# Figure Friday 2025 - week 28 **URL:** \ **Category:** Dash Python\ **Tags:** announcements, figure-friday\ **Created:** [July 11, 2025, 8:24pm UTC](https://community.plotly.com/t/figure-friday-2025-week-28/93088 "2025-07-11T20:24:24Z")\ **Posts on this page:** 18\ **Page:** 2
**Author:** ![marieanne](https://sea2.discourse-cdn.com/flex024/user_avatar/community.plotly.com/marieanne/32/29767_2.png) [@marieanne](https://community.plotly.com/u/marieanne)\ **Post date:** [July 16, 2025, 1:39pm UTC](https://community.plotly.com/t/figure-friday-2025-week-28/93088/22 "2025-07-16T13:39:57Z")
Hi @feanor_92, that was a lot of work, some great visuals 🚀 I’m missing the historical movie chloropleth, did you remove it? I think your app would improve for users who do not know the data, if you add a little (more) context to some pages. Example: if I go to the chloropleth page, I could be easily tricked into thinking “the more yellow or the higher the number” the better. That’s how it usually works and at least I do not read every word on a screen. Assuming we prefer less corruption, it’s exactly the other way around. The more yellow & higher rank, the more corruption thoughts. You could add context by using something like this for the chloropleth, with other values and text: ```auto colorbar=dict( title="CPI Score", tickvals=[2, cpi_average, 98], ticktext=["Highly Corrupt", f"Median {cpi_average}", "Very Clean"] ) ``` or in another way. I only know this (changing ticktext for the colorbar) because I used it for the first time this ff 😅 And after that removed the map, but it works very well. My thoughts, and I should study PCA, I still do not understand what I’m looking at, but that’s my thing. ---
**Author:** ![adamschroeder](https://sea2.discourse-cdn.com/flex024/user_avatar/community.plotly.com/adamschroeder/32/17280_2.png) [@adamschroeder](https://community.plotly.com/u/adamschroeder)\ **Post date:** [July 16, 2025, 2:14pm UTC](https://community.plotly.com/t/figure-friday-2025-week-28/93088/23 "2025-07-16T14:14:46Z")
Very nice app, @feanor_92 . I agree with @marieanne 's suggestion regarding the colorbar. I tend to view the colorbar and immediately assume that the higher (more yellow) the number the better. I liked the historical trends line chart. Interesting to see 2024 as one of the lowest points since 2012. Can you explain how to interpret the PCA chart? ---
**Author:** ![adamschroeder](https://sea2.discourse-cdn.com/flex024/user_avatar/community.plotly.com/adamschroeder/32/17280_2.png) [@adamschroeder](https://community.plotly.com/u/adamschroeder)\ **Post date:** [July 16, 2025, 2:16pm UTC](https://community.plotly.com/t/figure-friday-2025-week-28/93088/24 "2025-07-16T14:16:30Z")
This app is going to be amazing when it’s done, @Ester . What happens in the choropleth map when you select a country from the dropdown? ---
**Author:** ![Ester](https://avatars.discourse-cdn.com/v4/letter/e/f04885/32.png) [@Ester](https://community.plotly.com/u/Ester)\ **Post date:** [July 16, 2025, 2:18pm UTC](https://community.plotly.com/t/figure-friday-2025-week-28/93088/25 "2025-07-16T14:18:04Z")
I will show You tomorrow on pycafe. P.S. My birthday coincidentally almost fell on the same day as FF’s, but mine is actually today, which is why the cake icon is showing. 😀 ---
**Author:** ![adamschroeder](https://sea2.discourse-cdn.com/flex024/user_avatar/community.plotly.com/adamschroeder/32/17280_2.png) [@adamschroeder](https://community.plotly.com/u/adamschroeder)\ **Post date:** [July 16, 2025, 2:38pm UTC](https://community.plotly.com/t/figure-friday-2025-week-28/93088/26 "2025-07-16T14:38:03Z")
oh, now I see that cake icon 🙂 Happy Birthday Eszter. Did you do anything special for your birthday? How did you celebrate? ---
