Buch, Englisch, 200 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 453 g
A Beginner's Guide
Buch, Englisch, 200 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 453 g
ISBN: 978-1-032-93675-8
Verlag: Taylor & Francis Ltd
Introduction: Elevate Your Analytics with Python
In today’s data-driven world, the ability to efficiently analyze and interpret information is more crucial than ever, especially in the business sector. "Python for Excel Users: A Beginner's Guide" is tailored for business students and professionals who are proficient in Microsoft Excel but are ready to embark on their Python journey. As a powerful and versatile programming language, Python has become indispensable in data analysis. This book bridges the gap between Excel and Python by providing parallel exercises that demonstrate how Python can amplify business analytics tasks with unmatched efficiency and flexibility.
Through its side-by-side comparisons, interactive Python exercises, and a “teachable moment” approach, this guide offers a unique and intuitive learning experience. By translating familiar Excel tasks into Python’s dynamic and versatile ecosystem, you’ll not only enhance your data analysis skills but also gain confidence in programming.
Why Python?
Did you know that Python powers cutting-edge technologies like ChatGPT? Indeed, Python forms the foundation of many machine learning algorithms, including large language models (LLMs). Python is more than a programming language; it’s a tool for understanding and shaping the digital world. Despite its advanced capabilities, Python’s simple, readable syntax makes it accessible to everyone—from professional software developers to citizen developers like you. Dubbed the “language of the people,” Python is revolutionizing how we approach problem-solving and automation in the modern world.
Becoming Tomorrow’s Tech-Savvy Leaders
The leaders of tomorrow are not just visionaries—they are innovators who harness the power of technology to drive change and inspire others. This book guides you through different scenarios to help you understand the connections between business questions and analytics steps we are taking. As business students embracing Python, you’re positioning yourselves as future-ready leaders equipped to navigate and excel in the complexities of modern business.
Welcome to a journey that will elevate your analytics, expand your technological fluency, and transform you into a tech-savvy leader of the future.
Chou / Wang
Python for Excel Users jetzt bestellen!
In today’s data-driven world, the ability to efficiently analyze and interpret information is more crucial than ever, especially in the business sector. "Python for Excel Users: A Beginner's Guide" is tailored for business students and professionals who are proficient in Microsoft Excel but are ready to embark on their Python journey. As a powerful and versatile programming language, Python has become indispensable in data analysis. This book bridges the gap between Excel and Python by providing parallel exercises that demonstrate how Python can amplify business analytics tasks with unmatched efficiency and flexibility.
Through its side-by-side comparisons, interactive Python exercises, and a “teachable moment” approach, this guide offers a unique and intuitive learning experience. By translating familiar Excel tasks into Python’s dynamic and versatile ecosystem, you’ll not only enhance your data analysis skills but also gain confidence in programming.
Why Python?
Did you know that Python powers cutting-edge technologies like ChatGPT? Indeed, Python forms the foundation of many machine learning algorithms, including large language models (LLMs). Python is more than a programming language; it’s a tool for understanding and shaping the digital world. Despite its advanced capabilities, Python’s simple, readable syntax makes it accessible to everyone—from professional software developers to citizen developers like you. Dubbed the “language of the people,” Python is revolutionizing how we approach problem-solving and automation in the modern world.
Becoming Tomorrow’s Tech-Savvy Leaders
The leaders of tomorrow are not just visionaries—they are innovators who harness the power of technology to drive change and inspire others. This book guides you through different scenarios to help you understand the connections between business questions and analytics steps we are taking. As business students embracing Python, you’re positioning yourselves as future-ready leaders equipped to navigate and excel in the complexities of modern business.
Welcome to a journey that will elevate your analytics, expand your technological fluency, and transform you into a tech-savvy leader of the future.
Zielgruppe
Academic, General, and Undergraduate Core
Autoren/Hrsg.
Fachgebiete
- Wirtschaftswissenschaften Betriebswirtschaft Unternehmensfinanzen Internationales Rechnungswesen
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Programmier- und Skriptsprachen
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
- Wirtschaftswissenschaften Betriebswirtschaft Unternehmensfinanzen Controlling, Wirtschaftsprüfung, Revision
- Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik
- Wirtschaftswissenschaften Betriebswirtschaft Unternehmensfinanzen Betriebliches Rechnungswesen
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Algorithmen & Datenstrukturen
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Programmierung: Methoden und Allgemeines
- Wirtschaftswissenschaften Betriebswirtschaft Unternehmenskommunikation
Weitere Infos & Material
Preparatory Chapter Chapter 1: Data Exploration and Cleaning Chapter 2: Basic Computation Chapter 3: Aggregating Data Using Group-By and Pivot Tables Chapter 4: Data Visualization and Ranking Chapter 5: Conditional Functions and What-if Analysis Chapter 6: Record Lookup and Data Segmentation Chapter 7: Text Processing Chapter 8: Date Processing Chapter 9: Table Join and Merge
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