javierluraschi

https://kafka.apache.org/quickstart

wget http://apache.claz.org/kafka/2.1.0/kafka_2.12-2.1.0.tgz
tar -xzf kafka_2.12-2.1.0.tgz

bin/zookeeper-server-start.sh config/zookeeper.properties
bin/kafka-server-start.sh config/server.properties

bin/kafka-topics.sh --create --zookeeper localhost:2181 --replication-factor 1 --partitions 1 --topic test

javierluraschi

Building Arrow R Bindings in Windows

This doc captures results from investigating how to build the Arrow R bindings in Windows. The following options were explored:

• Building Arrow in MSys and bindings in RTools.
• Building Arrow and bindings in RTools.

The most promising long-term solution is to write a CMake generator that can be run from RTools; short term, we can continue making progress compiling Arrow from MSys.

This document explains other approaches considered and provides additional details.

javierluraschi

A script to demonstrate using TensorFlow in Spark with Amazon EMR and sparklyr.

1. Create an EMR cluster for sparklyr, connect to EMR and install required tools:

install.packages(tensorflow)
devtools::install_github("rstudio/tfdeploy")

2. Connect to Spark using sparklyr, copy some data and the mtcars TensorFlow model:

dgrapov

#plotly box or lasso select linked to 
# DT data table
# using Wage data
# the out group: is sex:Male, region:Middle Atlantic +


library(ggplot2)
library(plotly)
library(dplyr) 
library(ISLR) 

Vessy

############################################################################################
############################################################################################
# Plotting networks in R - an example how to plot a network and 
# customize its appearance in Cytoscape directly from R using 
# the RCy3 package
############################################################################################
############################################################################################
# Clear workspace 
# rm(list = ls())
############################################################################################

expersso

## Purpose: illustrate use of magick, gganimate, and purrr
## Inspiration:
## https://rud.is/b/2016/07/27/u-s-drought-animations-with-the-witchs-brew-purrr-broom-magick/
## and subsequent discussion on magick vs gganimate:
## https://twitter.com/hrbrmstr/status/758304420224466944
library(purrr)
library(ggplot2)
library(gganimate)
library(animation)
library(magick)

torgeir

Installing ubuntu snappy core on raspberry pi 2

Translated to os x from https://developer.ubuntu.com/en/snappy/start/#snappy-raspi2

Download the image

http://people.canonical.com/~platform/snappy/raspberrypi2/

Locate your sd card

yihui

Moved to https://github.com/yihui/shiny-apps/tree/master/voice

qinwf

#!/usr/bin/r

library(inline)
library(rbenchmark)

## openMPCode example from Rcpp/examples/OpenMP/ by Dirk E.

openMPCode <- '
   // assign to C++ vector
   std::vector<double> x = Rcpp::as<std::vector< double > >(xs);

thertrader

This Shiny application is designed to help analysing trading strategies. It is an ongoing project that I improve when time allows. Feel free to get in touch should you have any suggestion.

*How to use the App as it is?
The App uses as input several csv files (one for each strategy). Each file has two columns: date and daily return. There is an example of such a file in the Github repository. The code is essentially made of 3 files.
-ui.R: controls the layout and appearance of the app
-server.R: contains the instructions needed to build the app. You can load as much strategies as you want as long as the corresponding csv file has the right format (see below).
-shinyStrategyGeneral.R: loads the required packages and launches the app
put ui.R and server.R file in a separate directory

In the server.R file change the inputPath, inputFile and keepColumns parameters to match your setting. The first two are self explanatory the third one is a list of column names within the csv file. Keep only date and daily return