Learning Data Analysis with R [Video]

Preview in Mapt

Learning Data Analysis with R [Video]

Fabio Veronesi

Find, process, analyze, manipulate, and crunch data in R
Mapt Subscription
FREE
$29.99/m after trial
Video
$106.25
RRP $124.99
Save 14%
What do I get with a Mapt Pro subscription?
  • Unlimited access to all Packt’s 5,000+ eBooks and Videos
  • Early Access content, Progress Tracking, and Assessments
  • 1 Free eBook or Video to download and keep every month after trial
What do I get with an eBook?
  • Download this book in EPUB, PDF, MOBI formats
  • DRM FREE - read and interact with your content when you want, where you want, and how you want
  • Access this title in the Mapt reader
What do I get with Print & eBook?
  • Get a paperback copy of the book delivered to you
  • Download this book in EPUB, PDF, MOBI formats
  • DRM FREE - read and interact with your content when you want, where you want, and how you want
  • Access this title in the Mapt reader
What do I get with a Video?
  • Download this Video course in MP4 format
  • DRM FREE - read and interact with your content when you want, where you want, and how you want
  • Access this title in the Mapt reader
$0.00
$106.25
$29.99p/m after trial
RRP $124.99
Subscription
Video
Start 30 Day Trial

Frequently bought together


Learning Data Analysis with R [Video] Book Cover
Learning Data Analysis with R [Video]
$ 124.99
$ 106.25
Mastering Data Analysis with R [Video] Book Cover
Mastering Data Analysis with R [Video]
$ 124.99
$ 106.25
Buy 2 for $35.00
Save $214.98
Add to Cart
Subscribe and access every Packt eBook & Video.
 
  • 5,000+ eBooks & Videos
  • 50+ New titles a month
  • 1 Free eBook/Video to keep every month
Start Free Trial
 

Video Details

ISBN 139781785889868
Course Length6 hours 07 minutes

Video Description

R is a programming language and software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing. The R language is widely used among statisticians and data miners for developing statistical software and data analysis.

This video delivers viewers the ability to conduct data analysis in practical contexts with R, using core language packages and tools. The end goal is to provide analysts and data scientists a comprehensive learning course on how to manipulate and analyse small and large sets of data with R. It will introduce how CRAN works and will demonstrate why viewers should use them.

You will start with the most basic importing techniques, to downloading compressed data from the web and learn of more advanced ways to handle even the most difficult datasets to import. Next, you will move on to create static plots, while the second will show how to plot spatial data on interactive web platforms such as Google Maps and Open Street maps. Finally, you will learn to implement your learning with real-world examples of data analysis.

This video will lay the foundations for deeper applications of data analysis, and pave the way for advanced data science.

Style and Approach

In this practical video, you will learn to perform a range of data analysis tasks along with real world data sets. This video delivers viewers the ability to conduct data analysis in practical contexts with R, using core language packages and tools.

The overall vision of this video is structured as a series of practical tutorials which cover single tasks, with their appropriate R packages, in detail.

Table of Contents

Importing Data in Table Format
The Course Overview
Importing Data from Tables (read.table)
Downloading Open Data from FTP Sites
Fixed-Width Format
Importing with read.lines (The Last Resort)
Cleaning Your Data
Handling the Temporal Component
Loading the Required Packages
Importing Vector Data (ESRI shp and GeoJSON)
Transforming from data.frame to SpatialPointsDataFrame
Understanding Projections
Basic time/dates formats
Importing Raster Data
Introducing the Raster Format
Reading Raster Data
Mosaicking
Stacking to Include the Temporal Component
Exporting Data
Exporting Data in Tables
Exporting Vector Data (ESRI shp File)
Exporting Rasters in Various Formats (GeoTIFF, ASCII Grids)
Exporting Data for WebGIS Systems (GeoJSON, KML)
Descriptive Statistics
Preparing the Dataset
Measuring Spread (Standard Deviation and Standard Distance)
Understanding Your Data with Plots
Plotting for Multivariate Data
Finding Outliers
Manipulating Vector Data
Introduction
Re-Projecting Your Data
Intersection
Buffer and Distance
Union and Overlay
Manipulating Raster Data
Introduction
Converting Vector/Table Data into Raster
Subsetting and Selection
Filtering
Raster Calculator
Visualizing Spatial Data
Plotting Basics
Adding Layers
Color Scale
Creating Multivariate Plots
Handling the Temporal Component
Interactive Maps
Introduction
Plotting Vector Data on Google Maps
Adding Layers
Plotting Raster Data on Google Maps
Using Leaflet to Plot on Open Street Maps
Creating Global Economic Maps with Open Data
Introduction
Importing Data from the World Bank
Adding Geocoding Information
Concluding Remarks
Point Pattern Analysis of Crime in the UK
Theoretical Background
Introduction
Intensity and Density
Spatial Distribution
Modelling
Cluster Analysis of Earthquake Data
Theoretical Background
Data Preparation
K-Means Clustering
Optimal Number of Clusters
Hierarchical Clustering
Concluding
Time Series Analysis of Wind Speed Data
Theoretical Background
Reading Time-Series in R
Subsetting and Temporal Functions
Decomposition and Correlation
Forecasting
Geostatistics
Theoretical Background
Data Preparation
Mapping with Deterministic Estimators
Analyzing Trend and Checking Normality
Variogram Analysis
Mapping with kriging
Regression and Statistical Learning
Theoretical Background
Dataset
Linear Regression
Regression Trees
Support Vector Machines

