andilabs

from numpy import arange
from scipy import stats
l=arange(0.1,1,0.1)
print l
import itertools as it
pr=it.product(l,repeat=6)

l2=list()
for i in pr:
  l2.append(i)

andilabs

from numpy import arange
from scipy import stats
l=arange(0.25,1.01,0.25)# l=arange(0.1,1,0.1)
print l
import itertools as it
pr=it.product(l,repeat=6)

l2=list(pr)
# for i in pr:
#   l2.append(i)

andilabs

# -*- coding: utf-8 -*-
import xlrd
import csv
from os import sys

def csv_from_excel(excel_file):
    workbook = xlrd.open_workbook(excel_file)
    all_worksheets = workbook.sheet_names()
    for worksheet_name in all_worksheets:
  	worksheet = workbook.sheet_by_name(worksheet_name)

andilabs

library(matrixStats)
library(R.methodsS3)
#biblioteki plyr uzyjemy do szybkiego wygenerowania podsumowan 
library(plyr)
#do wykresow:
require(ggplot2)


#wyczyść wszystkie zmienne z pamięci
rm(list=ls(all=TRUE))

andilabs

You do not even need lists if your "number" values are all of the same mode. If I take Dirk Eddelbuettel's example:

> foo <- c(12, 22, 33)
> names(foo) <- c("tic", "tac", "toe")
> foo
tic tac toe
 12  22  33
> names(foo)
[1] "tic" "tac" "toe"
Lists are only required if your values are either of mixed mode (for example characters and numbers) or vectors.

andilabs

> dat=read.csv(file.choose(),header=FALSE,sep=" ")
> head(dat)
     V1     V2             V3     V4
1 83965 891552   Identifiable People
2 88599 891552   Identifiable People
3 42966 891552   Identifiable People
4 83965 891553 Unidentifiable People
5 88599 891553 Unidentifiable People
6 42966 891553 Unidentifiable People
> dat$LABEL<-do.call(paste,c(dat[c("V3","V4")],sep="_"))

andilabs

dat<-dat[,!(names(dat) %in% c("V3","V4"))]

andilabs

import csv
from sets import Set
import sys
results = {}
items = Set()#[]
workers = Set()#[]
def addItem(idict):
	#appending sets of workers and items
	if int(idict['worker']) not in workers:
		workers.add(int(idict['worker']))

andilabs

tr '\t' '\n' <input >output

andilabs

import csv
from sets import Set
import sys
golds = {}
items = Set()
def loadData(path):
  with open(path,'rU') as F:
		csvdr = csv.DictReader(F,delimiter='\t')
		for p  in csvdr:
			items.add(int(p['item']))