Data Science Manager - Accenture
M.S. in Predictive Analytics - DePaul University
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Built In
library(ggvis)
library(dplyr)
ncaa <- paste("https://www.dropbox.com/s/pappjoov6ozvvf0/ncaa.csv?dl=0")
ncaa <- repmis::source_data(ncaa, sep = ",", header = TRUE)
ncaa$id <- 1:nrow(ncaa)
all_values <- function(x) {
if(is.null(x)) return(NULL)
paste0(ncaa$Team[x$id],
"<br>",
ncaa$Record[x$id]
)
}
ncaa %>%
ungroup() %>%
ggvis(~Week,~Rank, stroke = ~Team) %>%
layer_points(size := 40, size.hover := 200, fill = ~Team, key:=~id) %>%
layer_lines(stroke.hover = ~Team, strokeWidth.hover := 8, strokeWidth := 1) %>%
add_axis("x", orient = "top", ticks = 0, title = "NCAA Men's Basketball AP Top 10",
properties = axis_props(
axis = list(stroke = "white"),
labels = list(fontSize = 0))) %>%
add_axis("x", title="Week", subdivide = 0, values = seq(1, 18, by = 1), format="####") %>%
add_axis("y", title="Rank", subdivide = 0, values = seq(1, 10, by = 1), format='####') %>%
scale_numeric("y", reverse=TRUE) %>%
add_tooltip(all_values, "hover")