Introduction

In this section, we will address the tidy data standards, which are essential principles for structuring data to streamline analysis and manipulation. We’ll delve into tidying tables, focusing on organizing data so that each column represents a variable and each row an observation.

Next, we’ll discuss tidying headers, highlighting the importance of clear and descriptive column headers for effective data understanding and management.

We’ll proceed with tidying columns, examining techniques to transform columns that may contain multiple variables into separate ones, ensuring each variable has its own column.

Finally, we will introduce data cleaning tools, which are invaluable for cleansing and preparing data, ensuring they are ready for analysis. This includes correcting invalid values and standardizing formats.

After each content segment, you will complete an exercise to consolidate your learning. Good luck with your studies! 🍀