WEBVTT 00:01.200 --> 00:08.220 In this session, we will discuss about data visualization, data visualization is a tool which helps 00:08.220 --> 00:12.300 us in locating the data visually. 00:12.810 --> 00:20.640 So we will be reading several blogs and learning how we can create blogs using the most frequency use 00:20.640 --> 00:30.990 libraries, which is my third clip, and see what my blog has extensive number of functions which allow 00:30.990 --> 00:36.930 us to change, even though my new details of the plot, which we are creating. 00:38.170 --> 00:46.240 And it takes a number of line of votes to bring those plot lines when we are working with C one, it 00:46.240 --> 00:53.490 helps in creating a lot more beautiful plot in a more concise number of line of. 00:54.670 --> 00:58.480 So we will learn both of these and see how things work out for this. 00:59.750 --> 01:07.520 So the first thing which we will be doing is we will import the required module, which is my dog fight 01:07.520 --> 01:13.050 block, and we will name it as blocked, this would be our Eleusinian. 01:14.500 --> 01:23.110 So let me in for this now, what we will be doing is here we have x axis values, so I have deleted 01:23.110 --> 01:30.040 certain X values, which is one, two and three and four responding by values as two, four and one. 01:30.990 --> 01:39.240 Now we will be plotting these ways, using like dot plot and we are living in the values X invite to 01:39.270 --> 01:39.420 it. 01:40.430 --> 01:42.830 So, ladies, just like this, much of the. 01:43.920 --> 01:45.200 Lines of code for now. 01:46.200 --> 01:49.940 So when I ran this, I get just a single line here. 01:51.820 --> 02:00.370 This single line does not have any name or any labels, what you can see here is just the values one 02:00.370 --> 02:01.210 for to. 02:02.170 --> 02:04.210 Then do up for. 02:05.300 --> 02:07.880 I'm sorry, Obama one. 02:09.000 --> 02:18.510 Now, next, what we will be doing is there are a few more functions like Lord X label, X label allows 02:18.510 --> 02:25.600 us to provide a label for the X axis, and while it will allow us to provide a label for the Y axis. 02:26.400 --> 02:30.870 So this is just the name which would be printed in front of the X and Y axis. 02:32.290 --> 02:37.000 Next is the title which allows us to give a title to the plot. 02:38.070 --> 02:45.460 Along with it, we have the option to sell the blood group if we want to say this, true or false. 02:45.780 --> 02:50.370 So let us put this as false for now and we'll just run this. 02:51.450 --> 02:57.590 So when we run this envelope, so forth, it brings the Y axis, the x axis, the graph name. 02:58.970 --> 02:59.730 Let me. 03:01.130 --> 03:07.320 Change this, so now it is giving a grade on top of what you can see, these blocks have been highlighted. 03:07.580 --> 03:11.390 So this is the grade, which it has noted for us. 03:13.010 --> 03:19.100 Now, next, what we will be doing is we will be plotting two lines instead of one line in a song we've 03:19.110 --> 03:21.600 got now, the process remains the same. 03:21.920 --> 03:28.730 We will give the X and Y points in the plot dot plot and we will give them leave before the line. 03:29.390 --> 03:35.630 Similarly, we will give the X and Y values for the second line and we will give the label for the second 03:35.630 --> 03:35.880 line. 03:37.070 --> 03:43.820 After this, we are giving a lot of thought, maybe this will give the next level to the Lord itself 03:43.830 --> 03:47.090 is inviolable for the y axis. 03:47.090 --> 03:49.160 And the other thing that I did, do it again. 03:50.230 --> 03:58.330 Now we will learn the religion, this plot basically plots this small block on the right side, which 03:58.330 --> 04:01.320 will give us what life actually represent. 04:01.330 --> 04:02.440 Which particular line? 04:02.440 --> 04:02.860 No. 04:05.210 --> 04:13.160 So this is what has been Peter and I, just coming this way, so now you can see that no legend has 04:13.160 --> 04:13.850 been printed. 04:14.060 --> 04:19.070 So this that legend basically allows us to create the legend. 04:22.450 --> 04:24.490 Now, the next option here is. 04:25.650 --> 04:33.300 To select the axis value, so again, we are giving X and Y values and along with the X and Y values, 04:33.510 --> 04:38.380 when we are giving the plot details, we are giving one more Nevius to it. 04:38.580 --> 04:43.710 Now, initially, what we used to give was we just used to give the X and Y values. 04:43.950 --> 04:50.070 And along with it now we are giving more details like what color do we want to have? 04:50.280 --> 04:53.580 What color lines do we want to have then? 04:53.580 --> 04:55.680 What type of line do we want to have? 04:55.860 --> 05:02.540 We do we want to have a continuous line or we want to have a dash line, then the width of the line, 05:02.910 --> 05:08.430 then the marker, which we want to use the face of the marker, the color of the market, which we want 05:08.430 --> 05:10.300 to use and the size of the market. 05:10.590 --> 05:13.560 So this is the floor which has been created to allow. 05:14.850 --> 05:16.740 Let me reduce the size of the. 05:21.790 --> 05:24.460 So this is the plot which has been delayed until now. 05:24.640 --> 05:28.420 Now, what we can do is let me remove this as of now. 05:31.520 --> 05:39.590 So now you can see if I will change the board of the line nine and so it will just change the way it 05:39.920 --> 05:40.100 is. 05:40.940 --> 05:42.030 It is more doctor. 05:42.030 --> 05:45.880 And now I just change it back to three. 05:46.460 --> 05:52.400 Now, my is basically the size of the door, which we are able to see so we can change it to a smaller 05:52.400 --> 05:53.210 value also. 05:53.570 --> 06:02.000 So you can see the SOCOs, how small a smaller size now and I just change the size 12 and the market 06:02.000 --> 06:03.260 would change to any other. 06:03.700 --> 06:05.390 So I'm changing it to a star. 06:05.900 --> 06:08.320 So it is changing into a star now. 06:08.660 --> 06:12.220 So same as the color of the market is still here. 06:12.380 --> 06:18.200 I can change 220 so that you will be able to see the color model so you can see the color again. 