cl1

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) %>%
                filter(sum(max.points, na.rm=TRUE) > 400) %>%
                spread(compName, max.points) %>%
                as.data.frame()
rownames(country_jumper_points) <- country_jumper_points[,1]
country_jumper_points <- country_jumper_points[,-1]
# how this table looks like
country_jumper_points[1:5,1:5]
#                 Bischofshofen Engelberg Falun Garmisch-Partenkirchen Innsbruck
# AMMANN SIMON               50        38    32                     60        80
# BARDAL ANDERS              40       105    40                     20        18
# DAMJAN JERNEJ               0        NA    24                      9        NA
# DIETHART THOMAS           100        90    14                    100        45
# FREUND SEVERIN             26        11   100                      0        16