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Python for Data Science

Ocena książki

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  • 240 stron
  • 9 godzin czytania

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A hands-on, real-world introduction to data analysis with the Python programming language, loaded with wide-ranging examples.Python is an ideal choice for accessing, manipulating, and gaining insights from data of all kinds. Python for Data Science introduces you to the Pythonic world of data analysis with a learn-by-doing approach rooted in practical examples and hands-on activities. You’ll learn how to write Python code to obtain, transform, and analyze data, practicing state-of-the-art data processing techniques for use cases in business management, marketing, and decision support.You will discover Python’s rich set of built-in data structures for basic operations, as well as its robust ecosystem of open-source libraries for data science, including NumPy, pandas, scikit-learn, matplotlib, and more. Examples show how to load data in various formats, how to streamline, group, and aggregate data sets, and how to create charts, maps, and other visualizations. Later chapters go in-depth with demonstrations of real-world data applications, including using location data to power a taxi service, market basket analysis to identify items commonly purchased together, and machine learning to predict stock prices.

Zakup książki

Python for Data Science, Yuli Vasiliev

Język
Rok wydania
2022
Oprawa
(miękka)
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Metody płatności

3,9
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13 Ocena

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Tytuł
Python for Data Science
Język
angielski
Rok wydania
2022
Oprawa
miękka
Liczba stron
240
ISBN10
1718502206
ISBN13
9781718502208
Seria
Tagi
Ocena
3,9 z 5
Opis
A hands-on, real-world introduction to data analysis with the Python programming language, loaded with wide-ranging examples.Python is an ideal choice for accessing, manipulating, and gaining insights from data of all kinds. Python for Data Science introduces you to the Pythonic world of data analysis with a learn-by-doing approach rooted in practical examples and hands-on activities. You’ll learn how to write Python code to obtain, transform, and analyze data, practicing state-of-the-art data processing techniques for use cases in business management, marketing, and decision support.You will discover Python’s rich set of built-in data structures for basic operations, as well as its robust ecosystem of open-source libraries for data science, including NumPy, pandas, scikit-learn, matplotlib, and more. Examples show how to load data in various formats, how to streamline, group, and aggregate data sets, and how to create charts, maps, and other visualizations. Later chapters go in-depth with demonstrations of real-world data applications, including using location data to power a taxi service, market basket analysis to identify items commonly purchased together, and machine learning to predict stock prices.