 next type of multi-dimensional graphs or multi-dimensional charts in many situations when we want to visualize more than one variable or more than one dimension in that situation this graph is very very useful and you have already seen some graphs, even they can be converted to this type of graphs but it will depend on technology, tool, libraries, so on and so forth and this is important to understand that the multi-dimensional graphs they have a lot of applications across industries you are in social sciences, in private sector, in public sector you will get these things almost everywhere now you see in this we have done that grouping and fisting these are two main parameters according to which you have made a group of students this is a group but what is inside it may be age group, it can be class, it can be grade in one group but in that there are multiple dimensions it can be different facets, facets mean that you have to do that in the graph this particular graph, if you see in this it is a three-dimensional graph in this you have one axis, x, y and z you have three axes available and its shape that is more self-explanatory you can say that these things are known from these types of graphs then you cannot see in this particular diagram that when you use a legend, the different color coding that helps you, we discussed the shape if you have to use triangle, you have to use scale, you have to use circle they can have different meanings similarly these different variables in one chart you can use them in different ways by grouping and using different shapes and different colors you can use them now see in this you can see the sales data order data is sale at sales quantity and shipping cost now these three different variables which you want to see in one graph may be you want to understand as a financial manager that the number of different sales is coming from my cost because in every business there is an important factor that how to optimize your cost and how to increase the sale there is a common phenomenon across industries one thing which is called top line this is basically your revenue or sale this is your top line and the other thing which is called bottom line this is your cost this is revenue now let us see in the next slide how these things are graphically represented now what we did is, I used a schema when you first created the schema in the schema you can see that sales, number, quantity, shipping cost all these things are coming then what I did is I created the data first you created the schema and then created the data for this you have created the number you have created the data for the data frames or in the NumPy or in the C-Bone library you can directly put these things in it and you don't have to worry about the coding there are a lot of tools they do it by themselves when I did it in the fusion chart it was almost the same after that you prepared the data for rendering then you created the index file after that you rendered the data and after that you have this graph now look at this I have discussed this multiple times now here you have the sales data this is quantity and this is shipping cost you can see these three but maybe if I you may not be able to compare but you must know look at this there is a lot of sales here but there is no shipping cost now what is the connection between them that we don't understand that's why the concept of data storing you need to add some notes but interestingly if there is more sales then there is more cost this means there is a direct link but the quantity maybe this can be a very expensive item this is again subjective from the situation in which industry you are selling your cars or you are selling your children's toys it will matter a lot now we are going to understand one thing that we have discussed earlier if we show this at one place then what is this? this is hodgepodge it is very difficult to understand you have said that this is my sale this is quantity and this is shipping cost in this graph I don't understand anything no one will understand anything this means even if I use a bar chart in which I have this kind of thing maybe that will be more useful but then can I relate to them or not for that maybe I have to use you know regression I will see that this is my cost and this is my sale this is the link this is basically again what I have said what is the graph you have to use that you will learn with the passage of time and when you know what is the problem of my business what is my audience then you will be able to select the right graph and the right representation and that is how it is going to help you this is a very interesting chart this is called senki chart and this is one of the latest editions these are all the graphs or their history is one if you go into the statistics or otherwise you will find out that there is a histogram or your pie chart this is a very basic chart and they are available for ages right as you understand data we say big data the variable of data is too big the size of data is too big then there are new charts these are new libraries these are Python libraries they did not exist 10 years ago there are revision charts these are also 5-10 years old so basically as your technology evolves industry's requirements increase similarly the vendors or the companies they bring new things like the digital ecosystem of information technology where data science is working so this is basically different if you look at it there are different countries where your production cost is less if we look at USA and Canada obviously one more thing there is a social factor USA, Canada, UK the western world the production cost is more than any other manufacturing because of the minimum wage rate or the social responsibility by laws they are very very strong if we look at some countries like China's example India's example or some other countries they differ similarly you can consider different things like fuel consumption fuel cost but this is again a very very interesting chart you will understand or try to see I have given this source from sanshdirect.com you can see different examples you will find more examples how you can use this chart