Hi, folks! We’re coming back today with an easier Just KNIME It! challenge to match the leisurely Summer vibes!
This week you’ll wear the social scientist hat to better understand how childcare works in the European Union. How do different countries handle childcare throughout the years?
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 JKISeason3-15.
Need help with tags? To add tag JKISeason3-15 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. Let us know if you have any problems!
Find herewith my submission - though for ranking order bump chart can be a better way over year while herein i just used donut chart for single year . There are many missing values in dataset while for latest year many of
data values missing thus trend of 2023 may not be a true representation ( or i am missing something) .
Here’s my solution - an interactive dashboards with 3 visuals:
Rank Bumb chart showing the top 10 development over time
2/3) line chart showing a) YoY Increase for each country and b) the 3 year moving average YoY increase for each country.
Countries to be displayed for 2/3 can be selected via combobox
Every time I work on a workflow I think I know how to do, I find new useful nodes. That is why these challenges are so brilliant, they force me to try new nodes, approaches
Hello everyone,
Here’s my solution. All the line plots for each country were output as images in a table view. Iceland, France, and Malta appear to show an increasing trend.Thanks.
We just posted our solution to last week’s Just KNIME It! challenge!
It looks like, if we discount the lingering effects of the COVID-19 pandemic, there is a rising trend in the percentages of people relying on childcare services in the EU. Let’s see how this evolves in the next couple of years!
We’ll be back tomorrow for a more complex data puzzle to hone your text mining skills. See you then!
Hello Everyone,
Please find my solution for the submitted challenge.
I only considered the datasets for which OBS_FLAG was missing. This resulted in 608 rows of data versus 627 rows in the original dataset.
I estimated the average mean for the OBS_VALUE for each country to estimate the countries with most and least ChildCare.
Childcare is MOST COMMON in Denmark
Childcare is LEAST COMMON in Turkey (Turkiye)
The overall increasing or decreasing trend has been estimated using a Linear Regression Learner and using the Co-Eff parameter for each country to understand the trend over the declared time periods.
Overall EU/Euro Area seems to have a flat growth. Even though Denmark registers the highest mean pct of childcare, Luxembourg registers the highest co-efficient indicating a significant increase in ChildCare. Interestingly, Denmark and UK have registered the lowest trends clocking a negative co-efficient indicating a declining trend over the declared period which is also visible through the yearly trends plotted in the component view.
The complete KNIME workflow is available at the below link.
Hi, folks! We’re coming back today with an easier Just KNIME It! challenge to match the leisurely Summer vibes! 
This week you’ll wear the social scientist hat to better understand how childcare works in the European Union. 
How do different countries handle childcare throughout the years?
Need help with tags? To add tag JKISeason3-15 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. 
Let us know if you have any problems!
We’ll be back tomorrow for a more complex data puzzle to hone your text mining skills. 
See you then!
