Applying Functions
3 Topics
Apply Basics
8 Sub-topics
Using apply() on DataFrame Columns
Using apply() on DataFrame Rows
Lambda Functions with apply()
Applying Functions with Arguments
Using applymap() for Element-wise Application
Vectorized Operations vs apply()
Map and Transform
4 Sub-topics
Using map() for Series Transformation
Using replace() with Dictionaries
Using transform() in Groupby
Using pipe() for Method Chaining
Conditional Operations
4 Sub-topics
Conditional Application with where()
Conditional Application with mask()
Using np.where() with Pandas
Creating Calculated Columns
Grouping and Aggregation
4 Topics
GroupBy Basics
8 Sub-topics
Understanding groupby() Concept
Grouping by Single Column
Grouping by Multiple Columns
Aggregation with min() and max()
Multiple Aggregations with agg()
Advanced GroupBy
9 Sub-topics
Custom Aggregation Functions
Grouping with Transformations
Size and Count Differences
Nunique for Unique Counts
Groupby with Multiple Statistics
GroupBy Performance
8 Sub-topics
GroupBy with Multiple Keys
GroupBy with Custom Functions
Nested GroupBy Operations
GroupBy Performance Tuning
GroupBy Result Formatting
Aggregation Patterns
8 Sub-topics
Custom Aggregation Functions
Multiple Aggregations Per Column
Different Aggregations Per Column
Aggregation with Filtering
Aggregation with Transform