^-?([0-8]?[0-9]|90)(\.[0-9]{1,10})$
- 56.3847
- -56.387
| Degrees Minutes Seconds (DMS) | |
| 40° 26′ 46″ N 79° 58′ 56″ W | |
| 40° 26′ 46″ S 79° 58′ 56″ E | |
| 90° 0′ 0″ S 180° 0′ 0″ E | |
| 40° 26′ 45.9996″ N 79° 58′ 55.2″ E | |
| Latitudes range from 0 to 90. | |
| Longitudes range from 0 to 180. | |
| Minutes & Seconds range from 0-60 | |
| Use N, S, E or W as either the last character, | |
| which represents a compass direction North, South, East or West. |
| library(googleVis) ## Version >= 0.3.2 required | |
| library(knitr) | |
| library(markdown) | |
| library(RCurl) | |
| ## URL to the Markdown example file on github:gist | |
| gist <- "https://raw.github.com/gist/3968910/4633a98fdc5193eb7da156059d182e61ccbfd4a8/MarkdownExampleWithGoogleVis.Rmd" | |
| knitrRmd <- paste(readLines(textConnection(getURL(gist))), collapse="\n") | |
| ## Write the content of knitrRmd into a Rmd-file, knit it and convert it | |
| ## into a html output. Finally show the file with the R-help http |
| # -- Load dependencies | |
| library(tidyverse) | |
| library(stringi) | |
| library(readxl) | |
| library(rvest) | |
| # -- Prep for download | |
| # url to get data from |
| source("fast-ngrams.R") | |
| con <- file("path_to_file", "r") | |
| data <- readLines(con, encoding = 'UTF-8') | |
| close(con) | |
| data <- clean(data) | |
| onegram <- text_to_ngrams(decode(data), 1) | |
| bigram <- text_to_ngrams(decode(data), 2) | |
| trigram <- text_to_ngrams(decode(data, 3)) |
| # script stolen from http://goo.gl/YbQyAQ | |
| # install.packages("tm") | |
| # install.packages("ggplot2") | |
| # install.packages("lsa") | |
| # install.packages("scatterplot3d") | |
| #install.packages("SnowballC") | |
| #if !(require('SnowballC')) then install.packages("SnowballC") | |
| library(tm) | |
| library(ggplot2) |
| #------------------------------------------------------------ | |
| # REVOLUTION ANALYTICS WEBINAR: INTRODUCTION TO R FOR DATA MINING | |
| # February 14, 2013 | |
| # Joseph B. Rickert | |
| # Technical Marketing Manager | |
| # | |
| # BIG DATA with RevoScaleR | |
| # | |
| # Copyright: Revolution Analytics |