ABSTRACT
MATLAB is highly used by professionals from different domains who do not know the data science domain. MATLAB provides us with a wide variety of built-in functions to perform analysis and numerical computations easily. Whichever data science software you use, it is mandatory to know the data science workflow and how it is incorporated with the software that is being used. Similarly, we begin this chapter by understanding the data science workflow in MATLAB. Once you know about the data science workflow, we will further move toward data storage. MATLAB supports various file formats, and these file formats can be imported into MATLAB. Importing data in MATLAB is performed just by one double-click on the MATLAB application. Further on, we will look into the data representation formats by MATLAB. MATLAB stores data in the form of rows and columns, i.e., in the table format. MATLAB is accurate enough to display the data types of the features in the data once you import the data into MATLAB. The data types suggested for the features are mostly accurate, but one can change these data types as well. We will go through the data types in MATLAB in detail. Data science is a vast field and so are the large-scale data science projects. These projects need multiple data files to be used in their analysis, so manually importing each of the files is a tedious task. In such cases, you can automate the import process in MATLAB using the Live Script. In data science projects, it is advisable to remove the irrelevant data from the file to enhance accuracy. Filtering the data comes in various types: you can remove the unwanted features or merge different features for analysis and so on. While performing numerical calculations, you will come across a situation where you will have to perform some calculation on a wide range of data; this can be performed using vectors or by creating functions. MATLAB provides different techniques to manipulate data and perform numerical computations on vectors, categorical data, and the functions as well. We will go through these techniques in this chapter.
