Data Science Fundamentals with R, Python, and Open Data
eBook - PDF

Data Science Fundamentals with R, Python, and Open Data

Marco Cremonini

Share book
  1. English
  2. PDF
  3. Available on iOS & Android
eBook - PDF

Data Science Fundamentals with R, Python, and Open Data

Marco Cremonini

Book details
Table of contents
Citations

About This Book

Data Science Fundamentals with R, Python, and Open Data

Introduction to essential concepts and techniques of the fundamentals of R and Python needed to start data science projects

Organized with a strong focus on open data, Data Science Fundamentals with R, Python, and Open Data discusses concepts, techniques, tools, and first steps to carry out data science projects, with a focus on Python and RStudio, reflecting a clear industry trend emerging towards the integration of the two. The text examines intricacies and inconsistencies often found in real data, explaining how to recognize them and guiding readers through possible solutions, and enables readers to handle real data confidently and apply transformations to reorganize, indexing, aggregate, and elaborate.

This book is full of reader interactivity, with a companion website hosting supplementary material including datasets used in the examples and complete running code (R scripts and Jupyter notebooks) of all examples. Exam-style questions are implemented and multiple choice questions to support the readers' active learning. Each chapter presents one or more case studies.

Written by a highly qualified academic, Data Science Fundamentals with R, Python, and Open Data discuss sample topics such as:

  • Data organization and operations on data frames, covering reading CSV dataset and common errors, and slicing, creating, and deleting columns in R
  • Logical conditions and row selection, covering selection of rows with logical condition and operations on dates, strings, and missing values
  • Pivoting operations and wide form-long form transformations, indexing by groups with multiple variables, and indexing by group and aggregations
  • Conditional statements and iterations, multicolumn functions and operations, data frame joins, and handling data in list/dictionary format

Data Science Fundamentals with R, Python, and Open Data is a highly accessible learning resource for students from heterogeneous disciplines where Data Science and quantitative, computational methods are gaining popularity, along with hard sciences not closely related to computer science, and medical fields using stochastic and quantitative models.

Frequently asked questions

How do I cancel my subscription?
Simply head over to the account section in settings and click on “Cancel Subscription” - it’s as simple as that. After you cancel, your membership will stay active for the remainder of the time you’ve paid for. Learn more here.
Can/how do I download books?
At the moment all of our mobile-responsive ePub books are available to download via the app. Most of our PDFs are also available to download and we're working on making the final remaining ones downloadable now. Learn more here.
What is the difference between the pricing plans?
Both plans give you full access to the library and all of Perlego’s features. The only differences are the price and subscription period: With the annual plan you’ll save around 30% compared to 12 months on the monthly plan.
What is Perlego?
We are an online textbook subscription service, where you can get access to an entire online library for less than the price of a single book per month. With over 1 million books across 1000+ topics, we’ve got you covered! Learn more here.
Do you support text-to-speech?
Look out for the read-aloud symbol on your next book to see if you can listen to it. The read-aloud tool reads text aloud for you, highlighting the text as it is being read. You can pause it, speed it up and slow it down. Learn more here.
Is Data Science Fundamentals with R, Python, and Open Data an online PDF/ePUB?
Yes, you can access Data Science Fundamentals with R, Python, and Open Data by Marco Cremonini in PDF and/or ePUB format, as well as other popular books in Ciencia de la computación & Minería de datos. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Wiley
Year
2024
ISBN
9781394213252

Table of contents