• Basic Concepts
    • Groupby splits data into groups based on specified criteria
    • Pandas groupby() method splits data into groups
    • Groupby can handle one to multiple columns
    Data Analysis
    • Size() method counts rows in each group
    • Count() method returns dataframe with group counts
    • Uniqueness() method counts unique values by group
    • Missing values can be added using mask() method
    Aggregation
    • Mean, median, standard deviation can be calculated by group
    • Agg() method combines multiple statistical measures
    • Custom functions can be used with agg()
    • SciPy methods can be integrated with agg()
    Advanced Features
    • Multiple groups can be counted simultaneously
    • Percentages can be calculated by group
    • Grouped data can be saved as CSV or Excel files
    • Multi-level indexing available for large datasets

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