Data Manipulation with R and Python focuses on transforming, cleaning, and organizing data using two of the most popular programming languages in data science. It enables efficient handling of structured and unstructured datasets for analysis and modeling. This training explains how to perform data wrangling tasks such as filtering, grouping, merging, reshaping, and handling missing values. It also covers key libraries like pandas in Python and dplyr in R for streamlined data processing. You will learn how organizations use R and Python to prepare high-quality datasets for analytics, machine learning, and visualization. The course also highlights best practices for writing efficient and reusable data manipulation code.
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