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Learn all about Pandas

About Learn all about Pandas

Learn all about Pandas The book covers the following topics: 1 Introduction Explanation of what Pandas is and its advantages 2. Installation and Setup How to install Pandas Setting up the environment (Jupyter Notebook, IDE, etc.) 3. Pandas Fundamentals Series and DataFrame objects Indexing and selecting data Operations and transformations on data 4. Data Cleaning and Preparation Handling missing values Removing duplicates Data types and conversions Merging, joining, and concatenating data 5. Data Analysis and Exploration Grouping and aggregating data Pivot tables and cross-tabulations Time-series analysis Visualization with Pandas 6. Advanced Topics Handling large datasets Memory optimization techniques Working with multi-dimensional data Custom functions and extensions 7. Real-world Applications Case studies and examples using Pandas in various domains Best practices and tips for efficient Pandas usage

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  • Language:
  • English
  • ISBN:
  • 9798394022715
  • Binding:
  • Paperback
  • Pages:
  • 78
  • Published:
  • May 7, 2023
  • Dimensions:
  • 152x229x4 mm.
  • Weight:
  • 118 g.
Delivery: 1-2 weeks
Expected delivery: December 8, 2024

Description of Learn all about Pandas

Learn all about Pandas The book covers the following topics: 1 Introduction
Explanation of what Pandas is and its advantages 2. Installation and Setup
How to install Pandas
Setting up the environment (Jupyter Notebook, IDE, etc.) 3. Pandas Fundamentals
Series and DataFrame objects
Indexing and selecting data
Operations and transformations on data 4. Data Cleaning and Preparation
Handling missing values
Removing duplicates
Data types and conversions
Merging, joining, and concatenating data 5. Data Analysis and Exploration
Grouping and aggregating data
Pivot tables and cross-tabulations
Time-series analysis
Visualization with Pandas 6. Advanced Topics
Handling large datasets
Memory optimization techniques
Working with multi-dimensional data
Custom functions and extensions 7. Real-world Applications
Case studies and examples using Pandas in various domains
Best practices and tips for efficient Pandas usage

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