Nicktz

// Use Gists to store code you would like to remember later on
console.log(window); // log the "window" object to the console

Nicktz

# Shows step by step how to plot drawdowns in R using ggplot2.

if(!require(tbl2xts)) install.packages("tbl2xts")
if(!require(tidyverse)) install.packages("tidyverse")
library(tbl2xts)
library(tidyverse)
library(PerformanceAnalytics)

# Now use TRI data:
data(TRI)

Nicktz

df %>% .[!Universe %in% c("JALSH", "AS51")]

Notice the ! before the data source, not before %in%.

Nicktz

dplyr allows the user to avoid loops. 

The loops are replaced by group_by() if data is well gathered into a tidy data frame.

E.g.:

  data <- data.frame(
  date = rep(c(1,2,3,4), each=25),
  Tickers = rep(c("A", "B", "C", "D")),
  Returns = rnorm(100),

Nicktz

RdsFilesIdentical <- function(RdsLocation1, RdsLocation2) {
  
  library(fairtreeR)
  load.packages()
  
  Rds1 <- read_rds(RdsLocation1)
  Rds2 <- read_rds(RdsLocation2)
  
  identical(Rds1, Rds2)

Nicktz

test <- function(x) {
y <- x^2
y
}

Nicktz

As I answered here: http://stackoverflow.com/a/37939267/4198868

To remove all columns with only zeros:
    dfzeroremoved <- df %>% .[,colSums(. != 0) > 0]

To remove all columns with only NA:
    dfzeroremoved <- df %>% .[,colSums(!is.na(.)) > 0]

Nicktz

# Simple:

select_(dataframe, .dots = VectorofNames)

Nicktz

library(far)

data <- 
  data.frame(x = rnorm(30, 0, 1.5), 
             y = rnorm(30, 0, 1.5),
             z = rnorm(30, 0, 1.5))

y <- 
  orthonormalization(data,basis=FALSE, norm=TRUE)
# basis = TRUE squares columns.

Nicktz

data %>% mutate_each(funs(scale), X, Y)
data %>% mutate_each_(funs(scale),vars=c("X","Y"))

Which will scale the selected columns to be N(0,1).

E.g.:

data <- data.frame(x = rnorm(10, 30, .2), 
                  y = runif(10, 3, 5),
                  z = runif(10, 10, 20))