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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
Data Loading and Saving
Reading Data from Files
CSV Files
read_csv() Function
Handling Delimiters
Specifying Column Names
Handling Missing Values
Reading Large Files in Chunks
Excel Files
read_excel() Function
Reading Specific Sheets
Reading Multiple Sheets
JSON Files
read_json() Function
Orient Options
Handling Nested JSON
HTML Tables
read_html() Function
Parsing Multiple Tables
Clipboard Data
read_clipboard() Function
Fixed-Width Format Files
read_fwf() Function
Parquet Files
read_parquet() Function
Feather Files
read_feather() Function
Writing Data to Files
CSV Files
to_csv() Method
Customizing Delimiters
Handling Index and Headers
Excel Files
to_excel() Method
Writing Multiple Sheets
JSON Files
to_json() Method
Orient Options
HTML Files
to_html() Method
Parquet Files
to_parquet() Method
Feather Files
to_feather() Method
Database Interactions
Reading from SQL Databases
read_sql() Function
Using SQLAlchemy
Reading with SQL Queries
Writing to SQL Databases
to_sql() Method
Appending vs Replacing Data
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4. Indexing and Data Selection