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Название: Learn Data Science Using Python: A Quick-Start Guide
Автор: Engy Fouda
Издательство: Apress
Год: 2024
Страниц: 190
Язык: английский
Формат: pdf (true), epub
Размер: 14.0 MB
Harness the capabilities of Python and gain the expertise need to master Data Science techniques. This step-by-step book guides you through using Python to achieve tasks related to data cleaning, statistics, and visualization. You'll start by reviewing the foundational aspects of the Data Science process. This includes an extensive overview of research points and practical applications, such as the insightful analysis of presidential elections. The journey continues by navigating through installation procedures and providing valuable insights into Python, data types, typecasting, and essential libraries like Pandas and NumPy. You'll then delve into the captivating world of data visualization. Concepts such as scatter plots, histograms, and bubble charts come alive through detailed discussions and practical code examples, unraveling the complexities of creating compelling visualizations for enhanced data understanding. For Data Analysts, data scientists, Python programmers, and software developers new to Data Science.
Автор: Engy Fouda
Издательство: Apress
Год: 2024
Страниц: 190
Язык: английский
Формат: pdf (true), epub
Размер: 14.0 MB
Harness the capabilities of Python and gain the expertise need to master Data Science techniques. This step-by-step book guides you through using Python to achieve tasks related to data cleaning, statistics, and visualization. You'll start by reviewing the foundational aspects of the Data Science process. This includes an extensive overview of research points and practical applications, such as the insightful analysis of presidential elections. The journey continues by navigating through installation procedures and providing valuable insights into Python, data types, typecasting, and essential libraries like Pandas and NumPy. You'll then delve into the captivating world of data visualization. Concepts such as scatter plots, histograms, and bubble charts come alive through detailed discussions and practical code examples, unraveling the complexities of creating compelling visualizations for enhanced data understanding. For Data Analysts, data scientists, Python programmers, and software developers new to Data Science.