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R Data Analysis Solution – Analyzing Time-Series and Social Media Data, and More

Video Description

Master this practical approach to performing analytical operations

About This Video

  • Learn how to extract actionable information from social network data

  • Implement geospatial analysis and carry out expert data analysis

  • Present your analysis convincingly through reports and build an infrastructure to enable others to play with your data

  • In Detail

    Data analysis has recently emerged as a very important focus for a huge range of organizations and businesses. R makes detailed data analysis easier, by making advanced data exploration and insight accessible to anyone interested in learning it. This course's hands-on approach will help you perform data analysis. You will learn to perform social network analysis, to uncover hidden insights and trends from data. Later you will perform geospatial analysis to bring data into action with the easy-to-follow examples featured in the video course. By the end of this course, you will mastered quickly adapting the example code for your own needs, thus saving yourself the time-consuming task of constructing code from scratch.

    Table of Contents

    1. Chapter 1 : Lessons from History - Time Series Analysis
      1. The Course Overview 00:03:48
      2. Creating and Examining Date Objects 00:03:57
      3. Operating On Date Objects 00:02:58
      4. Performing Preliminary Analyses on Time Series Data 00:02:39
      5. Using Time Series Objects 00:04:31
      6. Decomposing Time Series 00:02:45
      7. Filtering the Time Series Data 00:01:36
      8. Smoothing and Forecasting Using the Holt-Winters Method 00:02:14
      9. Building an Automated ARIMA Model 00:02:33
    2. Chapter 2 : It's All About Your Connections – Social Network Analysis
      1. Downloading Social Network Data Using Public APIs 00:08:24
      2. Creating Adjacency Matrices and Edge Lists 00:05:22
      3. Plotting Social Network Data 00:09:47
      4. Computing Important Network Metrics 00:05:32
    3. Chapter 3 : Put Your Best Foot Forward – Document and Present Your Analysis
      1. Generating Reports of Your Data Analysis with R Markdown and knitR 00:11:04
      2. Creating Interactive Web Applications with Shiny 00:09:02
      3. Creating PDF Presentations of Your Analysis with R Presentation 00:05:04
    4. Chapter 4 : Work Smarter, Not Harder – Efficient and Elegant R Code
      1. Exploiting Vectorized Operations 00:03:59
      2. Processing Entire Rows or Columns Using the Apply Function 00:03:00
      3. Applying a Function to All the Elements of a Collection with lapply and sapply 00:03:36
      4. Applying Functions to the Subsets of a Vector 00:02:08
      5. Using the split-apply-combine Strategy with plyr 00:04:12
      6. Slicing, Dicing, and Combining Data with Data Tables 00:08:18
    5. Chapter 5 : Where in the World? – Geospatial Analysis
      1. Downloading and Plotting a Google Map of an Area 00:03:04
      2. Overlaying Data on the Downloaded Google Map 00:03:42
      3. Importing ESRI Shape Files into R 00:02:51
      4. Using the sp Package to Plot Geographic Data 00:02:17
      5. Getting Maps from the Maps Package 00:02:44
      6. Creating Spatial Data Frames from Regular Data Frames Containing Spatial and Other Data 00:01:47
      7. Creating Spatial Data Frames by Combining Regular Data Frames with Spatial Objects 00:05:52
      8. Adding Variables to an Existing Spatial Data Frame 00:02:15
    6. Chapter 6 : Playing Nice – Connecting to Other Systems
      1. Using Java Objects in R 00:07:29
      2. Using JRI to Call R Functions from Java 00:04:32
      3. Executing R Scripts from Java 00:02:40
      4. Using the XLSX Package to Connect to Excel 00:04:36
      5. Reading Data From NoSQL Databases – MongoDB 00:03:33