• Big data in R
  • 1 Introduction
  • 2 Recommended resources
    • 2.1 Resources for handling big data in R
    • 2.2 Resources for the data.table package
    • 2.3 Resources for measuring R performance
    • 2.4 Resources for PostGIS database
    • 2.5 Resources for Alteryx software
    • 2.6 Datasets
    • 2.7 Extensions
  • 3 Getting started
    • 3.1 Installing packages
    • 3.2 Loading packages
    • 3.3 Install PostGIS and Alteryx software
      • 3.3.1 Install PostGIS
      • 3.3.2 Install Alteryx
  • 4 Working with big data in R
    • 4.1 Read in CSV files
      • 4.1.1 Read one large CSV file
      • 4.1.2 Fast reading multiple EPC csv files together in R
    • 4.2 Basic larger dataset munging/wrangling
      • 4.2.1 Select columns
      • 4.2.2 Changing column names to lower case or upper case
      • 4.2.3 Filter rows based on conditions
      • 4.2.4 Add in the ID column
      • 4.2.5 Convert datatable values to uppercase
      • 4.2.6 Delete a column
      • 4.2.7 Remove Duplicates
      • 4.2.8 Write files
      • 4.2.9 Bind datasets
    • 4.3 Work with PostGIS database in R
      • 4.3.1 Write files to PostGIS
      • 4.3.2 Read files from PostGIS
    • 4.4 Measure code performance
      • 4.4.1 Measure running time of the code
      • 4.4.2 profvis- an interactive profile visualizations
    • 4.5 Execute R code in Alteryx
  • Q & A
    • Thanks for your listening!
  • Published with bookdown

Working with large datasets in R

Working with large datasets in R

Bin Chi

25/3/2021