Atnaujinkite slapukų nuostatas

El. knyga: R for Data Analysis in easy steps, 2nd edition

3.95/5 (20 ratings by Goodreads)
  • Formatas: 192 pages
  • Serija: In Easy Steps
  • Išleidimo metai: 05-Jun-2023
  • Leidėjas: In Easy Steps Limited
  • ISBN-13: 9781787910027
  • Formatas: 192 pages
  • Serija: In Easy Steps
  • Išleidimo metai: 05-Jun-2023
  • Leidėjas: In Easy Steps Limited
  • ISBN-13: 9781787910027

DRM apribojimai

  • Kopijuoti:

    neleidžiama

  • Spausdinti:

    neleidžiama

  • El. knygos naudojimas:

    Skaitmeninių teisių valdymas (DRM)
    Leidykla pateikė šią knygą šifruota forma, o tai reiškia, kad norint ją atrakinti ir perskaityti reikia įdiegti nemokamą programinę įrangą. Norint skaityti šią el. knygą, turite susikurti Adobe ID . Daugiau informacijos  čia. El. knygą galima atsisiųsti į 6 įrenginius (vienas vartotojas su tuo pačiu Adobe ID).

    Reikalinga programinė įranga
    Norint skaityti šią el. knygą mobiliajame įrenginyje (telefone ar planšetiniame kompiuteryje), turite įdiegti šią nemokamą programėlę: PocketBook Reader (iOS / Android)

    Norint skaityti šią el. knygą asmeniniame arba „Mac“ kompiuteryje, Jums reikalinga  Adobe Digital Editions “ (tai nemokama programa, specialiai sukurta el. knygoms. Tai nėra tas pats, kas „Adobe Reader“, kurią tikriausiai jau turite savo kompiuteryje.)

    Negalite skaityti šios el. knygos naudodami „Amazon Kindle“.

The R language is widely used by statisticians for data analysis, and the popularity of R programming has therefore increased substantially in recent years. The emerging Internet of Things (IoT) gathers increasing amounts of data that can be analyzed to gain useful insights into trends.

R for Data Analysis in easy steps, 2nd edition has an easy-to-follow style that will appeal to anyone who wants to produce graphic visualizations to gain insights from gathered data. The book begins by explaining core programming principles of the R programming language, which stores data in “vectors” from which simple graphs can be plotted. Next, it describes how to create “matrices” to store and manipulate data from which graphs can be plotted to provide better insights. This book then demonstrates how to create “data frames” from imported data sets, and how to employ the “Grammar of Graphics” to produce advanced visualizations that can best illustrate useful insights from your data.

R for Data Analysis in easy steps, 2nd edition contains separate chapters on the major features of the R programming language. There are complete example programs that demonstrate how to create Line graphs, Bar charts, Histograms, Scatter graphs, Box plots, and more. The code for each R script is listed, together with screenshots that illustrate the actual output when that script has been executed. The free, downloadable example R code is provided for clearer understanding. By the end of this book you will have gained a sound understanding of R programming, and be able to write your own scripts that can be executed to produce graphic visualizations for data analysis. You need have no previous knowledge of any programming language, so it's ideal for the newcomer to computer programming.

Updated for the latest version of R. 

The R language is widely used by statisticians for dataanalysis, and the popularity of R programming has therefore increasedsubstantially in recent years. The emerging Internet of Things (IoT) gathersincreasing amounts of data that can be analyzed to gain useful insights intotrends.

R for Data Analysis in easy steps, 2ndedition has an easy-to-follow style that will appealto anyone who wants to produce graphic visualizations to gain insights fromgathered data. The book begins by explaining core programming principlesof the R programming language, which stores data in “vectors” from which simplegraphs can be plotted. Next, it describes how to create “matrices” to store andmanipulate data from which graphs can be plotted to provide better insights.This book then demonstrates how to create “data frames” from imported datasets, and how to employ the “Grammar of Graphics” to produce advancedvisualizations that can best illustrate useful insights from your data.

R for Data Analysis in easy steps, 2nd edition contains separate chapters on the majorfeatures of the R programming language. There are complete example programsthat demonstrate how to create Line graphs, Bar charts, Histograms, Scattergraphs, Box plots, and more. The code for each R script is listed, togetherwith screenshots that illustrate the actual output when that script has beenexecuted. The free, downloadable example R code is provided for clearerunderstanding. By the end of this book you will have gained a sound understandingof R programming, and be able to write your own scripts that can be executed toproduce graphic visualizations for data analysis. You need have no previousknowledge of any programming language, so it's ideal for the newcomer tocomputer programming.

Updated for the latest version of R. 



R for DataAnalysis in easy steps, 2nd edition iswritten using a proven easy-to-follow style for maximum appeal. It will beuseful to anyone who wants to begin programming in R, with minimum fuss.Updated for the latest version of R. 

  1. Getting started
  2. Storing values
  3. Performing operations
  4. Testing conditions
  5. Employing functions
  6. Building matrices
  7. Constructing data frames
  8. Producing quick plots
  9. Telling stories with data
  10. Plotting perfection
Mike McGrath gained his extensive knowledge of computer languages while working as a developer contracting to companies around the world. Mike is an established In Easy Steps author with several best-selling guides to his credit