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Data Analysis with Python

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  • 276 stron
  • 10 godzin czytania

Więcej o książce

This guide offers a hands-on learning experience in Python fundamentals, emphasizing its application in data analysis. It serves as an excellent starting point for beginners, providing a solid foundation in data analysis and various data science processes. Authored by an experienced data professional, the content introduces readers to essential Python libraries and scripting techniques commonly used in data analysis projects. The book covers well-known libraries such as Pandas, NumPy, and Matplotlib, demonstrating their use through practical examples. It begins with an introduction to Python programming fundamentals and progresses to numerical calculations and statistical libraries, ensuring that readers grasp essential programming concepts. Key learning outcomes include mastering core Python programming for data analysis, utilizing major data analysis and visualization libraries, and refreshing the data analysis process with live examples. Readers will also gain skills in real-time data analysis and creating simple Python scripts, as well as working with external files like Excel and CSV for data cleaning. This resource is designed for college students and data professionals eager to explore Python's data analysis capabilities, although prior knowledge of Python is beneficial.

Zakup książki

Data Analysis with Python, Rituraj Dixit

Język
Rok wydania
2022
Oprawa
(miękka)
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Tytuł
Data Analysis with Python
Język
angielski
Rok wydania
2022
Oprawa
miękka
Liczba stron
276
ISBN10
9355510659
ISBN13
9789355510655
Seria
Tagi
Opis
This guide offers a hands-on learning experience in Python fundamentals, emphasizing its application in data analysis. It serves as an excellent starting point for beginners, providing a solid foundation in data analysis and various data science processes. Authored by an experienced data professional, the content introduces readers to essential Python libraries and scripting techniques commonly used in data analysis projects. The book covers well-known libraries such as Pandas, NumPy, and Matplotlib, demonstrating their use through practical examples. It begins with an introduction to Python programming fundamentals and progresses to numerical calculations and statistical libraries, ensuring that readers grasp essential programming concepts. Key learning outcomes include mastering core Python programming for data analysis, utilizing major data analysis and visualization libraries, and refreshing the data analysis process with live examples. Readers will also gain skills in real-time data analysis and creating simple Python scripts, as well as working with external files like Excel and CSV for data cleaning. This resource is designed for college students and data professionals eager to explore Python's data analysis capabilities, although prior knowledge of Python is beneficial.