Preparing for an analysis

I found these in the documentation and thought it would be good to share here. 

• Remove duplicates – Use the ‘Remove Duplicates’ function to eliminate redundant data.
• Handle missing values – Use built-in functions to fill missing values with mean, median, or a specific value.
• Format data types – Ensure numerical values, dates, and categories are in the correct format.
• Filter outliers – Apply statistical methods (e.g., Z-score or IQR) to detect and manage outliers.
• Standardize and normalize data – Use scaling functions to prepare data for machine learning models.