Data Dashboard GUI App with Taipy Scenarios - Step by Step Python Tutorial

[@ChristianAkabu]

Hello. i watched this video and liked it a lot. nice studio, great project.i tried emulating the project but didn't workout so wanted to ask if this project supports intel(R) grahics. error message was invidia-smi not found. you really simplify python explanation. nice one. 👍

[@PythonSimplified]

It works, just not on your graphics card! You can proceed with the entire tutorial using regular Pandas, rather than the cuDF Pandas library that we install on minute 15:30. Just keep working inside your ds environment. Do not switch to ds_gpu and do not install or import cudf.pandas. Your app will work just fine with the CPU based Pandas. As I mentioned in the video, you need a special kind of hardware to proceed with GPU processing. It's an optional step that only works with Nvidia based GPUs that support CUDA. Please try it again, but make sure to skip the cuDF Pandas section between minutes 15:30 and 18:10. Good luck! 😃

[@ChristianAkabu]

@@PythonSimplified Ok. thanks very much.

[@drazzo777cod7]

Ur onlyfans link pls 😊​@@PythonSimplified

[@ecsantana]

You are undoubtly born with the gift of Teaching... You not only simplify things, but makes anything so much fun to learn! ! !

[@PythonSimplified]

Yeeey! Thank you so much for the lovely feedback!!! Super happy you like my teaching style! 🙂🙂🙂

[@dagooka8816]

Thanks for the awesome tutorial! Keep up the great work!

[@PythonSimplified]

Thank you so much, dear! I really appreciate your support! :)

[@davidtindell950]

Hi ! Thank You for providing this more 'advanced' and 'complete' Python Tutorial. Very engaging, helpful and useful !

[@xyzxyz6095]

Awesome preparation for this flawless lesson. Congratulations for your pedagogical methods,Maria. Salutations from France.

[@PythonSimplified]

Merci beaucoup!! Glad you like this tutorial! :)

[@ansahbritwum6439]

wonderfully made, smartly delivered

[@serta5727]

Great coding channel 🤓

[@javdmnm]

This video was absolutely amazing and informative. Thank you so much for your useful, practical, and up-to-date tutorials!.👍

[@PythonSimplified]

Thank you so much for the incredible comment!!! 🙂🙂🙂

[@Juanca-y3w]

Genial, ya active la notificación para que me avise 👏

[@GodX36999]

your voice is clear, well instruction, attraction, viral and lovely.

[@hk254lyt8]

Missed you. You helped me so much in my CS degree. Graduated this year 🎉

[@PythonSimplified]

That's awesome!!!! Super happy to help!! Right now I'm only waiting for the grades on my final project - and then I'll finally graduate too! 😉

[@rentipollo]

great inspiration, happy to have found this channel

[@PythonSimplified]

Thank you so much!!! Glad to have you on board! 😀

[@EnterPlayMode]

Whoa ❤‍🔥 you got your own emojis? That’s tuff! 💪🏾🔥

[@obc9794]

Nice tutorial, very instructive and easy to follow with your clear explanations. It must have consume a lot of your time. Thanks.

[@Sinke_100]

Like this Taipy thing, and you are killing it, Mariya 👍🏻

[@PythonSimplified]

Thank you, Sinisa!!! Now when I've learned how to work with Scenarios - I like Taipy much more than before! When I filmed my previous tutorial, I don't think Scenarios even existed! (Or maybe I just missed them in the documentation... 🤷‍♀️) It was a bit challenging to learn them on my end, but I hope I explained the principles in an intuitive way so folks will not have the same struggles! 😀

[@Sinke_100]

@PythonSimplified I was curious for Flet too, perhaps try it too somewhere in the future. I like gui variety. Taipy is kinda like React for Python, I am getting that vibe, lol. Haven't tryed it myself though yet

[@DerFlotteReiter]

It would be amazing if you could make a video were you backtest the strategies. And the tutorial is great. You present everything very well and your fluent speaking (without any "aaahhhs") is amazing.

[@hassanal8321]

As always, the teaching style is excellent all around! 🎓 I haven't completed watching the video, but I hope to finish it this weekend. 📅😊, Greate job Mariya 👏

[@yanDev]

Thanks you very much for this amazing tutorial i love you from France!! Please need more big vidéos like this!!

