R For Data Science

Author: Hadley Wickham
Publisher: "O'Reilly Media, Inc."
ISBN: 1491910364
Size: 14.69 MB
Format: PDF, ePub, Mobi
View: 5661
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"This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience"--

Using R For Data Analysis In Social Sciences

Author: Quan Li
Publisher: Oxford University Press
ISBN: 0190656239
Size: 52.54 MB
Format: PDF
View: 1568
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Statistical analysis is common in the social sciences, and among the more popular programs is R. This book provides a foundation for undergraduate and graduate students in the social sciences on how to use R to manage, visualize, and ...

Python For R Users

Author: Ajay Ohri
Publisher: John Wiley & Sons
ISBN: 1119126762
Size: 40.51 MB
Format: PDF, ePub, Mobi
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The definitive guide for statisticians and data scientists who understand the advantages of becoming proficient in both R and Python The first book of its kind, Python for R Users: A Data Science Approach makes it easy for R programmers to ...

Big Data Analytics With R

Author: Simon Walkowiak
Publisher: Packt Publishing Ltd
ISBN: 1786463725
Size: 76.54 MB
Format: PDF, ePub
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In this section, we will merely focus on a small fraction of selected topics in data
science using the R language. ... In the same way you exported R objects to
external files on your hard drive, you can just as easily import data into R from
almost ...

Applied Spatial Data Analysis With R

Author: Roger S. Bivand
Publisher: Springer Science & Business Media
ISBN: 1461476186
Size: 55.14 MB
Format: PDF, Mobi
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This book will be of interest to researchers who intend to use R to handle, visualise, and analyse spatial data.

Practical Data Science Cookbook

Author: Prabhanjan Tattar
Publisher: Packt Publishing Ltd
ISBN: 178712326X
Size: 77.70 MB
Format: PDF, Mobi
View: 1910
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Factors are the names for R's categorical datatype, which can be thought of as a
label or tag applied to the data. Internally, R ... In this case, R might import the
column of data as factors, which is often not what was intended by the data
scientist.

Data Science In R

Author: Deborah Nolan
Publisher: CRC Press
ISBN: 1482234823
Size: 71.59 MB
Format: PDF
View: 1300
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How do we read the contents of the files into R in a more general, automated,
machineindependent manner? And, is readLines() the function we should use?
Let's address the second question first. The manual, R Data Import/Export [3] ...

R Data Science Essentials

Author: Raja B. Koushik
Publisher: Packt Publishing Ltd
ISBN: 1785286366
Size: 59.60 MB
Format: PDF, ePub, Docs
View: 6886
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Importing data to R is quite simple and can be done from multiple sources. The
most common method of importing data to R is through the comma-separated
values (CSV) format. The CSV data can be accessed through the read.csv
function.