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ms6 <- lsmeans(model_mieszany, | |
pairwise~ typ*traktowanie, | |
adjust="tukey") | |
# $lsmeans | |
# Group lsmean SE df lower.CL upper.CL | |
# condition 1 -0.2208147 0.02642544 14.22 -0.2774102 -0.1642192 | |
# condition 2 -0.3123998 0.02628429 14.06 -0.3687533 -0.2560464 | |
# condition 3 -0.3500326 0.02688922 14.71 -0.4074429 -0.2926222 | |
# condition 4 -0.3249601 0.02589164 13.06 -0.3808715 -0.2690487 |
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model_mieszany <- lmer(kolec ~ typ*traktowanie + | |
(1|zwierze:typ) + | |
(1|zwierze:typ:skrawek) + | |
(1|zwierze:typ:skrawek:zdjecie), | |
data=dane) |
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library(shiny) | |
library(PogromcyDanych) | |
# wykonywane raz gdy uruchamiana jest plikacja | |
serialeIMDB$sezon <- paste(serialeIMDB$sezon, serialeIMDB$odcinek, sep="/") | |
shinyServer(function(input, output) { | |
# reużywalny fragment | |
dane <- reactive({ | |
serialeIMDB[serialeIMDB$serial == input$serial, |
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library(PogromcyDanych) | |
library(ca) | |
contingency <- table(auta2012$Kolor, auta2012$Marka) | |
# tylko kolory i marki, dla których jest przynajmenij 500 ofert sprzedaży | |
tab <- contingency[rowSums(contingency) > 500, colSums(contingency) > 500] | |
plot(ca(tab), arrows = c(TRUE, FALSE)) |
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auta2012[auta2012$KM > 500,"Kolor"] %>% | |
table() %>% | |
sort() %>% | |
tail(1) | |
## czarny-metallic | |
## 179 | |
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auta2012 %>% | |
filter(Kolor!="") %>% | |
group_by(Kolor, Rok.produkcji) %>% | |
summarise(median_KM = quantile(KM, 0.9, na.rm=T), | |
count = n()) %>% | |
filter(count>20) %>% | |
group_by(Rok.produkcji) %>% | |
arrange(-median_KM) %>% | |
slice(1) %>% | |
group_by() %>% |
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auta2012 %>% | |
group_by(Kolor) %>% | |
summarise(mKM = quantile(KM, .9, na.rm=TRUE)) %>% | |
arrange(-mKM) %>% | |
slice(1) |
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library(PogromcyDanych) | |
auta2012 %>% | |
group_by(Kolor) %>% | |
summarise(mKM = median(KM, na.rm=T)) %>% | |
arrange(-mKM) %>% | |
slice(1) | |
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labs <- function(data){ | |
if(is.null(data)) return(NULL) | |
paste0("<b>",data$name, "</b><br/> ", data$x, " <br/>", data$y,"") | |
} | |
abline_data <- function (domain, intercept, slope) { | |
data.frame(x = domain, y = domain * slope + intercept) | |
} | |
layer_abline <- function (.vis, domain, intercept = 0, slope = 1, dash = 6, ...) { | |
df <- abline_data(domain, intercept, slope) |
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library(ggvis) | |
df %>% ggvis(x =~ x, y =~ y) %>% | |
layer_points(fill = ~gr, size.hover := 200, | |
fillOpacity := 0.9, | |
fillOpacity.hover := 0.95) %>% | |
add_axis("x", title = group1) %>% | |
add_axis("y", title = group2) |