[@paulinofm]

Hola 😀. Amazing video!! , amazing project!!, amazing python packages!!! and super amazing teacher!!! 👧 SALUDOS DESDE ESPAÑA 🇪🇸

[@hassanal8321]

Thanks!

[@themarksmith]

Just found and subbed to your channel - amazing stuff!

[@PythonSimplified]

Thank you so much, dear!!! Welcome aboard! 😀😀😀

[@07bakabaka]

Fan here, please keep sharing your knowledge

[@VardisSartzetakis]

I apologize for the delay. It took me 8 min to subscribe to your channel.

[@PythonSimplified]

You must be a fellow Canadian if you apologize for something like that! 🤪 hahaha Welcome aboard!!! I hope you find my videos helpful! 😃😃😃

[@VardisSartzetakis]

@@PythonSimplified Yes I am, with a Greek background, unfortunately on the other side of Canada. Keep up the good work, you have talent!

[@ericmunene8521]

Your videos helped me convince my little sister get into fintech

[@NubsWithGuns]

"most certainly" Like . nah we don't do that here.. LOL Good to see that you are well, thank you for the new video.

[@michaelahonkova1499]

Hello! I love your video and teaching style. I ALMOST got to the end, I'm stuck at 1:13:25, where inside function split_data, you normalize the data to lay between 0 and 1, before returning them to get_rnn function. But, since split_data is used by all three prediction algorithms (lin, knn, rnn), wouldn't it normalize their data to lay between the 0 and 1 too? And I can see no step mentioned where we'd get back from the normalized to original scale, yet the presentation of the program right after this step shows predictions clearly on the original scale. What am I missing there? Thank you!

[@GodX36999]

I did it as your step by step then it work. Finally, I think the problem is that I have not installed things in conda but in python. Thank you

[@khaledkon7883]

wonderful, thank for this amazing tutorial 👏👏

[@PythonSimplified]

Thank you so much for your comment! 😀

[@6r31v1nZ]

this is gold, lady

[@serta5727]

It's pretty cool 😎

[@Firecodeman69]

This is amazing work. You are an awesome teacher. Would you ever consider a video showing how to host this application in taipy on your own web server? Thank you for the videos.

[@DarkLord-vk5bt]

Thank you lady❤❤

[@Jihaoui]

Great an very informative Tank you very much

[@Slavigrad]

Amazing project, cheers!

[@PythonSimplified]

Thank you so much!!! cheers! 🙂

[@tusharsingha7118]

I am 13, and I love your videos extremely ❤. Currently I am learning Python fundamentals😅.

[@LookNumber9]

Wonderful code topic on an excellent tool - and superb teaching method. Thank you! One thing that I noticed, but don't quite know how to fix is this scenario: 1. The program initializes with Lulu Lemon (from Canada) 2. We then add a company from another country, say Apple, from U.S. 3. If we then remove Apple from the company line . . . 4. the graph and stock information from Lulu remain, but the country drop-down remains as U.S., even thought the only stock is now Lulu Lemon (from Canada). I thought it might be in the on-change section, but I can't get it to re-initialize.

[@PythonSimplified]

Thank you so much, dear!! 😀 It's a great idea, and your instinct is right! It is something we fix within on_change, particularly inside the graph_data condition. Step 1. fetch the most recent company symbol by focusing on the column at index [-1]: state.graph_data.columns[-1] Step 2. find the company_data["Country"] where the company_data["Symbol"] is a perfect match to the symbol you fetched. Then assign it to state.country. Step 3. make sure your graph_data condition looks like this: if name == "graph_data": state.figure = display_graph(state.graph_data) # fetch latest country selection latest_symbol = state.graph_data.columns[-1] # set global state.country = company_data['Country'][ company_data['Symbol'] == latest_symbol ].values[0] I hope it helps! 🙂

[@LookNumber9]

@@PythonSimplified It looks like this code introduced some unintended consequences. But that's okay, I'll experiment a bit and see what I can come up with. Thanks!

[@chaimaghemati8713]

So excited to try it

[@PythonSimplified]

Awesome! Let me know how it goes! 😀 (and don't forget to share a link to your app if you end up customizing it! 😉)

[@synchlabcoding5345]

Awesome video

[@PythonSimplified]

Thank you! :)

[@joseramon1017]

Saludos desde MEXICO 🎉

[@PythonSimplified]

Hola desde Canada!! :)

[@joseramon1017]

😮

[@adrianguerra1952]

awesome video, thank you so much.

