Okay, so, in this chapter tree, we are going to talk about the the SDK script writer essentials. So, the SDK three and chrystia model, as I mentioned or say previously is that the SDK tree is developed by myself and is developed to match with the crease the model in mind. So, in the SDK screenwriter, ah, all the commands to put into our run in the SDK engine are actually matching into the Christie model. So for example, in the, the SDK screenwriter, we have that prepare. So prepare is small on the date, prepare Surprise, surprise more in the understanding. And we have the explode but tm.tm is that that's my name.

And we have Mada, which is the modeling that we had evaluate, which is the evaluation stage. So in this the SDK tree, you can see that all the the SDK engine commands are matching with the Christie model. So the SDK trees actually more target or more focused on the data mining, data mining, text mining. So now we talked about the SDK scripts in data. So in the SDK, and G DS TK and je, interpreter. So we write in the D SDK called money into the, the SDK and G. So the SDK itself has all the all the command has a syntax.

So far the SDK command syntax. So the first one is cross our category, which is the Import Export. Then we have the prepare x-prize part is brought in more than that and evaluate. So the first one is actually the cross or the category. Then follow by whitespace. We had a function.

Okay, so let's say in the import category, we have the CSV function. So, the first one is the cross the second one is the function. Then we have the firing separator is all these three is the properties are in programming in programming wise, we will call them parameters, which is more accurate. Okay, so this is a syntax for the SDK command. And we have the, let me we'll talk about a variable a variable variable Y variable two. So this variable, zero variable one variable two, also has a syntax.

Okay, so arroba zero. Usually mean is the first row of the data room variable Why? is the second row, second column of the data. So far the proper syntax the syntax variable, underscore the column number. So variable zero is the first column variable one is the second column, robot two is the column and bar row is the same. So row zero is the first row, row one is the second row.

So the row syntax is row and score and then the row number. Okay, so, row zero is the first row. So row, row underscore three is the fourth row, okay. Then I say we want to ah have many columns. So, we put the rubber underscore square bracket inside we have the order column number 013. So, these mean that we are stating the first column, second column and the fourth column.

So, the syntax for using the four by kathina a few column number is roba underscore in a bracket, okay. Okay, column number one, comma column number two comma column number three. So there should not be any space in between the square bracket. So, we should not have column number one comma space column number two, comma space. No we should not have any spacing This is the syntax for selecting the menu columns. Okay, then for comments, comments are usually those lines in the script that will not be run by the the SDK engine.

So command usually has a syntax how to slash then followed by a colon followed by a comma. So your description and a semicolon. So the semicolon should not have a spacing after a spacing between before. Okay, so semicolons so all comments and comments must end with a semicolon and semi colon up issue not happen in space. And before the semicolon should not have any spaces. Okay, so we usually use semicolons only when we are writing the the SDK script.

When we are writing the writing into the the SDK engine, and we only put in Java one column command, usually we don't need to put in a semicolon. So semi colon is usually for the SDK script. So script we have the SDK script, we have a few commands. So each after each commands, we should have semi colon up each command in our script, we also should have a semicolon. Okay, so the SDK script is surely run inside the the SDK script writer Okay, so far is the SDK syntax are we only have around to page to page of the D SDK script syntax to lambda by, okay. So unlike many other programming languages and we have a law, syntax, look steamer these are the SDK scrubbies.

Very straightforward. Okay is trying to be easy to write easy to understand and easy to read. Okay, so in the SDK is script syntax or the SDK command syntax we usually only usually need to learn on your route to patient per se synthesis, so the syntax or the grammar of the Scrivener or the programming course Okay, so the SDK script writer now we go into the understanding. So we will be doing the data understanding using the SDK script writer Okay. Okay. So this is the SDK script writer which we have previously used as I say ready when we are writing a script.

A script we have a few commands, they usually end with a semicolon okay a semicolon that should not be spacing up semi colon ah be Pause semicolon Okay, so we can add in our own comments to enter comments we use to slash to slash time we can type whatever text we want. So for this comment, I will write the description or the of the imports, import comments, okay. So I will write something like this import II, II II, II see me CSV then a semicolon, no spacing after that we have import rate CSV file in the drive a CMA dot CSV separator is comma is CO is true okay. FB a TA data review de variables okay. So we can run this code and see okay so in this script import the ACM EDI data and this is the data importer and these are the variables okay so a variable to select the column design should be the variable zero second column this one should be the variable one column this one should be the variable two.

