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Python For Data Analysis: A Complete Beginner Guide to Wrangling & Analyzing Data Using Python (Code tutorials)
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Dip your feet into the world of data analysis by leveraging the power of the most preferred programming language for the job, Python!
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What Stands Out
Λεπτομέρειες προιόντος
| Publisher | Independently published |
| Publication date | June 17, 2020 |
| Language | English |
| Print length | 113 pages |
| ISBN-13 | 979-8654757043 |
| Item Weight | 6.2 ounces (175.77 grams) |
| Dimensions | 6 x 0.29 x 9 inches (15.2 x 0.7 x 22.9 cm) |
| Book 4 of 5 | Code tutorials |
Who Should Buy?
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Aspiring Data Analysts
Beginners looking to start a career in data analysis will find structured learning and practical examples invaluable.
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Students and Academics
Ideal for college students or researchers seeking to enhance their data handling and analytical skills using Python.
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Professionals Transitioning Careers
Individuals switching to data-focused roles will benefit from comprehensive tutorials that ease the understanding of data manipulation.
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Advanced Users
Experienced data practitioners may find the content too basic and not offering enough depth for their expertise.
ΠΕΡΙΓΡΑΦΗ ΤΟΥ ΠΡΟΪΟΝΤΟΣ
Python For Data Analysis: A Complete Beginner Guide to Wrangling & Analyzing Data Using Python (Code tutorials)
Ερωτήσεις & Απαντήσεις Πελατών
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ερώτηση:
Do I need prior programming experience to use this guide?
απάντηση: No, this guide is designed specifically for beginners with no prior programming experience. -
ερώτηση:
What tools will I learn to use for data analysis?
απάντηση: You will learn to use essential Python libraries such as Numpy, Pandas, and Matplotlib. -
ερώτηση:
Why is Python preferred for data analysis?
απάντηση: Python offers a stunning ecosystem, simplicity, and a wealth of libraries that streamline complex data sets.
Software Design, Testing & Engineering Editorial Review
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Χαρακτηριστικά & Πλεονεκτήματα
- Simplify your data analysis processes with Python's powerful tools.
- Designed for beginners, no prior programming experience required.
- Learn essential data analysis techniques using libraries like Numpy and Pandas.
- Gain insights into data wrangling and visualization with Matplotlib.
- Understand the significance of data science for business success.
- Start your journey in data analysis with a comprehensive guide.
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