R For Data Science

Author: Hadley Wickham
Publisher: "O'Reilly Media, Inc."
ISBN: 1491910364
Size: 30.54 MB
Format: PDF, Kindle
View: 6003
Download Read Online
"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"--Page 4 of cover.

Beginning Data Science In R

Author: Thomas Mailund
Publisher: Apress
ISBN: 1484226712
Size: 29.64 MB
Format: PDF, ePub, Docs
View: 3216
Download Read Online
If your package has dependencies, you have three fields you can specify them in:
Depends, Imports, and Suggests.4 With Depends, you can specify both packages
that need to be installed for your package to work and which version of R is
required for your package to work. For packages, though, it is better to use
Imports and Suggests than Depends, so use Depends only to specify which
version of Ryou need. You specify it this like: Depends: R (>= 2.10) This is saying
that you need ...

Practical Data Science Cookbook

Author: Prabhanjan Tattar
Publisher: Packt Publishing Ltd
ISBN: 178712326X
Size: 54.65 MB
Format: PDF, Docs
View: 7095
Download Read Online
Ordinal data is just like categorical data, with one exception. There is a sense of
scale or value to the data. It can be said that one value is larger than another, but
the magnitude of the difference cannot be measured. Furthermore, when
importing data into R, we often run into the situation where a column of numeric
data might contain an entry that is non-numeric. 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: 13.41 MB
Format: PDF, Kindle
View: 969
Download Read Online
Given the organization and volume of files, we cannot simply read the files into R
by writing calls such as readLines("messages/easy_ham/00006.3
ca1f399ccda5d897fecb8c57...") 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] describes several functions available to us in R for
reading input from ...

Data Science For Dummies

Author: Lillian Pierson
Publisher: John Wiley & Sons
ISBN: 1118841522
Size: 67.35 MB
Format: PDF, ePub, Mobi
View: 4526
Download Read Online
In the practice of data science, you're likely to benefit from almost any package
that specializes in multivariate analysis. If you want to carry out logistic ... you can
read about in Chapter 3.) If you want to use R to take undifferentiated data and
identify which of its factors are significant for some specific purpose, you can use
factor analysis. ... Few people enter data manually into R. Data is more often
either imported from Microsoft Excel or from a relational database. You can find
driver ...

Python For R Users

Author: Ajay Ohri
Publisher: John Wiley & Sons
ISBN: 1119126770
Size: 15.83 MB
Format: PDF, ePub, Docs
View: 2257
Download Read Online
The author has helped create a SlideShare ppt on a side‐by‐side comparison of
R and Python syntax for data science at http://www.slideshare.net/ajayohri/
python‐for‐r‐users (35000+ views). ... from rpy2.robjects.packages import importr
import rpy2.robjects as ro import pandas.rpy.common as com We can pass
commands to the R session by putting the R syntax within the ro.r() method as
strings, and we can read the R data.frame into pandas data frame with com.
load_data method.

Web And Network Data Science

Author: Thomas W. Miller
Publisher: FT Press
ISBN: 0133887642
Size: 71.73 MB
Format: PDF
View: 1440
Download Read Online
And results, although not identical between Python and R, should be very similar.
# # # # # # # prepare for Python version 3x features and functions from __future
__ import division, print_function # import packages for text processing and
machine learning import os # operating system commands import re # regular
expressions import nltk # draw on the Python natural language toolkit import
pandas as pd # DataFrame structure and operations import numpy as np # arrays
and ...

Modeling Techniques In Predictive Analytics With Python And R

Author: Thomas W. Miller
Publisher: FT Press
ISBN: 013389214X
Size: 43.56 MB
Format: PDF, ePub
View: 506
Download Read Online
A Guide to Data Science Thomas W. Miller. Exhibit 2.1. Shaking Our
Bobbleheads Yes and No (Python) # Predictive Model for Los Angeles Dodgers
Promotion and Attendance (Python) # prepare for Python version 3x features and
functions from -_future__ import division, print_function from future_builtins
import ascii, filter, hex, map, oct, zip # import packages for analysis and modeling
import pandas as pd # data frame operations from pandas. tools. rplot import
RPlot, Trellis Grid, ...

Start Programming With R

Author: Valentina Porcu
Publisher: Valentina Porcu
ISBN: 8826459363
Size: 16.27 MB
Format: PDF, Docs
View: 832
Download Read Online
This book is meant as an introduction to R and is thought to be a quick reference guide for those who want to start programming in this language.

Python For Data Science For Dummies

Author: John Paul Mueller
Publisher: John Wiley & Sons
ISBN: 1118843983
Size: 23.82 MB
Format: PDF, ePub, Docs
View: 5541
Download Read Online
See why Python works for data science — tour the data science pipeline and learn about Python's basic capabilities Get set up — install Python, download datasets and example code, and start working with numbers and logic, creating ...