shivaram

# 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

gluc

This gist shows how to convert a nested JSON file to an R data.frame. To do this, it uses jsonlite and data.tree.

The gist contains two examples: one is a bit simpler, the second one a bit more advanced.

Example 1

In the first example, we download all the repos from Hadley Wickham's Github account from https://api.github.com/users/hadley/repos . This JSON contains a nested owner object. The code shows how to convert that in a flat data.frame in three statements:

1. line 5: download
2. line 8: convert to data.tree

andrawaag

library(SPARQL)
library(ggplot2)
library(rworldmap)

wdqs <- "https://query.wikidata.org/bigdata/namespace/wdq/sparql"
query = "PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX v: <http://www.wikidata.org/prop/statement/>

dopplershift

hfreire

# Install QEMU OSX port with ARM support
sudo port install qemu +target_arm
export QEMU=$(which qemu-system-arm)

# Dowload kernel and export location
curl -OL \
https://github.com/dhruvvyas90/qemu-rpi-kernel/blob/master/kernel-qemu-4.1.7-jessie
export RPI_KERNEL=./kernel-qemu-4.1.7-jessie

# Download filesystem and export location

JohannMG

#Setting Up AWS CodeCommit (Mac)

For all possibilities, amazon has guides here: http://docs.aws.amazon.com/codecommit/latest/userguide/setting-up.html

We chose to use HTTPS here

If git asks you to manually enter username or password it is incorrectly configured!

Similar to RSA, the AWS CLI credential-helper should be using your keys to create and send a dynamic password that updates every 15 minutes.

jcheng5

Using arbitrary Leaflet JS plugins with Leaflet for R

The Leaflet JS mapping library has lots of plugins available. The Leaflet package for R provides direct support for some, but far from all, of these plugins, by providing R functions for invoking the plugins.

If you as an R user find yourself wanting to use a Leaflet plugin that isn't directly supported in the R package, you can use the technique shown here to load the plugin yourself and invoke it using JS code.

timelyportfolio

Using arbitrary Leaflet JS plugins with Leaflet for R

The Leaflet JS mapping library has lots of plugins available. The Leaflet package for R provides direct support for some, but far from all, of these plugins, by providing R functions for invoking the plugins.

If you as an R user find yourself wanting to use a Leaflet plugin that isn't directly supported in the R package, you can use the technique shown here to load the plugin yourself and invoke it using JS code.

ericclemmons

Using <details> in GitHub

Suppose you're opening an issue and there's a lot noisey logs that may be useful.

Rather than wrecking readability, wrap it in a <details> tag!

<details>
 Summary Goes Here

gchavez2

# https://github.com/jiaaro/pydub

from pydub import AudioSegment

files_path = ''
file_name = ''

startMin = 9
startSec = 50