pbiecek

library(PISA2012lite)
pol <- student2012[student2012$CNT == 'Poland',]
model <- lm(cbind(PV1MATH, PV1READ, PV1SCIE)~ST28Q01+ST04Q01, pol)
# jeżeli nie jest zainstalowany to 
# install.packages("heplots")
library(heplots)
heplot(model, size="effect.size", las=1, term.labels=FALSE)

pbiecek

# install_github("amplab-extras/SparkR-pkg",  					
#               subdir="pkg")	
library(SparkR)

# you need to have a properly configured Spark installation
sc <- sparkR.init()

# read data from local disk
linesRDD  <-  textFile(sc,  "data.txt")	

pbiecek

## server.r
library(ggplot2)
library(scales)
library(Cairo)
library(ggthemes)
library(shiny)

load("dzch.rda")

zielonaChoinka <- function() {

pbiecek

## ui.R
library(shiny)

shinyUI(fluidPage(
  textInput(inputId = "imie",
                     label = "Zaznacz imiona",
                     value = ""),
  plotOutput("choinka", width=720, height=720)
  )
)

pbiecek

heatmap(as.matrix(country_jumper_points))

pheatmap(country_jumper_points,
         main="Where they've got points")

pheatmap(country_jumper_points, border="white",
         color = brewer.pal(9,"Blues"),
         main="Where they've got points")

pbiecek

library(pheatmap)
library(tidyr)
library(RColorBrewer)
library(SmarterPoland)

country_jumper_points <- skiJumps2013 %>% 
                mutate(jumper = paste(jumperSurname, jumperName)) %>%
                group_by(jumper, compName) %>%
                summarise(max.points = sum(classPoints, na.rm=TRUE)) %>%
                group_by(jumper) %>%

pbiecek

setwd("~/Dropbox/Projekt Akcelerometr/")

library(ggplot2)
library(lubridate)

read.table("2015-01-20_09-50-28.csv", h=T, sep=",") -> marsz
read.table("2015-01-26_12-32-02.csv", h=T, sep=",") -> schody
read.table("2015-01-26_20-43-38.csv", h=T, sep=",") -> skoki

marsz$loggingTime <- ymd_hms(marsz$loggingTime)

pbiecek

wynik_matematyka$Kolor <- ifelse(wynik_matematyka$CNT=='Poland','red','black')
OECD_mean <- mean(wynik_matematyka$PV)
### wykresy
ggplot(data = wynik_matematyka,
       aes(x=reorder(CNT,PV),
           y=PV)) +
  geom_errorbar(aes(ymin=PV-z_alpha*SE,
                    ymax=PV+z_alpha*SE)) +
  geom_point(colour='red') +
  theme_bw() + 

pbiecek

wynik_matematyka <- badanie %>%
          do(data.frame(PV1 = svymean(~PV1MATH,design = .$schemat),
                        PV2 = svymean(~PV2MATH,design = .$schemat),
                        PV3 = svymean(~PV3MATH,design = .$schemat),
                        PV4 = svymean(~PV4MATH,design = .$schemat),
                        PV5 = svymean(~PV5MATH,design = .$schemat))) %>%
          ungroup() %>%
          mutate(CNT = badanie$CNT) %>%
          gather(Stat,Value,-CNT) %>%
          separate(Stat,c('PV','STAT'),sep='\\.') %>%

pbiecek

### przedział ufności
alpha <- 0.05
z_alpha <- qnorm(1-alpha/2)
wynik$Kolor <- ifelse(wynik$CNT=='Poland','red','black')
### wykresy
ggplot(data = wynik,
       aes(x=reorder(CNT,PV1MATH),
           y=PV1MATH)) +
  geom_errorbar(aes(ymin=PV1MATH-z_alpha*SE,
                    ymax=PV1MATH+z_alpha*SE)) +