What You Will Learn

  • Import and export data in various formats in R
  • Perform advanced statistical data analysis
  • Visualize your data on Google or Open Street maps
  • Enhance your data analysis skills and learn to handle even the most complex datasets
  • Learn how to handle vector and raster data in R

Authors

Table of Contents

Importing Data in Table Format
The Course Overview
Importing Data from Tables (read.table)
Downloading Open Data from FTP Sites
Fixed-Width Format
Importing with read.lines (The Last Resort)
Cleaning Your Data
Handling the Temporal Component
Loading the Required Packages
Importing Vector Data (ESRI shp and GeoJSON)
Transforming from data.frame to SpatialPointsDataFrame
Understanding Projections
Basic time/dates formats
Importing Raster Data
Introducing the Raster Format
Reading Raster Data
Mosaicking
Stacking to Include the Temporal Component
Exporting Data
Exporting Data in Tables
Exporting Vector Data (ESRI shp File)
Exporting Rasters in Various Formats (GeoTIFF, ASCII Grids)
Exporting Data for WebGIS Systems (GeoJSON, KML)
Descriptive Statistics
Preparing the Dataset
Measuring Spread (Standard Deviation and Standard Distance)
Understanding Your Data with Plots
Plotting for Multivariate Data
Finding Outliers
Manipulating Vector Data
Introduction
Re-Projecting Your Data
Intersection
Buffer and Distance
Union and Overlay
Manipulating Raster Data
Introduction
Converting Vector/Table Data into Raster
Subsetting and Selection
Filtering
Raster Calculator
Visualizing Spatial Data
Plotting Basics
Adding Layers
Color Scale
Creating Multivariate Plots
Handling the Temporal Component
Interactive Maps
Introduction
Plotting Vector Data on Google Maps
Adding Layers
Plotting Raster Data on Google Maps
Using Leaflet to Plot on Open Street Maps
Creating Global Economic Maps with Open Data
Introduction
Importing Data from the World Bank
Adding Geocoding Information
Concluding Remarks
Point Pattern Analysis of Crime in the UK
Theoretical Background
Introduction
Intensity and Density
Spatial Distribution
Modelling
Cluster Analysis of Earthquake Data
Theoretical Background
Data Preparation
K-Means Clustering
Optimal Number of Clusters
Hierarchical Clustering
Concluding
Time Series Analysis of Wind Speed Data
Theoretical Background
Reading Time-Series in R
Subsetting and Temporal Functions
Decomposition and Correlation
Forecasting
Geostatistics
Theoretical Background
Data Preparation
Mapping with Deterministic Estimators
Analyzing Trend and Checking Normality
Variogram Analysis
Mapping with kriging
Regression and Statistical Learning
Theoretical Background
Dataset
Linear Regression
Regression Trees
Support Vector Machines

Video Details

ISBN 139781785889868
Course Length6 hours 07 minutes
Read More

Read More Reviews

Recommended for You

Mastering Data Analysis with R [Video] Book Cover
Mastering Data Analysis with R [Video]
$ 124.99
$ 106.25
R Data Analysis Solution - Analyzing Time-Series and Social Media Data, and More [Video] Book Cover
R Data Analysis Solution - Analyzing Time-Series and Social Media Data, and More [Video]
$ 124.99
$ 106.25
R Data Analysis Solutions - Machine Learning Techniques [Video] Book Cover
R Data Analysis Solutions - Machine Learning Techniques [Video]
$ 124.99
$ 106.25
Learning Data Mining with R [Video] Book Cover
Learning Data Mining with R [Video]
$ 84.99
$ 72.25
Data Analysis with Pandas and Python [Video] Book Cover
Data Analysis with Pandas and Python [Video]
$ 39.99
$ 34.00
Mastering Python Data Analysis with Pandas [Video] Book Cover
Mastering Python Data Analysis with Pandas [Video]
$ 124.99
$ 106.25