# r for data analysis in easy steps

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## R For Data Analysis In Easy Steps R Programming Essentials

**Author :**Mike McGrath

**ISBN :**1840787953

**Genre :**Data mining

**File Size :**79. 40 MB

**Format :**PDF, ePub, Docs

**Download :**818

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R for Data Analysis in easy steps is written using a proven easy-to-follow style for maximum appeal. It will be useful to anyone who wants to begin programming in R, with minimum fuss.

## R For Data Analysis In Easy Steps

**Author :**Mike McGrath

**ISBN :**9781840788150

**Genre :**Computers

**File Size :**44. 1 MB

**Format :**PDF, Kindle

**Download :**357

**Read :**699

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 has an easy-to-follow style that will appeal to anyone who wants to produce graphic visualizations to gain insights from gathered data. R for Data Analysis in easy steps begins by explaining core programming principles of the R programming language, which stores data in “vectors” from which simple graphs can be plotted. Next, the book 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 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. Contents: Getting started Storing values Performing operations Testing conditions Employing functions Building matrices Constructing data frames Producing quick plots Telling stories with data Plotting perfection

## Exam Prep For R For Data Analysis In Easy Steps

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**File Size :**85. 13 MB

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## R For Data Science

**Author :**Hadley Wickham

**ISBN :**9781491910368

**Genre :**Computers

**File Size :**73. 99 MB

**Format :**PDF, ePub, Mobi

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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"--

## Get Going With Amazon Echo And Alexa In Easy Steps

**Author :**Nick Vandome

**ISBN :**9781840788266

**Genre :**Computers

**File Size :**45. 32 MB

**Format :**PDF, Kindle

**Download :**609

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## Python In Easy Steps 2nd Edition

**Author :**Mike McGrath

**ISBN :**9781840788365

**Genre :**Computers

**File Size :**70. 95 MB

**Format :**PDF, Kindle

**Download :**535

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Python in easy steps, 2nd edition instructs you how to program in the powerful Python language, giving complete examples that illustrate each aspect with colorized source code. Python in easy steps, 2nd edition begins by explaining how to install the free Python interpreter so you can quickly begin to create your own executable programs by copying the book's examples. It demonstrates all the Python language basics before moving on to provide examples of Object Oriented Programming (OOP) and CGI scripting to handle web form data. The book concludes by demonstrating how you can use your acquired knowledge to create and deploy graphical windowed applications. Python in easy steps, 2nd edition makes no assumption you have previous knowledge of any programming language so it's ideal for the newcomer to computer programming. It has an easy-to-follow style that will appeal to programmers moving from another programming language, and to the student who is studying Python programming at school or college, and to those seeking a career in computing who need a fundamental understanding of computer programming. The Python 3.x language is under active development so frequent new releases are made available as small improvements are added to the language and Python in easy steps, 2nd edition features the very latest versions of Python at the time of publication. Python development is one of evolution, rather than revolution, so the examples provided in the book can be used in subsequent releases – simply download the latest version of Python then follow the easy steps. Python is the language used to program the Raspberry Pi - covered by Raspberry Pi in easy steps and Raspberry Pi 3 in easy steps. This second edition is updated to cover Python 3.7.

## Bash In Easy Steps

**Author :**Mike McGrath

**ISBN :**9781840788563

**Genre :**Computers

**File Size :**75. 91 MB

**Format :**PDF, ePub, Mobi

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The "Bourne Again SHell" (Bash) is a powerful command-line shell interface that lets you communicate directly with the kernel at the heart of a computer’s operating system for total control. Bash is the default shell for Unix-based operating systems Linux, Mac OS X, and Raspbian on Raspberry Pi devices, and is also available to Windows users on the Windows Subsystem for Linux (WSL) . This book will show you how to use the Bash command-line interface and how to employ Bash's programming abilities. Complete examples illustrate each aspect with colorized source code and full-color screenshots depict the actual output. Bash in easy steps begins by demonstrating Bash commands for system navigation and file manipulation so you will quickly become familiar with the command-line interface. It explains all the BASH basics before moving on to describe advanced features such as command history, command-line editing, and environment customization. The book then introduces Bash programming with examples of flow control, command switches, input/output, and debugging - allowing you to create your own executable programs by copying the examples. Bash in easy steps has an easy-to-follow style that will appeal to: · Users who are completely new to Unix-based operating systems · Casual users who wish to expand their knowledge of their computer system · Those who would like to learn coding skills by writing useful shell scripts · The student who is studying programming at school or college · Those seeking a career in computing and need a fundamental understanding of the BASH interpreter on Unix-based operating systems Table of Contents: Getting Started Managing Files Handling Text Editing Commands Customizing Environment Controlling Behavior Performing Operations Directing Flow Employing Functions Handy Reference