**Author:** ![Avacsiglo21](https://sea2.discourse-cdn.com/flex024/user_avatar/community.plotly.com/avacsiglo21/32/29861_2.png) [@Avacsiglo21](https://community.plotly.com/u/Avacsiglo21)\ **Post date:** [July 16, 2025, 2:45pm UTC](https://community.plotly.com/t/figure-friday-2025-week-28/93088/27 "2025-07-16T14:45:39Z")
Hi @feanor_92 Can you please share. if possible, some images of your app?. Unfortunately I can see it on Pycafe from my phone. Thanks in Advance ---
**Author:** ![Ester](https://avatars.discourse-cdn.com/v4/letter/e/f04885/32.png) [@Ester](https://community.plotly.com/u/Ester)\ **Post date:** [July 16, 2025, 3:08pm UTC](https://community.plotly.com/t/figure-friday-2025-week-28/93088/28 "2025-07-16T15:08:56Z")
Thank you @Adam! I was invited to a nice restaurant for lunch;) ---
**Author:** ![feanor\_92](https://sea2.discourse-cdn.com/flex024/user_avatar/community.plotly.com/feanor_92/32/30321_2.png) [@feanor\_92](https://community.plotly.com/u/feanor_92)\ **Post date:** [July 17, 2025, 12:46pm UTC](https://community.plotly.com/t/figure-friday-2025-week-28/93088/29 "2025-07-17T12:46:26Z")
Thank you so much for this feedback—I actually didn’t even notice this yesterday 😔 I’ve just pushed an update that adds contextual guidance on the map. Now, right above the map, users will see a note: > “※ Lighter colors indicate less perceived corruption (better); darker colors indicate higher corruption (worse).” I’ve also customized the colorbar ticks to clearly label “Highly Corrupt,” “Median CPI,” and “Very Clean.” I hope this makes the dashboard more intuitive for first‑time viewers 🙂 ---
**Author:** ![feanor\_92](https://sea2.discourse-cdn.com/flex024/user_avatar/community.plotly.com/feanor_92/32/30321_2.png) [@feanor\_92](https://community.plotly.com/u/feanor_92)\ **Post date:** [July 17, 2025, 12:51pm UTC](https://community.plotly.com/t/figure-friday-2025-week-28/93088/30 "2025-07-17T12:51:03Z")
> [@adamschroeder](#): > > Very nice app, @feanor_92 . > I agree with @marieanne 's suggestion regarding the colorbar. I tend to view the colorbar and immediately assume that the higher (more yellow) the number the better. > > I liked the historical trends line chart. Interesting to see 2024 as one of the lowest points since 2012. > > Can you explain how to interpret the PCA chart? Thanks for the kind words! 🙏 I’ve also updated the colorbar per @marieanne suggestion so that the tick labels (“Highly Corrupt,” “Median CPI,” “Very Clean”) make it clear that lighter shades are better and darker shades worse. As for PCA tab: - **PCA1 (x‑axis):** the combination of all numeric CPI measures that explains the most variation among countries. - **PCA2 (y‑axis):** the next most important, independent direction of variation. In short, the PCA chart is a quick way to spot groupings or unusual cases beyond just the single CPI score: Countries that close together have very similar overall CPI profiles. ---
**Author:** ![feanor\_92](https://sea2.discourse-cdn.com/flex024/user_avatar/community.plotly.com/feanor_92/32/30321_2.png) [@feanor\_92](https://community.plotly.com/u/feanor_92)\ **Post date:** [July 17, 2025, 12:53pm UTC](https://community.plotly.com/t/figure-friday-2025-week-28/93088/31 "2025-07-17T12:53:50Z")
Hi! @Avacsiglo21! Yes, of course 🙂 Add pictures: ![Снимок экрана 2025-07-17 151614](https://us1.discourse-cdn.com/flex024/uploads/plot/original/3X/3/7/371271f765c291f82e2b46a91468ce2f6bab6ea6.png) ![Снимок экрана 2025-07-17 154057](https://us1.discourse-cdn.com/flex024/uploads/plot/original/3X/f/1/f10848b23dfb0ac95ff72bf5a331cd9482d88c95.png) ![Снимок экрана 2025-07-17 155327](https://us1.discourse-cdn.com/flex024/uploads/plot/original/3X/1/5/157af3c87775e47f1b922f182a1e3137128e58d5.png) ![Снимок экрана 2025-07-17 151647](https://us1.discourse-cdn.com/flex024/uploads/plot/original/3X/5/e/5e04ac291beea7809f4fa357bcbe87a32382bcfd.png) ![Снимок экрана 2025-07-17 151654](https://us1.discourse-cdn.com/flex024/uploads/plot/original/3X/d/2/d257895aed626bd1bbfad900a7be2cf0d8263aba.png) ---
