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A parallel coordinates plot visualizes relationships and patterns across multiple variables using parallel axes.
Imputation replaces missing values with estimated ones, such as the mean or median.
One-Hot Encoding converts categorical variables into a format that can be used in machine learning models.
Feature scaling adjusts the range of feature values to improve model performance.
Principal Component Analysis (PCA) reduces dimensionality by transforming data into principal components.
Interactive Zoom in Plotly allows users to magnify specific areas of a chart for detailed inspection.
A funnel chart visualizes a process with decreasing stages, such as sales or conversion rates.
A bar chart is effective for showing rank or order by comparing the length of bars.
A stacked bar chart shows both individual category values and their total, providing a comprehensive view.
Plotly Dash is designed for creating interactive web applications with real-time data updates.