Data Exploration

Data exploration is the initial phase of data analysis, focusing on understanding the dataset's structure, quality, and relationships. It involves techniques such as data cleaning, visualization, and descriptive statistics to identify patterns, trends, and outliers. This phase is crucial as it helps analysts formulate hypotheses and direct subsequent data analysis. Through data exploration, valuable insights can be gained, leading to better informed decisions and enhanced understanding of the underlying data. This is a mind map about data exploration. The map contains 7 main branches, namely: Data Aesthetics, Types of Data, Coordinate Systems and Axes, Colour Scales, Data Cleanup Basics, Exploring the Data, and Introduction to Single Variable. Each main branch has detailed descriptions of multiple sub branches. Suitable for people interested in data exploration.

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