Pandas in 7 Days: Utilize Python to Manipulate Data, Conduct Scientific Computing, Time Series Analysis, and Exploratory Data Analysis by Fabio Nelli [Paperback]
PRODUCT DETAILS
"Pandas in 7 Days: Utilize Python to Manipulate Data, Conduct Scientific Computing, Time Series Analysis, and Exploratory Data Analysis" by Fabio Nelli is a practical paperback guide designed to help readers quickly master data manipulation and analysis using the Pandas library in Python.
Key features of the book include:
1. **Comprehensive Coverage**: The book covers essential topics such as data manipulation, scientific computing, time series analysis, and exploratory data analysis (EDA) using Pandas.
2. **Hands-on Approach**: Each chapter is structured to provide practical exercises and examples that reinforce learning and allow readers to apply Pandas functions in real-world scenarios.
3. **Scientific Computing**: Focuses on using Pandas for scientific computing tasks, including data aggregation, transformation, and cleaning.
4. **Time Series Analysis**: Covers techniques for handling time series data using Pandas, such as date/time indexing, resampling, and time-based operations.
5. **Exploratory Data Analysis (EDA)**: Discusses how to perform EDA using Pandas, including summary statistics, data visualization with Matplotlib and Seaborn, and identifying patterns and relationships in data.
6. **Python Integration**: Demonstrates how Pandas integrates with other Python libraries and tools for data analysis and visualization.
"Pandas in 7 Days" is suitable for beginners and intermediate-level Python programmers who want to enhance their skills in data manipulation and analysis using Pandas. It serves as a practical guide for anyone working with data, including data scientists, analysts, researchers, and students.
By the end of the book, readers will have a solid understanding of how to leverage Pandas to manipulate and analyze data effectively, conduct scientific computations, perform time series analysis, and gain insights through exploratory data analysis.
This book aims to empower readers to become proficient in using Pandas for data-driven tasks, enabling them to tackle complex data challenges with confidence and efficiency.