## Electronics In Easy Steps

**Author :**Bill Mantovani

**ISBN :**9781840788877

**Genre :**Technology & Engineering

**File Size :**46. 82 MB

**Format :**PDF, ePub, Docs

**Download :**651

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Ever wanted to know how things work, especially electronic devices? Electronics in easy steps tells you all about the building blocks that make up electronic circuits and the components that make an electronic device tick. It explains electronics in an easy to understand way and then takes you through some simple but useful circuits that you can build for yourself. Areas covered include: · the basic fundamentals of electricity · getting started in electronics · electronic theory explained · resistors and capacitors – what they do · transistors – how they work · crystals and coils · basic electronic building blocks · simple circuits described and explained · how a radio works · designing simple circuits · circuit design software · making printed circuit boards · building electronic circuits · soldering techniques · test equipment · circuit testing and fault finding Electronics in easy steps is ideal for anyone who has always wanted to know how electricity works and what electronic components do – from simple theory through to actually building, testing and troubleshooting useful and interesting circuits. Suitable for: · Students · DIY and Electronics Enthusiasts · Hobbyists · Radio Hobbyists · Short Wave Listeners and Radio Amateur Foundation Exam students · Members of the Cadets, Scouts, etc. and anyone with an inquisitive mind who wants to know how electricity and electronics works!

## Using R For Data Analysis In Social Sciences

**Author :**Quan Li

**ISBN :**9780190656218

**Genre :**Business & Economics

**File Size :**55. 42 MB

**Format :**PDF, Kindle

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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 analyze data. The focus is on how to address substantive questions with data analysis and replicate published findings. Using R for Data Analysis in Social Sciences adopts a minimalist approach and covers only the most important functions and skills in R to conduct reproducible research. It emphasizes the practical needs of students using R by showing how to import, inspect, and manage data, understand the logic of statistical inference, visualize data and findings via histograms, boxplots, scatterplots, and diagnostic plots, and analyze data using one-sample t-test, difference-of-means test, covariance, correlation, ordinary least squares (OLS) regression, and model assumption diagnostics. It also demonstrates how to replicate the findings in published journal articles and diagnose model assumption violations. Because the book integrates R programming, the logic and steps of statistical inference, and the process of empirical social scientific research in a highly accessible and structured fashion, it is appropriate for any introductory course on R, data analysis, and empirical social-scientific research.

## Learn R Programming In 1 Day

**Author :**Krishna Rungta

**ISBN :**

**Genre :**Computers

**File Size :**45. 64 MB

**Format :**PDF, ePub

**Download :**728

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R is a programming language developed is widely used for statistical and graphical analysis. It can execute advance machine learning algorithms including earning algorithm, linear regression, time series, statistical inference. R programming language is used by Fortune 500 companies and tech bellwethers like Uber, Google, Airbnb, Facebook, Apple. R provides a data scientist tools and libraries (Dplyr) to perform the 3 steps of analysis 1) Extract 2) Transform, Cleanse 3) Analyze. Table of Contents Chapter 1: What is R Programming Language? Introduction & Basics Chapter 2: How to Download & Install R, RStudio, Anaconda on Mac or Windows Chapter 3: R Data Types, Arithmetic & Logical Operators with Example Chapter 4: R Matrix Tutorial: Create, Print, add Column, Slice Chapter 5: Factor in R: Categorical & Continuous Variables Chapter 6: R Data Frame: Create, Append, Select, Subset Chapter 7: List in R: Create, Select Elements with Example Chapter 8: R Sort a Data Frame using Order() Chapter 9: R Dplyr Tutorial: Data Manipulation(Join) & Cleaning(Spread) Chapter 10: Merge Data Frames in R: Full and Partial Match Chapter 11: Functions in R Programming (with Example) Chapter 12: IF, ELSE, ELSE IF Statement in R Chapter 13: For Loop in R with Examples for List and Matrix Chapter 14: While Loop in R with Example Chapter 15: apply(), lapply(), sapply(), tapply() Function in R with Examples Chapter 16: Import Data into R: Read CSV, Excel, SPSS, Stata, SAS Files Chapter 17: How to Replace Missing Values(NA) in R: na.omit & na.rm Chapter 18: R Exporting Data to Excel, CSV, SAS, STATA, Text File Chapter 19: Correlation in R: Pearson & Spearman with Matrix Example Chapter 20: R Aggregate Function: Summarise & Group_by() Example Chapter 21: R Select(), Filter(), Arrange(), Pipeline with Example Chapter 22: Scatter Plot in R using ggplot2 (with Example) Chapter 23: How to make Boxplot in R (with EXAMPLE) Chapter 24: Bar Chart & Histogram in R (with Example) Chapter 25: T Test in R: One Sample and Paired (with Example) Chapter 26: R ANOVA Tutorial: One way & Two way (with Examples) Chapter 27: R Simple, Multiple Linear and Stepwise Regression [with Example] Chapter 28: Decision Tree in R with Example Chapter 29: R Random Forest Tutorial with Example Chapter 30: Generalized Linear Model (GLM) in R with Example Chapter 31: K-means Clustering in R with Example Chapter 32: R Vs Python: What's the Difference? Chapter 33: SAS vs R: What's the Difference?