| # Function to get data over to PostgreSQL quickly and with minimal loss | |
| # of information due to data type conversions. | |
| # Note that I have had cases where the pipe() call returned an error due | |
| # to lack of memory. So care should be taken with this function | |
| dbWriteTable.fast <- function (conn,name,value,row.names=FALSE, | |
| overwrite=TRUE,fix.names=TRUE) { | |
| # Conform names to PostgreSQL requirements | |
| pg.names <- make.db.names(conn,names(value)) | |
| # Homework 1 - Part 1 | |
| def palindrome?(string) | |
| string = string.downcase.gsub(/\W/, '') | |
| string == string.reverse | |
| end | |
| def count_words(string) | |
| Hash[ | |
| string.downcase.scan(/\w+/). | |
| group_by{|s| s}. |
| var ClientRouter = Backbone.Router.extend({ | |
| routes: { | |
| '404': 'notfound', | |
| '500': 'error', | |
| 'auth': 'auth', | |
| 'authCallback?oauth_token=:oauth_token&oauth_verifier=:oauth_verifier': 'authCallback', | |
| '': 'defaultRoute' | |
| }, | |
| defaultRoute: function() { |
| <!DOCTYPE html> | |
| <html> | |
| <head> | |
| <meta http-equiv="Content-Type" | |
| content="text/html; charset=utf-8" /> | |
| <script src="jquery-1.7.2.min.js" ></script> | |
| <script src="handlebars-1.0.0.beta.6.js" ></script> | |
| <script src="underscore-min.js" ></script> | |
| <script src="backbone-min.js" ></script> |
| # Set JAVA_HOME, set max. memory, and load rJava library | |
| Sys.setenv(JAVA_HOME='/path/to/java_home') | |
| options(java.parameters="-Xmx2g") | |
| library(rJava) | |
| # Output Java version | |
| .jinit() | |
| print(.jcall("java/lang/System", "S", "getProperty", "java.version")) | |
| # Load RJDBC library |
| "\e[A": history-search-backward | |
| "\e[B": history-search-forward | |
| set show-all-if-ambiguous on | |
| set completion-ignore-case on |
| # www.analytikdat.cz | |
| # www.analytikdat.cz/index.php/blog/entry/r-and-postgresql-using-rpostgresql-and-sqldf | |
| # Load required libraries | |
| library("RPostgreSQL") | |
| library("sqldf") | |
| # Establish connection | |
| drv <- dbDriver("PostgreSQL") | |
| # Simple version (localhost as default) |
| # R code for basic collocation statistics on a text corpus. | |
| # Extracts LHS and RHS collocates of a word of interest | |
| # over a user-defined span. Calculates frequency of | |
| # collocates and mean distances. | |
| examp1 <- "When discussing performance with colleagues, teaching, sending a bug report or | |
| searching for guidance on mailing lists and here on SO, a reproducible example is often | |
| asked and always helpful. What are your tips for creating an excellent example? How do | |
| you paste data structures from r in a text format? What other information should you | |
| include? Are there other tricks in addition to using dput(), dump() or structure()? |
-- Firstly, remove PRIMARY KEY attribute of former PRIMARY KEY
ALTER TABLE <table_name> DROP CONSTRAINT <table_name>_pkey;-- Then change column name of your PRIMARY KEY and PRIMARY KEY candidates properly.
ALTER TABLE <table_name> RENAME COLUMN <primary_key_candidate> TO id;
| doctype html | |
| html | |
| head | |
| title My App | |
| meta name="viewport" content="width=device-width, initial-scale=1.0" | |
| = stylesheet_link_tag "application", media: 'all', 'data-turbolinks-track' => true | |
| = javascript_include_tag "application", 'data-turbolinks-track' => true | |
| = csrf_meta_tags | |
| body |