Data Representation
The main objective of machine learning is to build models that understand data and find underlying patterns. In order to do so, it is very important to feed the data in a way that is interpretable by the computer. To feed the data into a model, it must be represented as a table or a matrix of the required dimensions. Converting your data into the correct tabular form is one of the first steps before pre-processing can properly begin.
Data Represented in a Table
Data should be arranged in a two-dimensional space made up of rows and columns. This type of data structure makes it easy to understand the data and pinpoint any problems. An example of some raw data stored as a CSV (comma separated values) file is shown here:

Figure 1.1: Raw data in CSV format
The representation of the same data in a table is as follows:

Figure 1.2: CSV data in table format
If you compare the data in CSV and table formats...