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Python for Data Science: Unlock the Power of Big Data: A Beginner's Guide to Analyzing and Visualizing Data with Python
Format:
Paperback
Detalles del producto
Disponibilidad:
En stock
En stock
Peso con empaque:
0.74 kg
0.74 kg
Devolución:
Sí
Sí
Condición
Nuevo
Nuevo
Producto de:
Amazon
Amazon
Viaja desde
USA
USA
Sobre este producto
- Python for Data Science: Unlock the Power of Big Data is the ultimate beginner’s guide to using Python for analyzing and visualizing data. Whether you’re new to programming or looking to transition into the world of data science, this book will teach you the skills necessary to handle and extract meaningful insights from data using Python's powerful libraries and tools.Python has become the go-to language for data science due to its versatility, simplicity, and the extensive ecosystem of libraries such as NumPy, pandas, and Matplotlib. In this book, you'll learn how to harness Python’s capabilities to process, analyze, and visualize both small datasets and large, complex big data, helping you unlock valuable insights and make data-driven decisions.What you’ll learn in Python for Data Science:Introduction to Data Science and Python: Understand the fundamentals of data science and the essential role Python plays in the field. Learn how Python’s simplicity and wide range of libraries make it the ideal tool for data analysis.Setting Up Python for Data Science: Learn how to install Python and essential data science tools such as Jupyter notebooks, Anaconda, and Python libraries like NumPy, pandas, and Matplotlib. Get familiar with creating an efficient development environment for your data science projects.Data Structures and NumPy Basics: Master the basics of Python data structures, including lists, dictionaries, and tuples, and dive into NumPy for handling numerical data. Learn how to work with NumPy arrays, perform mathematical operations, and manipulate large datasets.Exploring and Cleaning Data with Pandas: Learn how to use pandas for data manipulation and exploration. Understand how to load, clean, filter, and transform data in various formats like CSV, Excel, and SQL. Learn how to handle missing values, outliers, and data formatting issues.Data Analysis with Python: Discover how to perform descriptive and inferential statistical analysis with Python. Learn how to summarize datasets, calculate basic statistics, and perform data aggregation and grouping to derive insights.Data Visualization with Matplotlib and Seaborn: Master data visualization techniques with Python’s powerful libraries. Learn how to create a variety of plots such as line charts, histograms, box plots, and heatmaps to visualize trends, distributions, and relationships in your data.Handling Time Series Data: Learn how to work with time series data using pandas and how to visualize trends and patterns over time. Understand how to deal with date and time formats and perform operations like resampling and time-based grouping.Machine Learning with Python: Get introduced to machine learning concepts and how to use Python libraries like Scikit-learn to apply algorithms for predictive modeling. Learn how to prepare data for machine learning, train models, evaluate their performance, and improve their accuracy.Building a Data Science Workflow: Learn how to combine all the data science techniques you've learned to build a complete data science workflow. This includes data acquisition, cleaning, analysis, visualization, and machine learning modeling, culminating in presenting your findings.By the end of Python for Data Science, you'll have the skills to perform end-to-end data analysis, from data wrangling and exploration to visualization and machine learning. This book will provide you with a strong foundation in Python and data science, empowering you to solve real-world problems and make data-driven decisions.
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U$S 43,98
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