**Author:** ![adamschroeder](https://sea2.discourse-cdn.com/flex024/user_avatar/community.plotly.com/adamschroeder/32/17280_2.png) [@adamschroeder](https://community.plotly.com/u/adamschroeder)\ **Post date:** [July 17, 2025, 1:05pm UTC](https://community.plotly.com/t/figure-friday-2025-week-28/93088/32 "2025-07-17T13:05:56Z")
@feanor_92 Are you free to join us this Figure Friday session to go over your graphs? ---
**Author:** ![U-Danny](https://avatars.discourse-cdn.com/v4/letter/u/a9adbd/32.png) [@U-Danny](https://community.plotly.com/u/U-Danny)\ **Post date:** [July 17, 2025, 3:45pm UTC](https://community.plotly.com/t/figure-friday-2025-week-28/93088/33 "2025-07-17T15:45:14Z")
HI, This topic is very interesting. I find it notable how the range of CPI values can be visualized, and with that purpose, I have developed two complementary charts. Both aim to highlight clustering patterns and the temporal evolution of perceived corruption levels at the country level. ![cap_1](https://us1.discourse-cdn.com/flex024/uploads/plot/original/3X/3/7/375d694731e9000ee331b2be7e9f967b23662eab.png) ![cap_2](https://us1.discourse-cdn.com/flex024/uploads/plot/original/3X/5/b/5b4e4b65359927df3e0f1d1bab34712a82b103c3.png) [Application code](https://github.com/U-Danny/plotly_files/blob/main/dash_friday_28.py) ---
**Author:** ![Avacsiglo21](https://sea2.discourse-cdn.com/flex024/user_avatar/community.plotly.com/avacsiglo21/32/29861_2.png) [@Avacsiglo21](https://community.plotly.com/u/Avacsiglo21)\ **Post date:** [July 17, 2025, 4:55pm UTC](https://community.plotly.com/t/figure-friday-2025-week-28/93088/34 "2025-07-17T16:55:46Z")
Excellent thank you very much ---
**Author:** ![Avacsiglo21](https://sea2.discourse-cdn.com/flex024/user_avatar/community.plotly.com/avacsiglo21/32/29861_2.png) [@Avacsiglo21](https://community.plotly.com/u/Avacsiglo21)\ **Post date:** [July 17, 2025, 5:00pm UTC](https://community.plotly.com/t/figure-friday-2025-week-28/93088/35 "2025-07-17T17:00:24Z")
Really cool PCA scatter graph. I really like this type of analysis, well done. One question the clústers you identified or use k means clustering?. ---
**Author:** ![Avacsiglo21](https://sea2.discourse-cdn.com/flex024/user_avatar/community.plotly.com/avacsiglo21/32/29861_2.png) [@Avacsiglo21](https://community.plotly.com/u/Avacsiglo21)\ **Post date:** [July 17, 2025, 5:04pm UTC](https://community.plotly.com/t/figure-friday-2025-week-28/93088/36 "2025-07-17T17:04:40Z")
Interesting the Spyral chart, interesting analysis ---
**Author:** ![Avacsiglo21](https://sea2.discourse-cdn.com/flex024/user_avatar/community.plotly.com/avacsiglo21/32/29861_2.png) [@Avacsiglo21](https://community.plotly.com/u/Avacsiglo21)\ **Post date:** [July 17, 2025, 5:41pm UTC](https://community.plotly.com/t/figure-friday-2025-week-28/93088/37 "2025-07-17T17:41:53Z")
Dissmiss the question, I re-read you use quartile for grouping 💪 ---
**Author:** ![feanor\_92](https://sea2.discourse-cdn.com/flex024/user_avatar/community.plotly.com/feanor_92/32/30321_2.png) [@feanor\_92](https://community.plotly.com/u/feanor_92)\ **Post date:** [July 17, 2025, 5:48pm UTC](https://community.plotly.com/t/figure-friday-2025-week-28/93088/38 "2025-07-17T17:48:26Z")
@adamschroeder Thank you for invite! Yes, I’d love to join the session. And I’ll try not to spread my post-cold cough to anyone 😅 ---
**Author:** ![feanor\_92](https://sea2.discourse-cdn.com/flex024/user_avatar/community.plotly.com/feanor_92/32/30321_2.png) [@feanor\_92](https://community.plotly.com/u/feanor_92)\ **Post date:** [July 17, 2025, 5:52pm UTC](https://community.plotly.com/t/figure-friday-2025-week-28/93088/39 "2025-07-17T17:52:55Z")
Thank you so much! 🙏 In this version I didn’t run a formal clustering algorithm—those “groups” you see are simply countries colored by their CPI‐quartile (High → Very Low corruption). The PCA scatter just projects the data, and any visual clusters emerge naturally from those quartile labels. [Previous page](https://community.plotly.com/t/figure-friday-2025-week-28/93088.md?page=1)