Exploratory Data Analysis

ɪkˈsplɔːrətɔːri ˈdeɪtə əˈnælɪsɪs

Exploratory Data Analysis (EDA) is a critical phase in the data analysis process where analysts use various techniques to summarize and visualize the main characteristics of a dataset. This process often involves generating descriptive statistics, creating data visualizations, and identifying patterns or anomalies. EDA helps in understanding the data distribution, relationships between variables, and potential outliers, which can inform further analysis or model building. Common use cases include preparing data for machine learning, hypothesis testing, and decision-making processes in business and research.