[@PythonSimplified]

Thank you so much, dear! :)

[@nandadoneparthy1143]

really excellent, god bless you

[@GodX36999]

Yeah good job , so appreciated

[@PythonSimplified]

Thank you, dear!! :)

[@mouhameddiop2245]

Hello Marya Thank you for your presentation, it's amazing and the contains are awesome. But i have one question can i use your method in case where i have for example a dataset with regions and each region we have a list of sites radiocommunications . Another question your predict values are per day value or whole the values between start and end dates?

[@butoyaemma600]

is it possible to get that file where you do all of that to do practice?

[@PythonSimplified]

Sure! You can find the complete app on Github, inside the "complete_app" directory 😉 github.com/MariyaSha/data_science_dashboard

[@cx3268]

Buying & selling stocks & other assets for DECADES have noticed up & down statical patterns. BUT at times those patterns ignore other realities.

[@PythonSimplified]

Absolutley! On top of historical mathematical patterns, stock values are also affected by world events and politics 🙂 To take the other 2 factors into account, we can probably use an LLM and create a substantially more advanced application that skews the prediction based on news items. It could be a nice project, but would require much more technical knowledge and real-time updates via fancy web sockets 😉

[@MuhammadNurdinnewspecies]

​@@PythonSimplifiedcorrect.. event with xlstm we still have a long gap between prediction and real data for long term prediction. For short term maybe we still can use it

[@dipitjaywant8044]

It was really a nice video. You simplified a complicated topic like time series used for stock value prediction. The explanation of steps in simple language helped me, I was working on a similar thing.👍 Can you give the code for using LSTM as well because it is difficult to make modifications in the same code, as the input that should provided is different from that provided to the RNN model.Please.

[@GodX36999]

Hi , I have this error "PackagesNotFoundError: The following packages are not available from current channels: - rapids=24.10*" then I used this command to check rapids version =====> conda search rapids -c rapidsai Loading channels: done # Name Version Build Channel rapids 0.0.1 pyh9f0ad1d_0 conda-forge It's just 0.01. so what's wrong with this. Thank you

[@PythonSimplified]

Here's a quick troubleshooting checklist: 1. before you install RAPIDS, you need a compatible GPU. If you don't have an Nvidia Based GPU with CUDA capabilities - you shouldn't be installing RAPIDS in the first place. In that case, just skip the cuDF Pandas section from minute 15:30 to 18:10. Proceed with your initial "ds" environment, with the traditional CPU-based Pandas. The same commands that work with Pandas, also work with cuDF Pandas, so everything will work the same on you end (just a tiny bit slower, because CPUs are not very good at processing tasks in parallel). 2. in case your GPU hardware is compatible, but you're still getting this error. type "nvidia-smi" in your WSL terminal and see what version of CUDA your GPU driver has. Then, navigate to the official RAPIDS cuDF Installation Guide: docs.rapids.ai/install/ Select the following: - stable release - conda method - CUDA env that matches your version of CUDA - Python 3.11 or 3.12 - choose a specific package of cuDF And then, you can copy the generated command from the bottom into your terminal. Good luck and I hope it helps! :)

[@GodX36999]

@@PythonSimplifiedwow, how nice and details feedback. Thanks a million ❤❤❤

[@nightmisterio]

Oh yeah! 🎉

[@lorenzestermann3629]

Thanl you very much❤

[@robertwhite8194]

do you have a video about how to install a WSL terminal. I attempted to install Window Subsystem for Linux but got this: Downloading: Windows Subsystem for Linux 2.3.26 Installing: Windows Subsystem for Linux 2.3.26 Catastrophic failure

[@PythonSimplified]

I can't recreate your error, but I have a feeling it might be due to a partial installation of WSL that prevents you from running or installing a new one. Try the following: 1. run your Power Shell as administrator (administrator is very important!) 2. wsl --shutdown 3. wsl --install

[@robertwhite8194]

@ hey thanks so much for replying! I got WSL downloaded and completed this tutorial. I learned a lot! WSL is very cool, and the extension for it in VS code works great!

[@rofsjan]

Interesting. Stocks, finance. Thank you! Is it possible to get values of Moving averages, like 200 daily MA?

[@nazarshi9778]

anyone having issue with the plotting of the company values ? ?? any idea how to fix it ?

[@PythonSimplified]

What kind of issues are you having? And at which steps of the tutorial?

