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Highest ollie clustering example.Rmd
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---
title: "Clustering different heights of the worldwide Highest Ollie contest"
author: "Ben M"
date: "1/22/2017"
output:
html_document:
theme: journal
pdf_document: default
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
## Skate-aid Worldwide Highest Ollie Contest 2017
On 7th January 2017, [Skate-aid](http://www.skate-aid.org) organised a competition which involved the contestant(s). Jumping over an adjustable obstacle by Ollieing especially where they have established projects namely:
* Copenhagen, Denmark (DK)
* Cape Town, South Africa (ZA)
* Münster, Germany (DE)
* Nairobi, Kenya (KE)
* San Isidro, Costa Rica (CR)
* Dodoma, Tanzania (TZ)
* Bethlehem, Palestine (PS)
* Kigali, Rwanda (RW)
* Kampala,Uganda (UG)
* La Paz,Bolivia (BO)
Additionally, the rules to govern the event worldwide can be found here [rules](https://etrigg.com/event/skate-aid-worldwide-highest-ollie-contest-2017/49489654/). Here's a skater from Kenya jumping over the obstacle. Which is an adjustible wood plank in this case.
[Photo by Robert Opiyo, skateboarder Sydney Yongo](https://www.facebook.com/photo.php?fbid=1572448036103794&set=a.406576599357616.113391.100000158393836&type=3&theater)
'The aim of the contest was to unite skaters from all over the world and to help at-risk youths with a safe and constructive space that children require in their developmental ages.' [From page Skate-aid Shangilia Skatepark Nairobi - Kenya
](https://www.facebook.com/skateparknairobi/photos/a.622418004449939.1073741827.622414867783586/1423265004365231/?type=3&theater)
From the results of the competition. Which i acquired using this link [results](https://www.facebook.com/skateaid/posts/1379140678786498). Here are the results.
1. Copenhagen: Alexander Risrad - 103 cm (highest record)
2. Cape Town: Ryan Naidoo -99 cm
3. Münster: Georg G Anders -85 cm
4. Nairobi: Kevin Maina - 75 cm
5. San Isidro: William Morales -70 cm
6. Dodoma: Gideon -54cm
7. Bethlehem: Moyyed and Anas- 20 cm (Under 15 only)
8. Kigali: 15cm (under 15 only)
9. Uganda: from John Ray's post here [facebook post](https://www.facebook.com/search/top/?init=quick&q=highest%20ollie%20uganda&tas=0.20332534655961598)
cm- Centimeters in height.
I changed the results a bit so that they could be accomodated in the graph i've drawn below. Notice the changes in the lines of code below.
## Making the dataframe
```{r df}
# making a dataframe of the results of the contest
ctry <- c('DK','ZA','DE','KE','CR','TZ','UG','PS','RW','US') #different countries
hts <- c(103,99,85,75,70,54,88.4,20,15,114.3) # heights are in centimetres
names <- c('A.Risrad(103)','R.Naidoo(99)','G.Anders(85)','K.Maina(75)','W.Morales(70)','Gideon(54)','Peter(88.4)','Moyyed & Anas(20)','Na.RW(15)','A.Garcia(114.3)')
df <- data.frame(ctry,hts,names)
df
```
## Drawing the plot(dendrogram)
```{r}
# Make hierarichal clustering object and visualize
dist_mat <- dist(df[,2]) # selecting the second column
hc <- hclust(dist_mat)
plot(hc, labels = df$names, xlab = "Different heights of individuals in different countries", main = "How close the Ollie Heights were between countries \n
Skate-aid International Annual Ollie Contest 2017")
legend(x = "bottomright", legend = "Close heights are paired in the leaves.")
```
## Interpretation
The graph you've seen above puts the Ollie heights together with the ones most closest being in the same leaf. That is, **Moyyes & Anas** and **Na.RW** (i named it like that because the name of the person was missing and i didn't find it anywhere). In addition, the heights of **A.Risrad** and **R.Naidoo** are really close to each other. Notice i also added the [Guinness world record](http://www.guinnessworldrecords.com/world-records/skateboarding-highest-ollie-) as well for comparison.
## Conclusion
**A.Garcia** still holds the world record from Las Vegas, United States in 2011. But, if more practice & learning from mistakes could be used by **A.Risrad** and **R.Naidoo** the record could be beat as an example. Now, you know whose Ollie height was close to whom. Question is, where would yours be among these heights? Thanks for reading!
## References
[Text Mining course on Datacamp: Distance matrix and Dendrogram](https://campus.datacamp.com/courses/intro-to-text-mining-bag-of-words/adding-to-your-tm-skills?ex=3)
[Data Visualization in R course on Datacamp: Adding details to plots](https://www.datacamp.com/courses/data-visualization-in-r)
## To replicate use this
```{r}
sessionInfo()
```