Solutions to “Just KNIME It!” Challenge 6 - Season 3

[berti093]

My solution to challange 6:

JKISeason3-6 – KNIME Community Hub

It was a really fun challenge!

[AnilKS]

My submission for the challenge

JKI-SC6 – anilks

[jproudfoot111]

JKISeason3-6 – jproudfoot111

Ran a recursive loop to take account of opponent strength to weight results for rankings.
Removed “friendlies” for the Wins/year" categorization

[gonhaddock]

Hello knimers,
Just aiming to update. As the data in general is very discontinuous, I’ve been working a step further on my R ggbumpcharts (parallel coordinates plot in KNIME); because they resulted a bit messy to visualize as they were before (see my latest post).

I’ve segmented the vectors and added a single label on the first node at each segment. So now it’s easier to interpret what’s going on.

I tested the @MartinDDDD 's Bump Java Echart before (I’m impressed by the readability of it), congrats; however I decided to don’t use it, as I can’t achieve any Java result by myself; then coding it into R, where I feel more comfortable with.

Besides, the ELO algorithm result seems to display a more continuous chart; however achieving the very same output for the three top football teams

Anyhow, I’ve updated the workflow in Hub; and I’m posting an updated capture of R charts; as data results didn’t change.

Keep it coding

P.S About the results itself; I’m impressed with the reliability of England team, in the top ten leader board along the history…

[alinebessa]

Here’s our solution to last week’s Just KNIME It! challenge!

Challenge 6 - Visualizing Top Football Teams in History – knime

WOW! You folks really ran the extra mile with the meticulous data cleaning and visualizations! We’re very impressed!

In our solution, we found an interesting ranking for the 1980s, with South Korea at the top! Very curious!

[ApoorvaNS]

Thank you @alinebessa for creating this interesting challenge.

My simple solution is at https://hub.knime.com/-/spaces/-/~YF0FnxNO9QS8L62k/current-state/. My dashboard summarizes three parameters of interest :

• At the year level, a single filter summarizes top 3 teams by either goals / matches won

• At the country level, for the particular year, shows the total stats of the country

• At the country level, for the particular year, shows the match details

[ahmadulfi]

Here’s my attempt for this challenge. Still on progress. Not a perfect but based on my own curiosity

JustKnimeIt3Zul – ahmadulfi

Can anyone help me with displaying the team’s names on the scatter plot nodes?

Thank you!

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Ahmad Ulfi Jihad Dzulqornain
Bachelor Degree of Statistics
Let’s Connect!

[ahmadulfi]

I love the way you explore the data and explain it! Gotta learn more from this workflow

[alinebessa]

Wow! What an amazing first contribution to our forum! Welcome to our community!

[ahmadulfi]

Thankyou so much! Gotta learn more about this tools.