EDA preprocessing using MYSQL steps
EDA Preprocessing in MySQL: Connect to the MySQL database. Retrieve the dataset or table to be analyzed. Handle missing values: Identify columns with missing values. Decide on a strategy to handle missing values (e.g., removing rows, imputation). Implement the chosen strategy to fill or remove missing values. Handle duplicate values: Identify duplicate rows or columns. Decide on a strategy to handle duplicates (e.g., removing duplicates, keeping the first or last occurrence). Implement the chosen strategy to remove or modify duplicate values. Handle outliers: Identify columns with outliers. Decide on an approach to handle outliers (e.g., removing outliers, transforming values). Implement the chosen approach to handle outliers. Perform data type conversion and normalization: Convert columns to the appropriate data types (e.g., dates to datetime, numbers to numeric types). Normalize numerical columns if required (e.g., scaling to a specific range). Handle categorical variables: Identify ...