high prices correct and now you can simply hit shift enter and you will not see anything for now but if you write here plot. Legend you will see that you have a legend here so it will show you that for the open it is the blue line and for the high it is the red line with the U marker for the high we have diamond and for the open we have the small dot right you can also change the location of this Legend you can move it anywhere on the upper right on the lower right or on on the bottom left so it’s up to you you have the options you can give here the parameters you want let’s say if you want it somewhere else so what you will do you will write loc location is let’s say upper right and when you shift enter you will see that it has changed to upper right right you can even have like lower right and it will come to lower right so it’s up to you it’s your requirement okay next we have is the limiting access so let’s say if you have a very large value a outlier in any exis so.
It will like flatten out all the other values all the smaller values let me show you how let’s say you have the price and it’s going uh like simple 10 20 30 40 50 right and here you can give let’s say time so time is let’s say uh in the first month second month third month fourth month and fifth month so it’s simple you can like quickly uh plot this PLT do plot and you can give first time and then the prices so you’ll get a simple straight line so actually you can reverse this also let’s say 50 10 20 and 10 again or let’s say 40 again and here also you can give few more values 6 7 8 6 7 8 and 9 right so now you have double bottom right so what I’ll do in the 10th month what happened the price spiked right someone pumped the prices so what happened here the price went up from 50 to 5,000 in the 10th month right so now you can see that the remaining prices are all flattened out so we cannot see anything here so in that case what you can do you have the option to limit this so what you will do you’ll go here and write PLT DOT first X limit so if in X limit you have anything then you can limit but for now we only have the Y limit so in y limit you can limit it to let’s say from 50 to 150 right so from 50 to 150 so now what will happen no actually not from 50 you have to limit.
It from 10 to 150 so now what will happen it will trim above 150 so at least your graph will not be FL WR out and you will have the good values right similarly you can do it for the time also or it can be any other value also right so let’s say it shoot from 10 to 1,000 so what happened it is gone completely right okay actually we have to add another value here let’s say 500 so now what is happening so in the time also it went from 0 to 1,000 so you can also limit this so you can limit this with the help of X limit and you can give let’s say 1 2 15 so now your xaxis will go up to only 15 so this is how you can limit the X and Y axis right you have option of the grid also let me show you how uh so let’s copy and paste the above example again here and I’ll remove this and let’s say you want to have a grid so for that you can simply write grid and you will get the grid you can see here right so it might require some time right and also the last one is show so show I have shown you already that it is mainly for when you are programming in any IDE like python charm or any other script you are writing so for that you have to write this show otherwise it will not work the chart will not be displayed on the screen right so let me show you this again also let’s hit shift enter now it’s all good but if you remove this show you will see that nothing is there because let’s remove all these things from here and you will see that you have some strings here right so in order to remove this you just have to type lot. show and it will be removed so this is how you can use the show and yeah that is for the day and uh we will cover the rest in the next session and until then bye-bye take care have a nice day.
Watch this Day 33 video tutorial
Day 33: Matplotlib In Python
