Pandas Essential Training
From Jonathan Fernandes’ Pandas Essential Training (2017), I learned the foundations of working with Pandas, which is one of the most important Python libraries for data analysis. The training covered how to create and manipulate DataFrames and Series, import and export data from CSV/Excel/SQL, perform data cleaning (handling missing values, dropping duplicates), and carry out data transformations such as filtering, grouping, merging, and pivoting tables. It also emphasized how Pandas integrates with visualization libraries like Matplotlib to quickly turn raw data into meaningful insights. This directly relates to my major because Pandas is a core tool in data analysis, MIS, and business decision-making. As a Management Information Systems (MIS) student, I often need to work with large sets of business data—sales records, financial statements, or marketing metrics. Pandas helps me streamline data preparation and apply analytical techniques efficiently, which ties into my coursework in managerial accounting, economics, and data analytics. Beyond the classroom, mastering Pandas will also support my entrepreneurial projects (like AWAKEN MX and SPRK) where I need to analyze customer trends, social media metrics, and financial performance to make data-driven decisions.