nassimhaddad

(source: http://nvie.com/posts/a-successful-git-branching-model/)

create new branch:

git checkout -b develop

you can already use it this way

git remote add origin git push origin develop git pull origin develop

nassimhaddad

# remove non-ascii characters
df$text <- gsub("[^\x20-\x7E]", "", df$text)

nassimhaddad

#' best package to read excel files is gdata
#' which works with both .xls and .xlsx

#' windows: follow instructions here: 
#' http://cran.r-project.org/web/packages/gdata/INSTALL
library(gdata)
xlsx_file <- "myfile.xls"
sheet1 <- read.xls(xlsx_file,
                   sheet = "Sheet1", 
                   stringsAsFactors = FALSE, 

nassimhaddad

### string matching


### metric to find the similarity between two strings
### some context in:
### http://en.wikipedia.org/wiki/String_metric


### testing levenshtein metric
library(RecordLinkage)

nassimhaddad

# install.packages("rjson")
library("rjson")
json_file <- "json_file.json"
json_data <- fromJSON(paste(readLines(json_file), collapse=""))

# additional if needed
library(plyr)
json_data <- lapply(json_data, as.data.frame)
json_data <- do.call(rbind.fill, json_data)

nassimhaddad

library(digest)

test <- c("hobe", "jmjj", 1)

digest(test, algo = "md5")
digest(test, algo = "sha1")
digest(test, algo = "crc32") # not collision proof
digest(test, algo = "sha256")
digest(test, algo = "sha512")

nassimhaddad

plot(density(data1))
lines(density(data2), col = blue)

nassimhaddad

get_word_count <- function(string){
  length(unlist(strsplit(as.character(string), " ")))
}

nassimhaddad

# windows
x <- read.delim(file("clipboard","r"),
                header=TRUE,
                stringsAsFactors = FALSE)

# mac
data <- read.table(pipe("pbpaste"), sep="\t", header=T)

# read from and write to clipboard with Kmisc (windows + OS X):
library(Kmisc)

nassimhaddad

df <- data.frame(f = 1:4, g = letters[1:4])

df$g <- factor(df$g, levels = letters[4:1])