Skip to content

Instantly share code, notes, and snippets.

View pablogf75's full-sized avatar

Pablo Garrido Fernández pablogf75

1 follower · 4 following
View GitHub Profile
@pablogf75
pablogf75 / tufte
Created February 16, 2017 12:03 — forked from abresler/tufte
Recreating Edward Tufte's New York City Weather Visualization
library(dplyr)
library(tidyr)
library(magrittr)
library(ggplot2)
"http://academic.udayton.edu/kissock/http/Weather/gsod95-current/NYNEWYOR.txt" %>%
read.table() %>% data.frame %>% tbl_df -> data
names(data) <- c("month", "day", "year", "temp")
data %>%
group_by(year, month) %>%
@pablogf75
pablogf75 / dataframe_example.R
Created April 28, 2016 07:11 — forked from shivaram/dataframe_example.R
DataFrame example in SparkR
# Download Spark 1.4 from http://spark.apache.org/downloads.html
#
# Download the nyc flights dataset as a CSV from https://s3-us-west-2.amazonaws.com/sparkr-data/nycflights13.csv
# Launch SparkR using
# ./bin/sparkR --packages com.databricks:spark-csv_2.10:1.0.3
# The SparkSQL context should already be created for you as sqlContext
sqlContext
# Java ref type org.apache.spark.sql.SQLContext id 1
@pablogf75
pablogf75 / example-r-markdown.rmd
Created March 2, 2016 17:19 — forked from jeromyanglim/example-r-markdown.rmd
Example of using R Markdown
This post examines the features of [R Markdown](http://www.rstudio.org/docs/authoring/using_markdown)
using [knitr](http://yihui.name/knitr/) in Rstudio 0.96.
This combination of tools provides an exciting improvement in usability for
[reproducible analysis](http://stats.stackexchange.com/a/15006/183).
Specifically, this post
(1) discusses getting started with R Markdown and `knitr` in Rstudio 0.96;
(2) provides a basic example of producing console output and plots using R Markdown;
(3) highlights several code chunk options such as caching and controlling how input and output is displayed;
(4) demonstrates use of standard Markdown notation as well as the extended features of formulas and tables; and
(5) discusses the implications of R Markdown.
@pablogf75
pablogf75 / StreamingKMeans.scala
Created December 4, 2015 10:11 — forked from freeman-lab/StreamingKMeans.scala
Spark Streaming + MLLib integration examples
package thunder.streaming
import org.apache.spark.{SparkConf, Logging}
import org.apache.spark.rdd.RDD
import org.apache.spark.SparkContext._
import org.apache.spark.streaming._
import org.apache.spark.streaming.dstream.DStream
import org.apache.spark.mllib.clustering.KMeansModel
import scala.util.Random.nextDouble
@pablogf75
pablogf75 / gtk_install.md
Last active August 27, 2015 05:51 — forked from sebkopf/gtk_install.md
Installation information for R with GTK on Windows/Mac OS

##Installation information for R with GTK+

###Windows Install the newest version of R. Additionally, I highly recommend R-Studio for working with R regularly (but the basic command line will work just fine for most applications). Once R is installed, you can install GTK directly from within R (details below). In short:

  1. From the R command line (e.g. in R-Studio), install the RGtk2 package by running: install.packages("RGtk2", depen=T)
    This might fail with the warning that package ‘RGtk2’ is not available (for R version xxx) if your version of R has been released very recently. If so, just run install.packages("RGtk2", depen=T, type="source") instead to install the RGtk2 package directly from its source code (this might take a few mi