UsefulLinks
Computer Science
Data Science
Pandas Library
1. Introduction to Pandas
2. Core Data Structures
3. Data Loading and Saving
4. Indexing and Data Selection
5. Data Cleaning and Preparation
6. Combining and Reshaping Data
7. Grouping and Aggregation
8. Working with Text Data
9. Working with Time Series Data
10. Multi-level Indexing
11. Data Visualization
12. Advanced Topics and Performance
7.
Grouping and Aggregation
7.1.
GroupBy Mechanism
7.1.1.
Splitting Data into Groups
7.1.1.1.
Grouping by Single Column
7.1.1.2.
Grouping by Multiple Columns
7.1.1.3.
Grouping by Index
7.1.2.
Applying Functions to Groups
7.1.2.1.
Aggregation Functions
7.1.2.2.
Transformation Functions
7.1.2.3.
Filtration Functions
7.1.3.
Combining Results
7.2.
Aggregation Operations
7.2.1.
agg() Method
7.2.1.1.
Using Built-in Functions
7.2.1.2.
Using Custom Functions
7.2.1.3.
Applying Multiple Functions
7.2.1.4.
Different Functions to Different Columns
7.3.
Common Aggregation Functions
7.3.1.
count()
7.3.2.
sum()
7.3.3.
mean()
7.3.4.
median()
7.3.5.
std()
7.3.6.
var()
7.3.7.
min()
7.3.8.
max()
7.3.9.
first()
7.3.10.
last()
7.4.
Transformation Operations
7.4.1.
transform() Method
7.4.2.
Broadcasting Transformed Values
7.5.
Filtration Operations
7.5.1.
filter() Method
7.5.2.
Filtering Groups Based on Criteria
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6. Combining and Reshaping Data
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8. Working with Text Data