06:19.520 --> 06:26.150 Now, for the same things I've been through, I provided with is the violin with an X, this violin 06:26.150 --> 06:31.850 with the next movement will basically increase the range of the access which we have currently. 06:31.850 --> 06:34.340 We have one to six and one to six. 06:34.340 --> 06:35.530 I would the access. 06:35.720 --> 06:38.600 Now, what we are asking it to be is one, two, eight. 06:39.570 --> 06:43.940 Next is viable label in the title, so let me run this again. 06:45.170 --> 06:53.030 So now you can see the limits have been changed and the exercise has changed from one to six to one 06:53.030 --> 06:54.090 to eight to. 06:55.390 --> 07:00.500 Now, the next things which we have is, again, we are giving just the name is different. 07:00.700 --> 07:03.250 So initially we were giving X and Y values. 07:03.250 --> 07:06.230 Instead of that, we have just given right and left. 07:07.120 --> 07:10.600 Now, this is the same thing which we have provided now. 07:10.810 --> 07:17.240 Now, the plot is different now when we use a plot line for us. 07:17.530 --> 07:19.540 Now we're using Clodagh, but. 07:20.810 --> 07:23.850 This means that people want to plot Barcia. 07:24.410 --> 07:31.220 Now, what does a bar chart bar tried to something which has the bars for the frequency of the values 07:31.220 --> 07:36.480 which we have here, so that the values which we have is one, two, three, four, five. 07:36.710 --> 07:43.090 So for these values, the frequency of Ballston, the frequency of two is twenty five. 07:43.100 --> 07:45.600 The frequency of three is thirty five. 07:45.830 --> 07:47.800 So we have these frequency values. 07:48.050 --> 07:50.470 So the same thing that we have provided here. 07:50.490 --> 07:55.190 So we have provided one, two, three, four, five, and we have provided the height of the bar which 07:55.190 --> 07:56.120 we want to have. 07:56.450 --> 07:59.180 Identical labels is just the labels. 07:59.180 --> 08:01.760 Would you want to give for these values. 08:03.260 --> 08:08.610 So if we would not have given this, it would have simply shown one, two, three, four, five. 08:08.810 --> 08:11.390 But we wanted to give the actual tape. 08:11.390 --> 08:13.040 So we gave these values to. 08:15.250 --> 08:20.980 Now, what we are doing is we are simply saying goodbye, which means, please, a lot of our flight 08:21.640 --> 08:28.900 and for Varjak, give this X value, give high does value, then these are the big labels which you 08:28.900 --> 08:29.710 want to flog. 08:29.980 --> 08:33.280 The victim of the plot is Point East. 08:33.520 --> 08:35.920 And these are the values which you want to have. 08:36.280 --> 08:38.200 We can have given any colors. 08:38.210 --> 08:38.500 You. 08:39.760 --> 08:43.220 Now, here we have the verdict so we can change the world today. 08:43.260 --> 08:47.230 Also, let me put it as one point nine. 08:49.180 --> 08:55.930 So if you're on this so you can see the weight of the plot of the bars has fezzes, I can reduce it 08:56.110 --> 09:00.660 also now, so I have just reduce the rate of the blood on the jacket. 09:01.270 --> 09:06.770 So and these values may actually be available data. 09:07.090 --> 09:08.590 These are just the same things. 09:09.900 --> 09:13.260 And not to simply lotting the. 09:14.390 --> 09:16.770 A lot on this trip, Daniel. 09:18.740 --> 09:19.820 Now, the next thing. 09:21.170 --> 09:23.540 Now we are plotting the histogram. 09:24.410 --> 09:24.980 Now. 09:26.410 --> 09:34.240 This bar chart simply thinks the values from the heights here and similarly histogram will also do the 09:34.240 --> 09:34.850 same thing. 09:35.200 --> 09:42.850 It's the only difference which we have here in case of his program is that we will provide certain values. 09:44.780 --> 09:53.540 And from these values, it will break out on the basis of a certain range, I think, of frequency for 09:53.540 --> 09:54.710 the ranges. 09:55.760 --> 10:04.610 So we are giving the agents and we have given a list of agents here, and based on these ideas, we 10:04.610 --> 10:06.950 have given a range that we want to have. 10:06.950 --> 10:08.440 It is from zero to hundred. 10:08.810 --> 10:12.400 That is why it is creating a plot from zero to hundred. 10:13.870 --> 10:21.510 They are giving the vinces Benzi is basically the present how large we want these bars to be. 10:21.710 --> 10:24.350 Now, how we do that, I just show you in the white. 10:25.540 --> 10:31.220 Then we give the artist, which means that has to come now for this Instagram. 10:31.240 --> 10:34.270 We want it just to be in the X-axis. 10:34.600 --> 10:37.030 We want Vince to be in the Y-axis. 10:37.030 --> 10:41.680 Always remember, first we will give X, then we will give Y value. 10:42.550 --> 10:44.350 Then we provide the range. 10:45.530 --> 10:53.210 Then you provide the color, then we provide what type of Instagram do we want, we want the bar chart 10:53.210 --> 10:57.930 type always to come, and this is the word that you want to have. 10:58.160 --> 10:59.960 So let me change the post. 10:59.990 --> 11:05.330 So let me have it one point so you can see the word has changed. 11:07.400 --> 11:09.970 Let me make it back to zero point now. 11:11.180 --> 11:19.220 And the world has changed, but now the Belsize is five, which means that I want to have five bars 11:19.250 --> 11:21.930 here one, two, three, four, five. 11:22.430 --> 11:26.360 Now, what I could have done is I could have reduced the number of bins. 11:26.390 --> 11:29.020 So let us say I just want to have two bins. 11:29.240 --> 11:33.710 So when I have two bins, the frequency increases. 11:34.660 --> 11:40.930 The number of people in the first one is now 16 and the number of people in the second one is almost 11:41.320 --> 11:41.890 six. 11:44.160 --> 11:46.560 Then I have the vinces, the 20. 11:46.890 --> 11:55.450 What happens is now the highest number of frequency which we have is five and others are subdivided. 11:55.710 --> 12:01.110 So how precisely we want to see is dependent on the number of bits. 12:01.290 --> 12:10.980 If we want to see for a smaller range, then we will use the larger bean size if we want to have a view 12:10.980 --> 12:12.210 of a larger means. 12:12.240 --> 12:15.230 We want to view data for a broader sense. 