Description

Data wrangling is a crucial step in the data analysis process, as it involves the transformation and preparation of raw data into a suitable format for analysis. The "Fundamental Tools for Data Wrangling" course is designed to provide participants with essential skills and knowledge to effectively manipulate, clean, and analyze data. Participants will be introduced to the fundamental tools commonly used in data wrangling, including Python, data structures, NumPy, and pandas. Through hands-on exercises and practical examples, participants will gain the necessary proficiency to work with various data formats and effectively prepare data for analysis. In this course, participants will dive into the world of data manipulation using Python as the primary programming language. They will learn about data structures, such as lists, dictionaries, and arrays, and how to use them to store and organize different types of data. Furthermore, participants will explore the power of Python packages like random and math for generating and performing mathematical operations on data. They will also be introduced to NumPy, a powerful library for numerical computing, and learn how to efficiently work with multi-dimensional arrays and matrices. A significant focus of the course will be on pandas, a versatile library for data manipulation and analysis. Participants will discover various techniques to clean, reshape, and aggregate data using pandas, enabling them to derive valuable insights from messy datasets.