Thank you so much for the feedback and sorry for the later reply. What would you like to see in this series? Am welcoming ideas 🤗 and would love to know your opinion! 🙏👍

thanks buddy! happy it helped to simplify fixing some of the complications with Firebase and Python. thanks for the comment and the support!

Thank you so much! That is definitely possible. You only have to play around with the Plotly X,Y settings for these traces lines. The Plotly library has excellent documentation I would suggest you to go wild with it! Otherwise if you want to get quicker around it use Chat GPT and pass the code + what sou wish to have improved. I see myself using chat GPT to code almost on a daily basis thee days as it boosts up productivity so much in this area😂 Let me know if that helps!

Thanks For the awesome feedback! 🙏🤗

Thanks for the feedback! 🙏🙏🙏😇 glad it helped!

Thanks for the feedback! 🙏🤗😂 glad you liked it hehe

Thanks Marc! Am glad you enjoyed the tutorial!

Thanks for the feedback Ilias! 🙏🙏

Thanks for your feedback Mohamed!! Much appreciated!

Hey. Sure thing. You need to graph the close prices or just the highs or just the lows (or mean of those) across time and then you could just use plot a plotly line graph instead.

Hey! Thanks for the feedback. Absolutely u could. Instead of discarding them in the for loop, i would suggest you create a new list with them and then you just plot them in with a new trace.

Dear , i mean if you grouped 4 levels to one , is it possible to place the number 4 at the diplayed level ?

Thank you for your feedback! Am very glad you enjoyed thr content! I will make sure to increase the font a bit going forward to make it easier to follow along and read

Hey! Can you post the error?

Httperror: 400 client error: Bad request for url:

I just wanna have the stock data website like yours. I'm new to python and your videos are super helpful. Im waiting for your videos to learn more.. but if i have the website like that for myself, it will be soo good😄

@@krish7068 thanks for the feedback! I will be releasing 2 new videos hopefully in the comming weeks! It may look hard but its easier than it looks. Keep on coding and you will get there! As for the error, did you your own firebase database and place the access variables into that dictionary at the start as per the video? Client error seems to me that you are not connecting to any firebase database currently. If you only execute the code in the colab notebook as it wont work. You need your own database setup first (i walk uou through that at the start of the video)

@@FoxyFi i did as you said in tutorial. I got my own config files, it showed up my email in firebase but at verification step I'm getting this error.. I think it is related to requests module or idk😂

Hey! I have another tutorial on my chanel covering some of that called Stock Market analysis using python.

@@FoxyFi Can you maybe send me the link of that video please?

@@jdf2159 sure. kzbin.info/www/bejne/nICcq5KHnMaDqZo

Hey! Thanks for the feedback! Happy to know the video is helping! The upcomming ones will go deeper into detail with the dash components and bootstrap components. To answer your questions: 1. Yes you are right! Will update the colab notebook when im back from traveling! From dash import html is the correct syntax now. 2. I usually start the app always right after the import. But both work just fine. But i would say starting the app first is cleaner from a hierarchical point of view. 3. To make it stop running you can interrupt or restart the kernel in the notebook. That will interrupt all processes and only restart the app once you re-run the cell again. But only necessary if you need to use the same local host ip, port, etc for something else. Otherwise you can just close the window and the colab notebook (which is what i do most of the time) Hope this helps! Dash is a fantastic framework. The educational website i built to do these tutorials (www.foxyfi.cc) was fully built in dash!

@@FoxyFi Thanks for the explanation. I would also like to know about options for deployment of web apps

@@shantalamukherjee3506 great! There will be a tutorial ln that as well soon!

got it, here it is.. abs(x-y) < mean for y in levels gives list of TRUE or FALSE, then we sum it, if the count is > 0, then the function returns FALSE. which means its matching with at least 1 of the prior levels.

So in that line essentially you are checking if the resistance levels you obtained (each level in that levels list) is affected by volatility. Essentially you would get too many resistance levels if you do not account somewhat for volatility. In this case volatility is extracted as the average diff between highs and lows (what you see as the mean volatility in the code there). If you want to remove all resistance levels that are in theory just the mean volatility moves and not "real resistance levels" then you check if each price point minus the resistance level you identified is less than the mean volatility level (which would mean that the low price point (x) has moved up and beyond the mean (volatility) and is a new resistance level. So if the sum of all those conditional tests is 0 (meaning the price point reached a new high beyond the noise of volatility of every level within that list) then you consider it a real resistance level. Essentially you are taking that list and discarding every item that is a resistance level below what the price could potentially move with volatility alone.

Most welcome 😃

Hey thank you so much for the feedback! Here is the code: colab.research.google.com/drive/16yWD7FJ-moOc9jjymDgQjLXvW-yPKSf3?usp=sharing

Thanks mate !!! Happy you enjoyed the video

@@FoxyFi 😘

Absolutely. You could add 1 more column to store the latest support and resistance or you can go into the levels and level_types lists and loop through them to retrieve the last resistance and last support level added.

@@FoxyFi is it possible to give me the code plzz

Thanks for the feedback buddy!! 🙏🙏 god bless

Thank you so much for the awesome feedback! 🙏🙏

Thanks for your feedback! This chart is generated with mpl_finance and matploib. I didnt explore adding that to the chart itself but it should be possible. One sokution i found reading is in this stackovdrflow post link: stackoverflow.com/questions/11779315/mouse-hover-in-matplotlib-candlestick-for-python I also did a video on using the backtesting library for algo trade strategy testing. You can also use that which will give you a very complete and detailed graph with those functionalities already. But resistance and support would have to be implemented onto it manually similarly to what i did here with matplotlib. Hope this helps.

Thanks for the feedback!

Thanks Anton!!!

Thanks Sebastian! Looking forward to share it and hopefully you will enjoy that too!

Hey. Well depends. I use it for entering equity option trades. But i trade windows of 1 week to 45 days or even up to 1-2 years. For day trading or rather high frequency trading then idd say you need to be very close to the data centers of the exchanges and have high speed computing power/internet which will likely require resources that usualy only investment companies have. But it absolutely helps me to invest long term into asset X and use these algos to determine if i should wait a bit longer to buy/sell based on the technical indicators it returns

Thank you aemoreno90! Am super gratefull that you enjoy the content. 🙏🙏

Thank you Aflous! Am super happy you enjoy the content! 🙏🙏🤩

Thanks Fabian!!

🙏🙏🙏 thank you Mariana!

Thank you Raquel! 🙏🙏🙏

Thanks for the feedback Mariana!

Glad you enjoyed it Raquel! 😃

Glad it was helpful! Thanks Fabian!

Thanks for the feedback Mariana! 🦊🙏