12:15.480 --> 12:17.980 Then we will use the smaller bins. 12:18.210 --> 12:20.730 So let us get back to the five minutes now. 12:21.390 --> 12:24.590 So this is showing for a larger space. 12:24.810 --> 12:27.270 So it is showing the range from zero to 20. 12:27.300 --> 12:32.490 This particular 20 to 40, this particular it was showing for the smaller, smaller amount that the 12:33.110 --> 12:34.550 five within that. 12:36.150 --> 12:40.600 Now, other things remain the same makes me believe I live in L.A. or. 12:44.230 --> 12:47.950 Now, again, let us get back now. 12:47.960 --> 12:54.040 This is the X and Y value, and the block which we are trying to block now is Scatterplot. 12:54.820 --> 13:02.530 Now, Scatterplot is again taking the similar kind of input values would just X and Y values then the 13:02.530 --> 13:05.600 label, what kind of label we want to have. 13:05.830 --> 13:12.730 So the label is then the color is green, the marker which we have. 13:13.750 --> 13:22.150 Is stars here, and this is the size of it, so I would have like thirty three hundred also, so now 13:22.150 --> 13:23.650 the size has increased. 13:26.010 --> 13:32.670 Now, the legal simply means, what is the name of the Markovitch we want to have so we want to give 13:32.670 --> 13:35.880 this stock so that is why we have these funds. 13:36.360 --> 13:41.310 Now, these actually bilabial didley is just the same thing. 13:41.310 --> 13:43.220 And Florilegium is, again, the same thing. 13:43.560 --> 13:51.270 Scatterplot is simply what gives us a market at every point, at every data point. 13:51.600 --> 13:54.670 So actively explain why it gives the market. 13:54.780 --> 13:56.160 This is what the scatterplot. 13:58.500 --> 14:05.670 Now, the next kind of plot which we will be talking about is the five plot, so by plot will basically 14:05.670 --> 14:06.570 give us a fight. 14:07.170 --> 14:11.270 So in this fight, we have, first of all, defining the labels, which we have. 14:11.550 --> 14:16.450 So the labels are these activities, which is easy, Wolf. 14:16.470 --> 14:22.090 And then the portion of time or portion of each label which has been covered is also given. 14:22.260 --> 14:24.620 So it is three seven, eight six. 14:24.960 --> 14:32.400 So it will Kanwar this are these values and find out the percentage of area of the pie and what should 14:32.400 --> 14:34.960 be given to this much sleights. 14:36.620 --> 14:38.710 Then these are the pilots for each Eataly. 14:40.070 --> 14:46.690 Now, what we do in case of blood is we give the slices values, we give the labels that water labels 14:46.730 --> 14:54.220 should be given, we provide the colors, then we provide the angle that we want the starting gun going 14:54.230 --> 14:55.230 to be 90 degrees. 14:55.700 --> 14:58.500 Then we give the Shadowfax false. 14:58.760 --> 15:03.440 So let's say instead of 90, we wanted to have seen it see 180. 15:07.610 --> 15:14.240 So it changes initially it signaled something which actually had nine people think of the need of it, 15:14.810 --> 15:18.590 but now it has been something which is nearer to 180 degree angles. 15:18.830 --> 15:26.510 So let's say we wanted to have a smaller angle, say one hundred, so it will decide accordingly. 15:27.470 --> 15:31.580 So it has one hundred degree angle and beginning with a 100 degree angle. 15:31.790 --> 15:39.410 So for more like looking, we will just select 90 degree because 90 degree looks better with you. 15:41.190 --> 15:43.110 Now, the next thing which we have this. 15:44.120 --> 15:51.290 We will have the shadow, so we are putting shadows false so you can see there is no shadow behind if 15:51.290 --> 15:52.670 I make this as true. 15:56.800 --> 16:00.500 It adds a shadow to the speech and it gives a 3D look. 16:01.690 --> 16:05.050 Next is the explored option. 16:05.290 --> 16:12.290 Explored option basically allows us to have this thesis pulled out of the plot itself. 16:12.520 --> 16:18.320 So if I just change this to zero point three, this one until then, it will be a lot more. 16:20.840 --> 16:26.480 And if I give this as itself, then it will be just a part of the. 16:28.220 --> 16:35.690 And one point is the radius of this block, and this is changing to automatically percentage for. 16:36.650 --> 16:41.010 Then legend will allows it to create a legend. 16:41.030 --> 16:43.790 So if I had just done this. 16:45.270 --> 16:54.540 It was the legend again, now how we provide the size of the blocks, how we decide where the site should 16:54.540 --> 16:59.600 be, is is done by the Lord God religion. 17:00.090 --> 17:06.440 So we are doing it if using this legend and this is the location which we want. 17:06.900 --> 17:11.070 So we are seeing that we wanted to be at the center live. 17:11.460 --> 17:14.250 So let we not give this as of now. 17:17.370 --> 17:22.440 And on this, so now it is President Sando and it is president of the left. 17:22.900 --> 17:26.070 Now let me change it to center right. 17:28.820 --> 17:32.000 So it goes to the center right now. 17:32.120 --> 17:39.910 I want to change the location of it, so I want to change the box location to one and. 17:41.110 --> 17:44.930 Let's say zero point five to zero point five. 17:45.220 --> 17:46.130 So it goes by. 17:46.990 --> 17:49.090 I wanted to be one. 17:50.070 --> 17:53.530 And zero point five, so its location is slightly more changed. 17:53.940 --> 17:59.270 I wanted to have one point five and one point five, so it goes outside. 17:59.550 --> 18:01.880 So it is from the center of the block. 18:02.220 --> 18:08.610 This exercise has been decided so you can modify it and decide where you want this legend to be. 18:10.690 --> 18:14.950 Now, the next block years are simply using a sign. 18:15.670 --> 18:18.720 So in this we are simply creating a function. 18:18.970 --> 18:25.990 So I am randomly selecting the values of X and we are randomly creating the Y values based on these 18:25.990 --> 18:28.480 X values and we are simply plotting. 18:29.750 --> 18:31.640 So it gives us this function. 18:32.830 --> 18:41.200 The next is we are generating plants based on the coordinates, so I'm just giving a function here and 18:41.410 --> 18:47.440 this function is generating four types of plants, which is already flawed cubic lorden. 