Of course column design should be a rubber tree okay so Now I want to do expiration on the 123 column. So should be variable to variable one variable two, okay. So when I look for the spa, spa has broad cross is broad category, so when I paint to pull in this one okay, I got to close the SDK engine first. Okay. Okay, so now I do it I sprawl so a straw descriptives variable to Okay, let's call them variables, zero second column row variable one column vailable to so as broad as supply is cross the category for the data understanding that descriptive is at the descriptive statistic for the bureau board wishes that column okay? So I just click this one and press view and run.

Okay so you can see we have descriptive 402012 Okay. So we have the mean, we have medium minimum maximum Aaron's gave us underscore S is Barents for Semper. Fi underscore S is fast temper percent are 0.05 issues. You can say the first quarter 4.7 Pfizer aquata kurtosis, schooners confidence in about 95% okay the lower limb end one is the lower one is a polymer okay. We can do some exploration also. So we can get the rows for the population.

It runs underscore, S is the variance for the sample, underscore P is the population so we can put in to So, so taking the column me run Okay, so we have a reference for population. So point 002 a, two a one. Issue b, d from from the sample. Yeah. Different. Okay.

And then we add in the Korean coalition also. As for our correlation, robot to the robot tree. Me you can see Ah, let's see. Okay, so we have the correlation alecto there are about three correlation between the column, robot to robots a little bit Robo on there are about two and a fourth column variable tree. So this is a cold relation. And we can also put in the t test.

T test. Also test between the two column. They're about to end the rubber tree and then we run it. So the issue here is t statistic Okay. I will have to say this the SDK and June is still in the beta version. So there may be some inaccuracy or maybe some bugs.

You can feed back to us or regarding any bugs. All right. Any inaccuracy and we can try to correct them here. Okay. Okay. So this is Ravi yes probably can also ask the linear regression.

Simple linear regression. So let's say s variable s variable by put ms to why their best tree actually run again. As you can see Paul simile a simple linear regression. So the update Oh is that Sharon she will be watching 1.13 times x Ras negative though pi 01 Okay. So the slope or the MR gradients should be 1.13 and C or some of them call beta should be minus 0.01 and a square raise 0.29 and the R square is 0.28. Okay, so roughly we have run most of the important statistical analyses.

So, we have run the descriptive statistics and the variance in terms of our population correlation. There we run a inferential That is in the teeth as to sampa an equal difference in every run regression analysis using simple linear regressions okay. So, we can also he can also do the plotting plotting a graph, so, sprawl proc, there are variables to be two three okay so this one should be variable to is widely available tree ah oh can be the dry this is a stop ah So, should be scatter dot png can run, generate ID Dr. png so D drive scatter scatter PNG Okay, so, this is a scatterplot the robot was S S, S S S, the robot tree as the y axis. So the robot fee is the y label here. So this is why it's axis is called a robot tree is a white label these white label here while labor, okay, as labor available to okay and then these are the two variables to be problem and then to generate alpha.

Okay. Let's see how close our viewers are. This one is to generate a result in two as far as results or view the test file Okay. So again we come here about crayon crayon this January results and clear result oh yeah not using that get results okay. Yeah run because I have no procedure okay. Random going to see more properly okay so you see if you generate result who can adiz dialog here So this one you can copy and paste in your Microsoft Word test document.

So you can can pacing in Notepad or you can paste a resign the Microsoft Word okay. So Ctrl V they have other result so you can use the result to do all your work or projects. Okay so you can see we have Kaabah all the Most of the preparation analysis using descriptive statistics, inferential statistics and the regression analysis and then data visualizations. So are these are the commands for the data exploration or the data understanding stage? They should be somewhere see, they should be somewhere here the understanding. Okay.

So as you can see these, the SDK tree follow very closely to this Christy and model. So we are we just and Nevada scrubbies to do some data analysis or the understanding on the data. Okay, so the next one we will be doing will be more on data preparation okay.