Okay. So, in this course we also be discussing about basic processing. So, I will say our basic processing is the data preparation stage. This is the model. So we have business understanding then after that we go into data understanding so we use all those descriptive statistics, inferential statistics. We can also use those our data visualization which we'll be covering in another course on this data understanding and these are the using our data visualization and all those histograms line chart as block diagram and we will be using these our GG plot tool for more advanced charting and Polly, Polly for interactive charts are these.

So for data visualization, we also inside this our data understanding station So, in this course, we these are descriptive statistics and inferential statistics and regression adisa applies test statistic is also inside this data understanding. So, after we use all these statistics to understand our data or we use auto data visualization to look into our day time view them as some chart and after we understand about our data, we can go into the preparation stage where we will do some of the preparation or some other processing of the data by removing all those duplicates removing all those missing values and so on species in this data preparation stage Okay, so for this course we will be doing some simple data processing using our For advanced data preparation, we can use our D very famous dpl Allah package which we can search online is a very famous. So for Advanced Data Preparation, we can use our dp Li libraries.

So for this course, we will be doing the basic data processing. So after importing the data, we may need to do some simple data processing like selecting data, sorting data, filtering data, getting unique values and removing the museum values. So, selecting data we can select a few colors from the data using a vector. So let's say we have data. Okay, then we can select a data using our data and then a comma C and s and s3. So let's say we have data Okay, so this is our data okay.

So let's see I want to see lead data I can do some data and then I can put a comma and see okay. So, I pull out comma and then I see okay, so I have a series of variable name. So I can select s two and y okay. So our s two K, one Y Okay. So, I will Salah as to m y, ah, these two attributes variables are all the same, and then you may want to know why I put a comma here So, the first one here are before this or after this Way better here is actually the row and then after the comma is columns, you can search online for to see which one or which are damaged row and column. So we can select let's say two variables or attributes or columns are using these are vector okay then we can also select a variable using $1 sign.

Okay, so okay let's see. Select variable using dollar size something like this. Okay, maybe I so they are why Okay, so I selected a Y variable. I can also do some