18:48.460 --> 18:55.900 But they fly, and this is one thing where you can find out different types of stylesheet stylesheets 18:55.960 --> 18:59.060 is just how we want this block to look. 18:59.440 --> 19:05.020 There are different color schemes which are present so you can select from different color schemes from 19:05.020 --> 19:06.300 this particular website. 19:07.030 --> 19:11.040 And this is the plot, not style, which we are currently using. 19:11.440 --> 19:14.580 And now the most important thing. 19:14.620 --> 19:19.390 Now, what we have been doing is we have been plotting just one single thought in the area. 19:20.910 --> 19:26.130 Now we have to decide how we can have multiple plots. 19:27.880 --> 19:32.620 Created in a single figure, so that is what we are doing now. 19:32.950 --> 19:37.960 So what we have to do is the first thing that we do is we declare off the good. 19:39.240 --> 19:49.230 We let my relatives know that we have to create a figure, so we say feel good and we believe that my 19:49.230 --> 19:51.690 figure needs to have a subplot. 19:53.140 --> 20:03.190 And for that, what I do is I feel that my subplot has to be us to cross, to make Rick's my subplot 20:03.190 --> 20:08.050 has to be a fog of cross to matrix and legacy. 20:08.080 --> 20:10.120 This is Michael rostral matrix. 20:13.390 --> 20:20.680 Now, here's what I wanted to have, is I want to see a trustful matrix, so it creates a matrix like 20:20.680 --> 20:21.100 this. 20:21.110 --> 20:25.560 First of all, we declare a figure so it knows that we want to create a figure. 20:25.720 --> 20:30.670 And also that figure we declare that I want to have a two plus two matrix. 20:30.680 --> 20:31.960 So it should have. 20:33.970 --> 20:34.630 One. 20:41.540 --> 20:41.960 To. 20:44.970 --> 20:45.480 Three. 20:47.200 --> 20:56.710 And full portions, so this is one, two, one, two, so this is like two cross two and it has four 20:56.710 --> 20:57.700 subdivisions. 20:58.120 --> 21:02.550 So out of this Blue Cross do anyhow, it will have four subdivisions. 21:02.710 --> 21:10.180 So what I learned is that in this figure I had a subplot and one that subplot has to be it has to be 21:10.180 --> 21:19.870 two women who do find one, which means that it has to be this two plus two one section, this one section. 21:19.870 --> 21:21.990 It has to meet after that. 21:22.010 --> 21:29.380 When I say good, I don't add subplot to Bill to this means that in this to graspable matrix, pick 21:29.380 --> 21:31.390 out the second one for me. 21:32.470 --> 21:41.290 Then when I say I got I've subplot two to three, it means that out of this to Matrix pick out the code 21:41.290 --> 21:42.420 works for me now. 21:43.060 --> 21:49.030 And similarly to do for me from the book was to pick out the fourth one for me. 21:51.480 --> 21:59.670 So based on this, we provided that I wouldn't float one or two or three or four to be like this, and 21:59.700 --> 22:06.720 after that, once we have provided, then this should be my blog, then I would love not be destroyed. 22:07.110 --> 22:12.930 So what I do is I simply get the X and Y credentials and these X and Y values. 22:12.930 --> 22:18.900 I put it in Duflot one dot plot and I put the X and Y values and provide. 22:20.250 --> 22:28.830 Similarly I get the X, X and Y values and get the block to and in plot to I be X and Y values. 22:28.830 --> 22:29.270 And so. 22:30.590 --> 22:31.100 Now. 22:32.370 --> 22:37.110 While I do this, I also give the title and by giving the title. 22:38.260 --> 22:44.440 We have this mathematical function available, which basically allows us to provide subscriptions to 22:44.440 --> 22:51.610 Facebook, so whenever I'm writing something between these dollar signs and I am using the underscore 22:51.610 --> 22:57.990 inside this, so whenever I'm using an underscore, it understands that this number was just following 22:58.000 --> 23:06.120 on whatever characteris has to be made a subscript and whatever is followed by this bovver site is a 23:06.130 --> 23:07.090 superscripts. 23:07.960 --> 23:13.540 So similarly, this one becomes a subscript deal and this too becomes a superscript you. 23:15.000 --> 23:17.260 Everything is is just the same. 23:17.700 --> 23:20.880 We simply have this sick title. 23:20.910 --> 23:25.620 All these values and apart from that, we have this figured out subplot. 23:25.620 --> 23:30.660 And just so we are giving the height and weight spaces so I can give. 23:31.640 --> 23:36.770 Point two also here, so you can see one side you point to this will change gradually. 23:38.420 --> 23:45.440 See, the space between these has been decreased a lot, so I'll just simply give one on one here so 23:45.440 --> 23:47.360 that it has sufficient space. 23:52.130 --> 23:58.430 Now, the next thing which we will be doing here is we are creating a group saying now this is one method 23:58.430 --> 24:02.150 of creating a grade one method of plotting different. 24:03.410 --> 24:07.230 Figures together adding different floods to a single figure. 24:07.520 --> 24:11.970 Now, another way of doing this is define us in red size. 24:12.410 --> 24:14.080 So this is my size. 24:14.330 --> 24:21.180 When I say to me, Grosseto, this means that I want to have to be rows of data and two columns. 24:21.980 --> 24:27.800 Now, what I'm seeing here is my finger size has to be 12 for my eight. 24:30.410 --> 24:33.470 So it has to be 12 portions. 24:34.480 --> 24:36.060 Call eight portions. 24:37.500 --> 24:38.590 I'm out of this. 24:38.610 --> 24:42.860 What I want to have is that they're zettl pharmaceutically stopping. 24:43.440 --> 24:48.130 Give me a call, Spanel, and we'll spanel who and make it up. 24:49.300 --> 24:50.150 It's a good one. 24:50.180 --> 24:51.350 This is one. 24:52.290 --> 24:56.870 I'm aware, glad I have this great size starting from zero. 24:57.330 --> 24:58.560 Give me a portion. 24:59.690 --> 25:06.140 As to and wherever you go, no one is stopping, give me a portion extra. 25:08.130 --> 25:09.900 So let us see how this works out. 25:15.900 --> 25:24.390 So here's what we have is we have up to the four million, which means there's this complete image is 25:24.390 --> 25:28.590 created out of three rolls and two volumes. 25:29.570 --> 25:37.450 So although this we are selecting we are starting from zero point zero, which is the origin point, 25:37.640 --> 25:42.260 this particular point I'm from this I want to have two volumes. 