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
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Working with large datasets in R
Q & A
Thanks for your listening!
