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Hey everyone.

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Before moving to the Lords there's something I need to tell you here and that's something I believe

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important that what we are going to study in this module we need to categorize this module.

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Otherwise you will get any problem there.

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So first thing is not like the metallurgy there have been everything from the beginning like how the

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X label is denoted how y level is appointed and how these points are created there.

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Every syntax because that's what you have already done.

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Handy seaborne we are going to move on floats that how we can analyze the professional data by using

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these blobs and that's what you will get in your companies and industries or in any project.

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And we are going to work on the same type of data that you will get on all duty places like in your

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job in your projects or in your industries.

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So now before categorizing the module there there's one thing that we're going to develop the data our

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own.

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So if you have seen the data the data will look like something this one this one is a excel sheet and

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in a program this will be like this one.

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Have you noticed this one is something like a data entry that is developed by using bound.

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And here we have more adoption.

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This one is an Excel sheet.

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First you will get the data annual access you then you will create that one in your bonds data frame

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and then you will use that one on your programs.

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But we are not going to waste over time creating the data and making the data frames because this process

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is I believe very low.

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It takes a number of hours and then you will be able to create only one data offering because you need

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to enter all the values again and again and check whether something right or wrong so we are going to

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use some data shoots that are predefined with Siebel that are available in the Siebel library.

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So you just need to load these files and you will get these data sheets for that data sheets you need

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to go here just write data sets in Siebel

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they will get this website Seabourn don't load underscored Data Set Don't Go for the official seaborne

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one that is not showing here

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likely that one that something like a I go here because we also need network so if you just google out

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Siebel and you will get this one seamless statistical data visualization don't go for that one then

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it will be a little complex to find these go for this one the state data sets in Python or data shoots

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in the seaborne sorry their base and get to the Web site heavily a the speech on this page you will

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have a link here that is denoting the tub dot com because Seabourn is officially released at its hub

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and there you will find every five to Siebel so here if you click on that one it will direct you to

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the IT hub page very you have the datasets here these CSC files that you have we have also loaded in

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upon the section so these are some predefined files which are going to use here in this module and some

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of these we are going to need is this one it is good CSP tips NTSB and diamonds NTSB you can use anyone

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you want to but I have selected these three because tips is what using every kind of like teaching one

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because it has all types of data and has much viz. that bill I will tell you that protecting and this

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is about the data that from there we are going to get the data to analyze that one and you can also

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involve your own data that you are working on if you are looking in at any project then you can have

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that data also.

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Now let me move to the plot.

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So here I have got radicalized deployed in four basic parts.

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Two things here.

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This categorization is not official like it will get this one on the Google or anything else.

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I have just categorize them on a simple basis.

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So you will understand them better.

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You can classify them as you want to or you can just go for the official one like what the distribution

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type and all that data.

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And second thing here these four no do not include all the plots here.

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These four just include the plots to require new projects like they are the plot also that is known

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as regression plots that are something related to machine learning and because this one is a topic of

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that part and if you are working on machine learning because data sciences in general is to learn for

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machine learning then I will also tell you about duplication plots and modification is now here.

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I have defined these four categories these four categories are defined in a V like if I have the official

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seaborne website and if I move to the category you will find different groups here.

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And if you plot on any plot like if I go for this one Katie

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then you will find this one.

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This is the main we can see.

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That means in Texas uploading the data head in that one you find different parameters.

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That is X here by here see map shared true.

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These parameters are just for the styling or we can see some extra things required in any plot.

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But first two are denoting the labels.

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That is what is on accesses and what is on Vi X is based on these two.

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These four categories are categorized here.

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Like if you notice here we have two wells that is X and Y.

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And if you go for something like Here let me search did this load and if I open line plot also

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so here.

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Line plot also include two parameters

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and no deadline.

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Maybe that one is not shown here.

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But the thing I need to tell you here like when we have open the one like line built here.

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If you notice here we have two parameters in those we have two different parameters.

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They are distorting the distribution blocks.

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If I have any data shoots like let me open one or just load anyone from these into your dataset but

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let me take a simple example.

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Go to the images and if I open this one any random one then you will notice here we have different columns

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some columns have numeric value some have strings and the strings are not listed here like this one.

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Here we have some have strings some have numbers and some have floating point values.

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So first we have point plots they are the plots that uploaded like the simple plot but they have only

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one parameter defined by user out of these columns or all these.

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If I just load any graph on the basis of frequency here and the second component will be maybe that

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one numbers or anything the computer want to set up there based on that one the frequency is vetting

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then those plots are known as Point plots in which we have only one parameter will officially point

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plots or something else.

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If you search on here on this one you will also find a point plot there.

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And again I would not be able to find that one let me suggest that here.

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I have point blowout

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and David over DC on point plot.

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You will find something like these.

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This is known as the point Lord in Siebel.

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But this categorization here point plots doesn't mean this one that only mean we are using only one

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column.

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Or we can see one parameter.

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Here we have two barometer total bill and pay.

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So this will fall in distribution process.

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So distribution codes include in which we have two columns.

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Like if a plutocrat between hope and frequency that how much frequency is vetting and variation of host

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then that will be a distribution program that I am using two columns or against it.

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Two parameters different one to show did its own deletion that how they are betting with each other.

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Third one is the category plus category.

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Blood is something like when I am plotting a numerical value with any string value like if I have a

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number of smokers in a city then I would float a graph on that one that how many smokers do we have

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and categorized them according to male and female.

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Then those blows are known as category blocks.

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I hope you got the idea after that we have met explode.

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There's something else I will tell you while we are working on that one so I hope you got the idea that

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what the four plots are and how I have categorized them these two are the official one that I will tell

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you you will get the same result for them.

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But these two are something I just made to make you understand better.

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You can also learn that one in play but this will help you more after that.

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One more thing like the data why we are not creating the data in this body next because whenever you

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are going to work on any project 9 in 90 percent cases you will find that data already made by any other

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person because there are a number of data scientist working on data science projects and students also

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limit the data files by day.

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So don't waste time on making the data files.

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And if you are looking for any particular data.

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I but you have defended the line just get that file and change the data according to your say.

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Like if you are uploading marks of students or heights of student then just download any data related

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to that front and change the data according to that like changed the names and change the Heights.

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That's the normal way of working because if you take a simple example like we have seen six mobile companies

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and we have some users that are working or using their cell phones or SIM cards then these all the six

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companies will not get data from every single user.

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They will do something like either integrate this area in six part like you take this one I take that

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one and then we will share the data with any one company can get the data and it will sell the data

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it does so never get worried about the data retention of data is very easy.

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If you go for easy they like in a smart way.

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And if you are going like I will create my data my own then that is also good.

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But that good news consume your time and network time is the first parameter.

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Anyone observe while taking you on any job or selecting you for any job.

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So thanks for watching.

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I hope you got the idea that what we are going to do here and how the points are categorized more you

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will get these ideas that what they are when we dominate them.

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So from the next video we will work on the point.

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So thanks for watching and we will continue in the next video.