25:42.260 --> 25:48.620 I thought this is two column I thought out was a little three. 25:49.760 --> 25:51.410 So let me change it to. 25:52.870 --> 25:54.370 One volume and one. 25:58.990 --> 26:06.970 So now you can see that one problem is this much so this is Tuvalu's and Thoros area, which we had 26:06.970 --> 26:10.150 earlier given to the this X one. 26:11.470 --> 26:14.050 Now, let me do one thing, let me change it from. 26:15.870 --> 26:17.820 Two one zero one one one zero. 26:20.510 --> 26:24.200 So now the figure which was present below has moved up. 26:25.630 --> 26:28.700 And now what I can do is I can also change the size of it. 26:30.410 --> 26:31.190 Eigen. 26:32.150 --> 26:33.590 Change the size to. 26:39.510 --> 26:41.550 I want to have calls been asked to. 26:46.160 --> 26:53.390 So now the columns fan of this one has been pleased to do so, similarly, you can fix the size of the 26:53.390 --> 27:00.260 grade and point at which location do you want the finger to start back and where you want to have this 27:00.260 --> 27:03.960 particular plot to start the subplots to start. 27:04.340 --> 27:07.370 So similarly, we have created another plot here. 27:07.610 --> 27:13.100 And in this plot, I have given the size of 11 Gunma one. 27:13.430 --> 27:20.270 And this is the position which I have I have selected from a zero and from zero point zero. 27:20.270 --> 27:23.240 I have given a rule span of three and a span of one. 27:23.630 --> 27:28.590 And and based on that, I have given this kind of distribution. 27:29.150 --> 27:32.240 So this is the distribution which I have received finally. 27:32.540 --> 27:40.820 So you can try different combinations of rule span and call span and find out what or how this actually 27:40.820 --> 27:41.360 works. 27:43.110 --> 27:51.540 Now, the next type of figure which we have is a plot stack plot basically allows us to create plot 27:51.810 --> 27:54.030 with just that one over the other. 27:54.300 --> 28:01.620 So I have this particular plot for East Asia and that is the plot for Eurasia and another plot for East 28:01.620 --> 28:06.840 Asia, Oceania, Asia, which is plot one over the other. 28:07.080 --> 28:13.320 So what I have done is I have simply created certain values of years. 28:13.740 --> 28:16.140 Orangy and are the. 28:18.090 --> 28:26.940 So this is the X value, which is the year and the Y value is basically this Orenda plus orangy. 28:28.600 --> 28:34.530 And the Lebas is East Asia, Eurasia and Oceania, and this is the 29th. 28:34.780 --> 28:36.780 This is the legendary location. 28:37.150 --> 28:43.810 This is the Lislevand and this is the Slimer, what I want the cinema to be. 28:44.440 --> 28:47.950 And based on this, I have just started this entire thing. 28:48.020 --> 28:50.810 I be brought into sackcloth. 28:53.650 --> 28:59.940 Now, the next thing what we can do is we are plotting a combination of lots. 29:01.000 --> 29:09.040 So what we have simply done is we have simply said we want to have a figure and in that figure we want 29:09.040 --> 29:18.100 to have subplots and these subplots should have in rules one and volume two, the number of rules is 29:18.100 --> 29:22.360 one, the number of columns is two and the total figure sizes also provided. 29:22.810 --> 29:26.920 So based on there, it will automatically subdivide this. 29:27.860 --> 29:35.330 This particular area, based on these plot and we are simply giving that X one should be a scatterplot 29:35.330 --> 29:40.280 and these other things for the scatterplot, then X2 should be a histogram. 29:40.280 --> 29:46.090 And these are the details for the Instagram and hence this has been created. 29:46.470 --> 29:56.060 Now, the only thing to notice here is that we have simply provided the number of rules and number of 29:56.060 --> 30:01.220 columns which we want to allocate to these two figures. 30:01.550 --> 30:08.560 And it has authorized, bitterly divided the area equally for the full subplots, which we have in the. 30:12.110 --> 30:14.960 Next is the Seabourne Library. 30:15.880 --> 30:20.380 So in case of civil liability, we will be learning about the fate of flight. 30:21.460 --> 30:29.650 Now, one thing to notice here is that we will be walking on different floors now, these plants will 30:29.650 --> 30:36.080 also help us analyze what type of data we have, what type of distributions do we have. 30:36.640 --> 30:40.150 So we are picking out one detail said. 30:41.340 --> 30:48.360 So the data set is basically of this FIPS dataset. 30:48.660 --> 30:50.610 So this is what we will be using here. 30:51.060 --> 30:54.770 So let me show you what all plots do we have here. 30:55.930 --> 31:04.570 So first of all, we are improving the libraries, which is no fun, does the one make our site bisects? 31:06.800 --> 31:17.000 So we are simply creating a distribution block distribution plot is simply a plot which has the density 31:17.270 --> 31:26.010 of data, how data is distributed or where different values and blood clot did before that. 31:27.110 --> 31:33.470 So here you can see when we think the normal distribution floor without any bottom windows, this is 31:33.470 --> 31:34.520 what it lot. 31:35.240 --> 31:38.650 So I have generated this with random values. 31:39.380 --> 31:42.970 So here you can see the values are ranging from minus two to three. 31:43.250 --> 31:46.150 And these are the frequencies for these values. 31:46.490 --> 31:53.150 And this is the density of the value, which is similar to somewhat similar to what the histogram also 31:53.150 --> 31:53.630 depicts. 31:54.350 --> 32:01.780 So although the density plus is a lot more smoother in nature, so we get a better picture. 32:03.660 --> 32:11.700 So when we use the distribution block and we see the full defaults, you can see the line for the van 32:11.740 --> 32:15.390 to be full, which was created, has been removed. 32:16.260 --> 32:18.960 And there is another option to include a drug. 32:19.890 --> 32:29.070 This really is these small lines which are depicting the density of the dog, any particular point of 32:29.070 --> 32:29.410 time. 32:30.540 --> 32:38.390 So you can see these have a higher density, so this has a more density of smaller draglines here. 32:40.030 --> 32:46.300 We have another option to keep or remove the histogram, so when I make this histogram as follows, 32:46.300 --> 32:48.610 the Instagram behind has been removed. 