jeffreyiacono

library(ggplot2)
library(reshape2)

df <- data.frame(grp = 1:25, start = rnorm(25, 10, 5), end = rnorm(25, 5, 3))
df$end_higher <- df$start < df$end

mdf <- melt(df, id.vars = c("grp", "end_higher"))
names(mdf) <- c("grp", "end_higher", "category", "value")

mdf$grp <- factor(mdf$grp)

jeffreyiacono

library(ggplot2)
library(reshape2)

# data setup
df <- data.frame(grp = 1:25, start = rnorm(25, 100, 10), end = rnorm(25, 10, 5))
 
# ** plotting using base plot functions
par(mfrow = c(1, 1))
rng <- range(df$start, df$end)
 

jeffreyiacono

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

jeffreyiacono

options(repos = c(CRAN = "http://cran.rstudio.com"))

install.packages("ggplot2")
install.packages("dplyr")

require(ggplot2)
require(dplyr)

points <- 10000
buckets <- 20

jeffreyiacono

Keybase proof

I hereby claim:

• I am jeffreyiacono on github.
• I am jfi (https://keybase.io/jfi) on keybase.
• I have a public key whose fingerprint is 9313 2A1C 7607 9701 D3EF B96F 28F3 F2D8 4DE7 2229

To claim this, I am signing this object:

jeffreyiacono

d <- rnorm(1000)

df <- data.frame(x = seq(1, length(d), by = 1), y = d)
df$zscore <- (df$y - mean(df$y, na.rm = TRUE)) / sd(df$y, na.rm = TRUE)

ggplot(df, aes(x = x, y = y, group = abs(zscore) >= 1.95)) + geom_point(aes(color = abs(zscore) >= 1.95))

ggplot(df, aes(x = x, y = y, group = abs(zscore) >= 1.95)) + geom_point(aes(color = abs(zscore) >= 1.95)) + scale_color_manual(values = c("FALSE" = "grey", "TRUE" = "red"))

jeffreyiacono

def something a, b, &block
  sum = a + b
  another_private_thing = "only something can see this"

  puts "I'm in something, executing code."
  puts "I added #{a} + #{b} and got #{sum}"
  puts "and I can access my local vars: another_private_thing = #{another_private_thing}"

  yield sum, another_private_thing

jeffreyiacono

library(UsingR)
library(ggplot2)
library(reshape)

data(galton)

freqData <- as.data.frame(table(galton$child, galton$parent))
names(freqData) <- c("child", "parent", "freq")
freqData$child <- as.numeric(as.character(freqData$child))
freqData$parent <- as.numeric(as.character(freqData$parent))

jeffreyiacono

library(ISLR)
library(ggplot2)
library(caret)

data(Wage)

# remove logwag as predicting wage, so this would be a pretty good predictor :)
Wage <- subset(Wage, select = -c(logwage))

# cross-validation data

jeffreyiacono

x = -10:0.1:10;
plot(x, 1 ./ (1 + e .^ -x))