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
6.
Combining and Reshaping Data
6.1.
Concatenating DataFrames
6.1.1.
concat() Function
6.1.1.1.
Concatenating Along Rows
6.1.1.2.
Concatenating Along Columns
6.1.1.3.
Handling Indexes During Concatenation
6.1.2.
append() Method
6.1.2.1.
Appending Rows
6.1.2.2.
Differences Between append() and concat()
6.2.
Merging and Joining DataFrames
6.2.1.
Database-style Joins
6.2.1.1.
merge() Function
6.2.1.2.
Inner Join
6.2.1.3.
Left Join
6.2.1.4.
Right Join
6.2.1.5.
Outer Join
6.2.1.6.
Merging on Multiple Keys
6.2.1.7.
Handling Overlapping Column Names
6.2.2.
Index-based Joining
6.2.2.1.
join() Method
6.2.2.2.
Joining DataFrames by Index
6.3.
Reshaping DataFrames
6.3.1.
Melting Data
6.3.1.1.
melt() Function
6.3.2.
Pivoting Data
6.3.2.1.
pivot() Function
6.3.2.2.
pivot_table() Function
6.3.3.
Stacking and Unstacking
6.3.3.1.
stack() Method
6.3.3.2.
unstack() Method
6.3.4.
Transposing DataFrames
6.3.4.1.
transpose() Method
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5. Data Cleaning and Preparation
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7. Grouping and Aggregation