In schubertjan/giro2019: Constains Data From Giro 2019 Roadbook

knitr::opts_chunk$set(
  fig.width = 7,
  fig.height = 4.5,
  collapse = TRUE,
  comment = "#>"
)

The data comes from Giro road book and has been downloaded using the tabulizer package: tabulizer::extract_tables("http://www.giroditalia.it/wp-content/uploads/2019/04/Garibaldi_Giro_italia_2019_low_res.pdf", pages = c(17, 18))

tabulizer::extract_tables("https://static2.giroditalia.it/wp-content/uploads/2017/04/Garibaldi_2017.pdf", pages = c(10))

tabulizer::extract_tables("https://legaciclismo.files.wordpress.com/2018/05/garibaldi-2018.pdf", pages = c(19, 20))

You can download the whole package including the data and all the reports with devtools::install_github("schubertjan/giro2019").

Total Elevation Gained In categorized Climbs

Riders did an extra 3000m of climbing in 2017 compared with 2019. 2019 sees 1800m more categorized climbing than last year, or one big category 1 climb.

library(giro2019)
library(DT)

#fill the data with all stages
fill <- data.frame(tappa = 1:21)
climbs_2019 <- merge(fill, climbs, by = "tappa", all.x = TRUE)
fill <- data.frame(stage = 1:21)
climbs_2018 <- merge(fill, climbs_2018, by = "stage", all.x = TRUE)
climbs_2017 <- merge(fill, climbs_2017, by = "stage", all.x = TRUE)

#replace NA
climbs_2019$`disl.(m)` <- ifelse(is.na(climbs_2019$`disl.(m)`), 0, climbs_2019$`disl.(m)`)
climbs_2018$disl.m <- ifelse(is.na(climbs_2018$disl.m), 0, climbs_2018$disl.m)
climbs_2017$disl.m <- ifelse(is.na(climbs_2017$disl.m), 0, climbs_2017$disl.m)

#create colours
col_2017 <- rgb(200, 79, 178, maxColorValue = 255)
col_2018 <- rgb(105, 147, 45, maxColorValue = 255)
col_2019 <- rgb(85, 130, 169, maxColorValue = 255)

comp <- data.frame(Year = factor(c("2017", "2018", "2019")),
                   Total.elev = c(sum(climbs_2017$disl.m, na.rm = TRUE),
                                  sum(climbs_2018$disl.m, na.rm = TRUE),
                                  sum(climbs_2019$`disl.(m)`, na.rm = TRUE)))
with(comp,barplot(Total.elev, 
                  names.arg = Year,
                  xlab = "Stage",
                  ylab = "Total Elevation (m)",
                  main = "Total Elevation Gained in Categorized Climbs",
                  cex.axis = .8,
                  cex.names = .8,
                  col = c(col_2017, col_2018, col_2019)))

DT::datatable(comp, rownames = FALSE)

Total Elevation Gained By Stages

All building up for week 2 and 3. Unusually late GC action for Giro. On paper, stage 20 looks like the hardest in the last 3 years.

#summary by stage
s_2019 <- with(climbs_2019, tapply(`disl.(m)`, tappa, sum))
s_2018 <- with(climbs_2018, tapply(disl.m, stage, sum))
s_2017 <- with(climbs_2017, tapply(disl.m, stage, sum))

plot(names(s_2017), 
     s_2017, 
     type = "b",
     lwd = 3, 
     col = col_2017,
     ylim = c(0, max(c(s_2017,
                       s_2018,
                       s_2019))),
     main = "Total Elevation Gained in Categorized Climbs By Stages",
     ylab = "Total Elevation (m)",
     xlab = "Stage",
     cex.main = .8,
     cex.axis = .8,
     cex.lab = .8,
     xaxt="n",
     pch = 16)
lines(s_2018, lwd = 3, pch = 16,col = col_2018, type = "b")
lines(s_2019, lwd = 3, pch = 16, col = col_2019, type = "b")
axis(1, labels = names(s_2017), at = names(s_2017), cex.axis = .8)
legend("topleft", 
       legend = c("2017", "2018", "2019"), 
       col = c(col_2017, col_2018, col_2019),
       lwd = c(3,3,3),
       cex = .8)
DT::datatable(data.frame(giro2017 = s_2017,
                         giro2018 = s_2018,
                         giro2019 = s_2019))

Total Cumulative Elevation Gained By Stages

Despite little GC action in week 1, riders will end week 2 with about the same amount of gained elevation as in previous 2 years. Week 3 is tougher than last year.

#summary by stage
cs_2017 <- cumsum(s_2017)
cs_2018 <- cumsum(s_2018)
cs_2019 <- cumsum(s_2019)
#replace NA


plot(names(s_2017), 
     cs_2017, 
     type = "b",
     lwd = 3, 
     col = col_2017,
     ylim = c(0, max(c(cs_2017,
                       cs_2018,
                       cs_2019))),
     main = "Cumulative Total Elevation Gained in Categorized Climbs By Stages",
     ylab = "Cumulative Total Elevation (m)",
     xlab = "Stage",
     cex.main = .8,
     cex.axis = .8,
     cex.lab = .8,
     xaxt="n",
     pch = 16)
lines(cs_2018, lwd = 3, pch = 16,col = col_2018, type = "b")
lines(cs_2019, lwd = 3, pch = 16, col = col_2019, type = "b")
axis(1, labels = names(s_2017), at = names(s_2017), cex.axis = .8)
legend("topleft", 
       legend = c("2017", "2018", "2019"), 
       col = c(col_2017, col_2018, col_2019),
       lwd = c(3,3,3),
       cex = .8)
DT::datatable(data.frame(giro2017 = cs_2017,
                         giro2018 = cs_2018,
                         giro2019 = cs_2019))