Solutions to “Just KNIME It!” Challenge 27 - Season 3

:boom: Wow! Didn’t we just come out with a new Just KNIME It! challenge! :boom: Time is running by this year, folks! :running_woman: How are we at challenge 27 already?

:earth_africa: This week, our challenge focuses on the 2024 World Happiness Report to explore which countries are the top happiest for different age groups. :relaxed: Are there any interesting country overlaps in this report?

Here is the challenge. Let’s use this thread to post our solutions to it, which should be uploaded to your public KNIME Hub spaces with tag JKISeason3-27 .

:sos: Need help with tags? To add tag JKISeason3-27 to your workflow, go to the description panel in KNIME Analytics Platform, click the pencil to edit it, and you will see the option for adding tags right there. :blush: Let us know if you have any problems!

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My solution to the challange:

The solution contains my visualization if the TOP10 countries by the categories (and scraped down the necessary flag picture to show it in the table :slight_smile: )

I think the scraping down and embed totally custom images to your dashboards is one of the strongest possibility (besides E-charts of course) in KNIME dashboarding!

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Here’s my solution. As usual, nothing fancy. It would be helpful to know the age ranges for the age groups. A quick observation - the old age group is unhappy at about the same rate as the two middle groups. Conversely, the old group is happier then either of the middle groups.

Country Rank
Happiness by Age Group

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I noticed this and it definitely made me… think!

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Interesting that the US only shows up in the top 10 for “the old” - I look forward to analyzing next years dataset!

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Hello, here is my solution.

I made a dynamic component with bar chart and geospatial view.

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Hi all,
Here is my solution. I have color-coded them by country for easier viewing.

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Hello all, This is my solution to the challenge. I opted to present the output in three different ways.

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Here’s my solution - I used one of my favourite visualizations - the bump rank chart:

  1. part shows a global view and displays rank development of top-10-ranked countries in each category. I note that there are four countries that are in the top 10 across all age groups: Finland, Denmark, Iceland, Netherlands. Happy nordics :slight_smile:

  2. Pie charts show the share of age group for happiest and unhappiest. It looks like happiness and optimism diminishes over time

  3. Rank chart allows to display development of a single country starting from young on the left to old on the right with all ages being the last category. It looks like as a german counting myself to the lower middle category I am at peak happiness right now :smiley:

Link to my solution:

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Hi all,
Here is my solution.

I implemented the visualization in a heatmap with interactive filters.

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Hi Knimers! :ninja: :bar_chart:
This is my first time to join in Just KNIME It Challenges. :hugs:
The enthusiasm for KNIME grows daily, as more users discover the joy and benefits of using this powerful analytics platform.
Here is: my solution

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Find My Submission : JKISeason3-27 – KNIME Community Hub




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We’re so happy to hear that you feel more and more enthusiastic about KNIME! Welcome to our community: we hope these challenges greatly contribute to your data-focused learning!

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Super cool use of the bump rank chart: I personally rarely remember to use it!

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This is my solution.

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:sun_with_face: Good morning, folks! :sun_with_face:

As always on Tuesdays, here’s our solution to last week’s Just KNIME It! challenge!

We used the Geospatial View node to check where the happiest countries are, and also to facilitate checking whether or not they are close to each other. Definitely interesting to see how countries in Oceania and America appear a bit more often for older groups…

:moneybag: We hope to see you tomorrow for a challenge on the crypto market!

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I tried to check the solution but when I “execute all” the KNIME crashes but if I “execute” nodes one by one it works. :thinking: :thinking: :thinking:
I suspect on “Geocoding” & Geospatial view nodes which they are running parallel.
I tried to increase the memory allocation but still the same.

my problem solved by reducing parallel execution. :upside_down_face:
I set : Maximum working threads for all nodes : 1

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