32:51.780 --> 32:58.500 Now, all we have been creating, only singleplayer to now what we are doing is we are creating multiple 32:58.890 --> 33:03.350 plot and these plots are actually the forward into the plot Stinson's. 33:03.630 --> 33:07.800 So the plot is what gives us the then to develop. 33:08.730 --> 33:15.280 And I'm just plotting to be called into these plots in a single plot here. 33:16.140 --> 33:20.460 So each line represents a different continents like. 33:22.210 --> 33:32.690 And that is an option to include the shading, this shading basically eyes this color below the area 33:32.690 --> 33:35.800 of just covered as a part of the skull. 33:37.230 --> 33:46.200 And we have an option to either block, which is, I think, the drugs to it, so we could have achieved 33:46.200 --> 33:49.310 this using density lost plot also. 33:49.620 --> 33:52.270 So the distribution plot also. 33:52.470 --> 33:56.730 So it is completely up to you how you want to plot this then. 33:57.120 --> 33:59.790 And the plot is the distribution plot against. 34:02.010 --> 34:10.740 In this distribution block, I am have I begged the government entity I have given the drug lord also 34:11.100 --> 34:18.450 and I have also given defragment, these beans walk the same way, how other beans and other things 34:18.450 --> 34:19.350 to them as well. 34:19.920 --> 34:29.700 So as the increase, the number of beans, a smaller bar, a smaller size bar will be added so more 34:29.730 --> 34:31.340 number of bars will need. 34:35.090 --> 34:38.370 And when we decrease the number of Beenz. 34:40.480 --> 34:44.350 Smaller number of bars would be needed, which would be broader in size. 34:47.970 --> 34:49.560 Now, here we have. 34:51.390 --> 34:52.650 Again, the. 34:54.810 --> 34:58.050 Seabourn style, which is why the great. 34:59.010 --> 35:01.770 And this is the data set which we are loading. 35:05.050 --> 35:11.380 And here we have the distribution block, which we are creating for the global village values, so this 35:11.710 --> 35:13.210 is a total value. 35:13.420 --> 35:24.640 So you can see the usually the bail amount is ranging from as low as five or two and it is going up 35:24.640 --> 35:25.450 to 50. 35:25.750 --> 35:34.500 But most of the people who are visiting the restaurant are being something around 15 to five. 35:37.290 --> 35:40.080 Next is the distribution floor for the VIPs. 35:41.220 --> 35:50.820 Here you can see that the tapes are usually ranging for one to eight and then also by the major tapes 35:50.820 --> 35:52.800 are between two to four dollars. 35:55.140 --> 36:01.530 Now, this is the box, we have also discussed this earlier, but let me repeat this again. 36:01.530 --> 36:06.290 So a box flight is a representation of the coordinates. 36:06.720 --> 36:11.750 So the lower part of the box is queue one line. 36:12.060 --> 36:14.000 So below this line. 36:14.280 --> 36:16.740 Twenty five percent of the data is in. 36:17.490 --> 36:22.440 The middle of the box is represented by the median, which means that. 36:24.130 --> 36:28.690 Fifty percent of the vice president below the same, then the upper line. 36:30.000 --> 36:37.740 Is the quality of the data, which means that seventy five percent data is present in this particular. 36:38.980 --> 36:42.190 Then we have the law with the. 36:43.290 --> 36:52.110 Then no outlier value has risen, the whiskered would be lying Geike, Q1 minus. 36:53.250 --> 37:01.860 The story then, no detail will be present, no outline that will be present, this law school will 37:01.860 --> 37:08.460 be present at the minimum value in case of our client would be present, then this is the way we move 37:08.940 --> 37:14.550 to Q1 minus one point five IQ and the outliers will be below this. 37:16.050 --> 37:24.870 And when the upper riska will be present, the maximum value, when there will be no outlier. 37:26.030 --> 37:29.450 Above and it will be present at. 37:30.430 --> 37:33.400 Guilty plus one point five Fames Aikawa. 37:34.750 --> 37:40.670 In case any outliers are present and the outliers will be present here, just like they are present 37:40.690 --> 37:41.880 at this particular moment. 37:44.260 --> 37:57.670 So this is what a box blood is, so this also shows that the values are majorly present between of 12 37:57.670 --> 37:59.650 to 24 something. 38:00.880 --> 38:04.930 And a more a better version of this. 38:05.950 --> 38:09.850 In case we want to view the Golden City also. 38:10.700 --> 38:11.690 Is the William. 38:13.110 --> 38:24.000 The wilin plot is similar to this plot, but it does not show the exact points of median. 38:24.030 --> 38:31.680 You can see the point of median as this white dot, the darker point here and this darker line here 38:31.740 --> 38:33.590 as you one and three. 38:34.500 --> 38:45.210 And these the smaller lines, this thinner line represents the line for the minimum the law was and 38:45.210 --> 38:46.860 the line for the upper Mr.. 38:47.800 --> 38:48.970 Apart from that. 38:50.440 --> 38:57.640 This majorly shows the only to be so you can see how the values are changing actually in this particular 38:57.640 --> 38:58.360 dataset. 39:00.160 --> 39:04.150 Now, another plot that we have is about plot. 39:05.410 --> 39:07.880 This is a bad lot for the Devastator. 39:09.320 --> 39:10.750 Here we have a count. 39:10.850 --> 39:21.140 Lord count gives the count of the values, so we have created the ground floor for the sex column and 39:21.140 --> 39:24.340 it has the values, male and female. 39:24.830 --> 39:30.470 So the male values is around 160 and the female value is around 80. 39:32.080 --> 39:38.200 And you can see the majority value is for males and females is not in the majority. 39:40.670 --> 39:43.850 Then here is a count for these. 39:45.770 --> 39:54.110 So you can see the maximum number of customers come during the weekends, that is on Saturdays and Sundays. 39:55.400 --> 40:00.410 I'm here is a lot of VIPs, the. 40:01.570 --> 40:08.770 And here they have provided a view which is a change in color and this change in color is shown with 40:08.770 --> 40:09.790 respect to time. 40:11.120 --> 40:17.500 So there are two times when people are coming in, one is lunch and another one is enough. 