Before analysis can begin, data must be successfully loaded and its basic characteristics understood. This chapter concentrates on these initial, practical steps within the Exploratory Data Analysis process.

You will learn how to use the Pandas library to read data from common file types, including CSV, Excel, and JSON, into DataFrames. Following data loading, we will cover techniques for initial inspection: checking the data's shape, previewing the first and last few rows, and examining the data types ($dtypes$) associated with each column.

Furthermore, this chapter introduces fundamental data cleaning methods. You will learn how to identify missing data points (often represented as $NaN$) and explore common strategies for handling them, such as imputation or removal. We will also address the detection and management of duplicate records within your dataset. Upon completing this chapter, you will be able to load datasets and perform essential preliminary checks and cleaning operations.