[@travisschwartz3397]

Solidity editor do they have one ? 😅❤

[@JNET_Reloaded]

i dont use sh1tty conda its bs use uv instead ok! also no gpu so how do we do it without it i need cpu only mode as on a rpi 5 ty

[@Optimusjf]

Greats

[@desiduniya2425]

Yay, Nice ezy pzy✌️

[@NIRMITKUMARSHAH]

Hello Mariya, Glad to learn from you could you please Help i'm stuck in find gap between tier Thread from camera Image (2D image taken from mobile phone) any idea or suggestion or small video clip will make my day hope some replay from you. Thank you for your cooperation and assistance. Please do the needful!!

[@georgevillac]

awesome

[@tenamsb686]

Mariya, I had a question! Why aren't the developers using the docker container as an environment?! Every other youtube tutorial I watch by someone - they use either venv, conda, not to mention - you doing it in wsl as well. But why not docker?! Do people / developers hate docker?!

[@Juanca-y3w]

Next tutorial, Flet and python

[@willy_fonker]

Flet is an awesome library.... But I personally think it's a bit too new to be deeply invested in. But maybe in the later future it can be awesome working with it

[@PythonSimplified]

It actually looks pretty intuitive and simplistic! If I see more comments, I might cover it in the future (however, not in the next tutorial 😅)

[@willy_fonker]

@@PythonSimplified yeah, just play around with it ... (Desktop, web, mobile)All in one library💯

[@myJapanTV013]

Nice

[@oraz.]

Following along

[@thomashering1482]

Hallo.. I use python (and other) since 2002 at work... there is so many stuff. I'm not sure.. was taipay also a thing for android ? For logic and data ... and everything you can solve on a commando line: python is the boss. Bur gui is a pain in the ass. For 20 years ongoing.

[@willy_fonker]

@@thomashering1482 GUI in python, you just have to be creative

[@travisschwartz3397]

How do smart contracts work 😅

[@gabrielmegiatoreloferreira5860]

Owww. Now the videos have translation!

[@PythonSimplified]

Yup! That's a new KZbin feature! All video are automatically captioned and translated! 🙂🙂🙂 I used to generate captions via Adobe Premiere and translate them via HuggingFace Transformers, it used to take HOURS to generate files for 8 languages... now I don't need to worry about it at all! 🥳 Thank you KZbin!

[@lonnieo4676]

...Past performance is not indicative of Future Results

[@PythonSimplified]

and yet somehow history tends to repeat itself 😉

[@lonnieo4676]

@@PythonSimplified lol..

[@stergios_karantanis]

👏

[@Kracyignacy2]

Can you add Polish to the subtitles?

[@artstechnology7809]

You are beautiful girl and with beautiful minds ❤❤❤

[@shoshanamofaz3012]

Don’t use Python as much as I used to Dell has me using Java Spring for server side Typescript for client side

[@PythonSimplified]

I'm so happy to see you in the comments again, Shoshana!!! 😀😀😀 It's been a long while, and I was wondering how you've been doing during these uneasy times! Glad you're still with Dell! (but very sad they're using a Java backend instead of Python 🤪 hahaha). Cheers, and have a fantastic rest of your week! וכמובן, שבת שלום!! וד"ש מקנדה המושלגת! 🙂

[@jayanthsw]

Hello! Thank you very much for this tutorial. It has been very helpful. I am working on replicating the code and am getting a recursion error. Here is a part of the error from the command prompt . Specifically around time 32:35 - right after creating the scenarios. Let me know your thoughts.! Any suggestion would be helpful """\anaconda3\Lib\site-packages\taipy\core\config\data_node_config.py", line 292, in __getattr__ return _tpl._replace_templates(self._properties.get(item)) ^^^^^^^^^^^^^^^^ [Previous line repeated 997 more times] RecursionError: maximum recursion depth exceeded""

[@shoshanamofaz3012]

Still working for Dell I am a single mother now

[@albertcowley7679]

At the risk of being accused a sexist, can someone tell me if this girl is actually such an accomplished programmer. Brilliant presenter she is, but I wonder if that is indeed all she is. To me she looks too good be true and looks more like a model. It doesn't really matter of course as content is great but I am still curious. Any ideas?

[@GodX36999]

Hi, I have install tensorflow and keras together in vs code but don't use conda, I have error missing import when code " from tensorflow.keras import layers" but no error if I did " from tensorflow import keras from keras import models " . but chatgpt told me that have some key difference