40:18.290 --> 40:28.700 So if they come back, you can see that people are coming usually during lunchtime in the days and during 40:28.700 --> 40:30.590 dinner time during the weekends. 40:31.460 --> 40:34.810 And there are more number of people coming during the weekend. 40:34.820 --> 40:38.240 And you can see that all the people who are coming are. 40:39.240 --> 40:40.890 Coming during the dinnertime. 40:43.890 --> 40:51.450 Now, these are all analysis, which we have done on a single column on a single variable. 40:52.260 --> 40:56.340 We can also do analysis on multiple variables. 40:56.670 --> 41:00.840 So these are a few analysis which we have done here. 41:02.370 --> 41:11.150 So here we have created a box plot and we have created the box plot between the X value being the which 41:11.160 --> 41:13.530 is closed Friday, Saturday, Sunday. 41:15.320 --> 41:17.240 And that would be. 41:19.060 --> 41:26.560 Now, when we compare these of the plot, which has been created, you can see that the total bill is 41:26.560 --> 41:32.680 higher during Saturdays and Sundays and even the median value. 41:33.780 --> 41:37.770 For these bills is higher during the meakins. 41:39.930 --> 41:43.320 While the total bill is lower during the weekdays. 41:45.300 --> 41:54.400 When we compare the time with the amount of depth, you can see that immediately, the tapes do not 41:54.420 --> 41:55.440 very much. 41:56.820 --> 42:05.760 Although the median of the depths is higher during the dinner time and the median for lunch is lower. 42:08.530 --> 42:16.030 And there are also certain outliers present during the dinner time which supports the fact that the 42:16.030 --> 42:20.580 person would be getting more tips if they're walking in the dinner shift. 42:23.290 --> 42:32.620 Then here is a comparison between the total bill for smokers, so this has been segregated with smoker 42:32.620 --> 42:33.840 and non smoker. 42:34.090 --> 42:44.080 So you can see here when we compare with the Thursday and Friday with respect to smokers, the total 42:44.380 --> 42:48.430 value that the blue is for smokers. 42:48.680 --> 42:55.930 So you can see the value is not really changing much, although there are a few outliers in case of 42:55.930 --> 42:56.710 smokers. 42:57.980 --> 43:09.170 But the value is almost similar, like in the case of the Vikings, the value is comparatively the free 43:09.650 --> 43:11.920 in case of smokers and nonsmokers. 43:12.080 --> 43:17.480 As you can see, the median for smokers and non smokers is very different. 43:18.650 --> 43:20.480 For weekends. 43:23.230 --> 43:26.780 And then is a larger amount of. 43:28.440 --> 43:30.840 Outliers present in these cases. 43:33.180 --> 43:37.290 Here we are again, comparing the two Thebans and the De. 43:38.400 --> 43:40.110 With respect to Smokers'. 43:43.430 --> 43:50.810 So here you can see that the values are not changing much, but in case of smokers. 43:52.130 --> 43:55.610 The total bill is higher and. 43:56.690 --> 43:59.540 For nonsmokers, the total bill is almost similar. 44:01.450 --> 44:10.630 Here is another kind of plot, which is a joint plot, joint plot is a collection of two plots, so 44:10.630 --> 44:13.480 it has a histogram on the top. 44:15.210 --> 44:23.310 And it has it has another kind of plot in between this kind of plot could be a scatterplot, it could 44:23.310 --> 44:27.380 be a regression, it could be a residual, it could be a corporate entity plot. 44:27.390 --> 44:29.700 Any kind of fraud could be present in between. 44:31.440 --> 44:32.560 So here it is. 44:33.480 --> 44:38.120 We have not provided the kind, so it has taken the lead for skying, which is the site. 44:38.820 --> 44:43.020 So we have plotted the total bill with respect to the tips. 44:43.710 --> 44:49.410 So you can see there is somewhat a linear relationship between the billion tips. 44:49.980 --> 44:54.450 As the total billing freezes, the tips also increase. 44:55.400 --> 44:56.000 And. 44:58.230 --> 45:03.810 You can see this is, again, the plot for the value with respect to the depth. 45:05.300 --> 45:09.830 So you can see these plots also created by the site. 45:11.910 --> 45:19.680 Now we can change the mind also here, so we have the defined progression, which is the reason why 45:19.680 --> 45:22.200 it has added to this regression line here. 45:26.830 --> 45:34.690 Here you can see we have converted the type two hexagon, so instead of having these dots, it has actually 45:34.690 --> 45:42.800 created hexagons here and you can see the color variance in the types of hexagons. 45:43.270 --> 45:52.720 So wherever the density of the points is higher, the color of the hexagon is doubtful, while wherever 45:52.720 --> 45:55.420 the density of the point is lower. 45:56.950 --> 46:01.390 The hexagons are lesser in number and the color is lighter. 46:05.600 --> 46:10.070 Now, here we are creating another blog. 46:11.450 --> 46:19.310 And this one is a joint plot where we have given the kind as hexogen and we have provided a stai to 46:19.310 --> 46:27.050 the axis, so this is the axis styling, which we have provided under the existing name is dark. 46:27.650 --> 46:30.980 So we can provide Stine's to these also. 46:31.890 --> 46:35.260 So there are a lot of methods which are present. 46:35.280 --> 46:42.360 There are a lot of variants present for each and every plot which we are generating. 46:42.810 --> 46:51.120 The foreign leaders, which we are including for any plot, are a lot lesser in number in comparison 46:51.120 --> 46:52.920 to those actually exist. 46:53.760 --> 47:00.600 So whenever you are creating a plot and you think that there should be some way in which you need to 47:00.600 --> 47:05.130 have, then you can go to the documentation of that particular plot. 47:06.260 --> 47:13.730 And see what will be the inside of prison, what changes you can do the Fulda in good barometers to 47:13.730 --> 47:17.840 get a different kind of Lord or any changes in your. 47:21.180 --> 47:28.080 So here we have created another joint plot and you can see I have just changed the size by changing 47:28.080 --> 47:29.520 the height and racial. 47:29.760 --> 47:36.980 So you can play around with the height, value the racial value and change these things. 47:38.610 --> 47:41.110 Here I have needed a relation, Lord. 47:42.110 --> 47:45.870 Relation plot is just creating a line here. 47:46.550 --> 47:52.730 I have given the X values, the Y values, apart from that, I have given no hue. 47:53.240 --> 47:58.910 Hue is basically a color line, which I have provided, and the hue is for smoker. 47:59.910 --> 48:05.450 So for the values of small, good, different values of small good, that is a different color vision. 48:05.790 --> 48:09.000 So because Morgan has two values, yes and no. 48:09.420 --> 48:11.790 So, yes, he has a different color of line. 48:11.790 --> 48:13.920 I know has a different color of mine. 48:15.370 --> 48:22.930 Apart from the color of lime, we can also have a stai, like we have here, style as dyeing. 48:23.260 --> 48:27.750 So because the time has dinner and lunch, two different values. 48:28.000 --> 48:31.600 So the style of the line has also been changed. 48:31.840 --> 48:40.180 So for all the detail which is related to dinner, the style is a straight line, while for lunch the 48:40.180 --> 48:41.800 style is a dotted line. 48:44.350 --> 48:52.990 Similarly, we have this size and sizes for size group of the size of the people coming, so we have 48:53.140 --> 48:56.890 four types of size, zero to four and six. 48:57.610 --> 49:04.330 So based on the size of group of people, again, the width of the line has been changed. 49:06.450 --> 49:10.490 I'm kind is basically the lying vibe that we have provided here. 49:13.840 --> 49:16.510 Now for this relation block. 49:17.440 --> 49:25.360 We have, again, given the similar data and we have given although if a state. 49:28.330 --> 49:31.500 So it has created this line here. 49:35.190 --> 49:41.460 Another thing is here we have the same thing, we are given a different dataset here. 49:42.090 --> 49:46.950 So when we create this relation floor, it also gives. 49:47.950 --> 49:48.640 Oh. 49:51.110 --> 49:59.540 Confidence in double value, so you can see this light shade area, which has been cheated here, apart 49:59.540 --> 50:05.200 from the line, this is basically the confidence interval which has been shown now. 50:05.210 --> 50:11.690 Similarly, when we are giving the CIA the confidence interval value to be standard deviation. 50:13.090 --> 50:20.200 In that case, it has created the value as standard deviation now of the confidence interval is actually 50:20.200 --> 50:22.270 pointing towards the standard deviation of the. 50:25.920 --> 50:34.350 So similarly, we can plot different kind of clouds beginning different hues to the Lord and divide 50:34.350 --> 50:36.030 the plot into different plots. 50:36.210 --> 50:38.800 So there are different kind of things which we can do here. 50:39.270 --> 50:42.740 Another thing which we can do is we can either rose in volumes. 50:43.350 --> 50:50.120 So here we have created a simple relation plot with X and Y, and we have given the difference in color 50:50.130 --> 50:53.580 using human being for smokers. 50:54.120 --> 50:56.560 And apart from that, we have given column. 50:56.910 --> 51:02.590 So we have created two columns based on the time at which the customer is coming in. 51:03.000 --> 51:07.430 So if the customer is coming in lunch, so there is the left column for that. 51:07.650 --> 51:13.230 And if the customer is coming in, then also there is this right column for that so that we can compare 51:13.230 --> 51:15.410 these right in front of each other. 51:16.780 --> 51:24.550 Similarly, we can have multiple roles and multiple columns based on the types, the categories, the 51:24.550 --> 51:25.370 categories. 51:25.630 --> 51:31.690 So if time has two more categories, then it will create four columns here. 51:33.110 --> 51:43.180 And here we have event value and we have a region value, so here Virgin has two types of values and 51:43.250 --> 51:43.800 strengthens. 51:44.930 --> 51:51.950 So two columns have been created here because we have given column time as region and we have given 51:52.220 --> 51:53.360 life as giving. 51:54.820 --> 51:59.920 So based on what event it has created, two different rules for us. 52:02.720 --> 52:09.410 And again, we have given the kind of line, the x value, the value that he knew to be the subject 52:09.650 --> 52:16.340 and raised on the subject and has created different lines, now, we could have taken a subset of the 52:16.340 --> 52:22.900 subjects and created different lines for those also to view it more clearly. 52:23.180 --> 52:25.910 So there are different variants which we can try here. 52:28.230 --> 52:30.630 And here we have a beer plant. 52:31.390 --> 52:35.650 A beer plant is basically gives a complete. 52:37.380 --> 52:47.730 Analysis of different variables come back together in pairs, so if we compare different values with 52:47.730 --> 52:55.650 different numerical problems, so we have size, we have tips we have to table and these have been compared 52:55.650 --> 52:57.990 with each other and created plots for. 52:59.090 --> 53:02.990 So here we can analyze and see what is related to what help. 53:03.840 --> 53:10.950 And the last one is the correlation plot, which shows how one column is correlated with another. 53:11.310 --> 53:19.140 So here you can see the lighter value refers to one, which means that the diagonal will always be one 53:19.140 --> 53:26.400 because it would be always highly correlated with total because it is the same column by here you see 53:26.400 --> 53:36.870 the values dips has zero point six to eight as the correlation coefficient with the size has zero point 53:36.870 --> 53:37.260 six. 53:37.710 --> 53:46.050 Correlation with total size has zero point four nine as correlation coefficient with dips. 53:46.320 --> 53:53.130 So similarly, the more the number of columns, the more colors will be present here and then we can 53:53.130 --> 53:53.850 find out. 53:54.940 --> 54:02.050 The columns, which are highly correlated and then again removed them, we will see how we remove the 54:02.050 --> 54:02.650 columns. 54:02.920 --> 54:08.980 We will be using this correlation matrix to remove certain columns. 54:10.080 --> 54:14.670 In upcoming video in the next session, probably. 54:15.670 --> 54:17.770 And then you can see how this works.