Build 12 Data Science Apps with Python and Streamlit - Full Course

Learn how to build interactive and data-driven web apps in Python using the Streamlit library.

⭐️ Course Contents ⭐️
⌨️ (0:00) Introduction
⌨️ (2:54) 1. Simple Stock Price
⌨️ (13:24) 2. Simple Bioinformatics DNA Count
⌨️ (29:44) 3. EDA Basketball
⌨️ (50:39) 4. EDA Football
⌨️ (1:00:48) 5. EDA SP500 Stock Price
⌨️ (1:24:03) 6. EDA Cryptocurrency
⌨️ (1:50:47) 7. Classification Iris
⌨️ (1:58:58) 8. Classification Penguins
⌨️ (2:16:08) 9. Regression Boston Housing
⌨️ (2:27:53) 10. Regression Bioinformatics Solubility
⌨️ (2:54:27) 11. Deploy to Heroku
⌨️ (3:04:37) 12. Deploy to Streamlit Sharing

⭐️ Code ⭐️
💻 1. Simple Stock Pric
💻 2. Simple Bioinformatics DNA Coun
💻 3. EDA Basketbal
💻 4. EDA Footbal
💻 5. EDA SP500 Stock Pric
💻 6. EDA Cryptocurrenc
💻 7. Classification Iri
💻 8. Classification Penguin
💻 9. Regression Boston Housin
💻 10. Regression Bioinformatics Solubilit
💻 11. Deploy to Heroku

⭐️ More ways to connect with Chanin Nantasenamat ⭐️

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[TheGrandmaster]

I honestly can barely believe this channel exists. If you take the entire channel with all the videos, we literally get an entire college degree worth of learning for free. People can build better careers and improve their entire lives because of this channel. Thanks guys, keep it up please. I have a lot to learn, but I hope I can be successful!

[rinkujain]

This guy: Builds 12 apps in 3 hours
Me: Writes 10 lines of code in 3 hours

[dryadeknight]

50:00 this works because the original dataframe has all of its columns as object, you will need to cast to int/float accordingly. So the workaround, export then import as csv, actually casts the data to the correct datatype.

[yunakamura]

If I had known such a tool and tutorials would be available for free, I would have been born twenty years later. Yet, never too late to appreciate. Thanks!

[yichengwang]

For those that had the ValueError: could not convert string to float for the Basketball EDA project, you need to filter out the non-numeric columns like this "df = df.select_dtypes(include=[float, int])" before doing df.corr()

[homestar]

it is absolute insane that this is free. thank you so much

[techwills]

Thank you professor ! That's exactly what I needed to make a cool visualisation of my project

[prashant]

Absolutely brilliant, easy, straight to point, confidence booster tutorial with top down approach to learn DS. Subscribed to your channel

[RoleJohn]

Thank you sir for sharing. best 3 hours of my recent data science journey.
Thank you again. i need more content like this

[Coolhotriad]

Saving this for this weekend! Awesome stuff.

[MrSCVideo]

right away i get the feeling that you lay things out in a genius fashion this is great and focused upon efficiency and simplification

[mohammadabdelrahman]

at 6:34 pip install
be careful, if you're using windows you may need to open the cmd as an administrator (right click -> open as administrator)

[quyenscc]

I cannot thank you enough for this series of projects. It is amazing. Thanks a lot.

[jetjet]

YES! Instant bookmarked for the weekend :)

[sashjov]

*Note* - Currently there is an issue between yfinance and panadas 1.4, resulting in error: 'Index' object has no attribute 'tz_localize'. The yfinance community is aware of the issue and a fix will be deployed soon. In meantime there are two solutions:
1. downgrade back to pandas 1.35
2. Use period='max' then filter the data using pandas:

# symbol
symbol = yf.Ticker("MSFT")

# get historical market data
hist = symbol.history(period="max")
hist =

st.line_chart(hist.Close)
st.line_chart(hist.Volume)

[vinaynaik]

Great collaboration thank you data professor 👨‍🏫

[keshavarya]

Stop scrolling down the comment section and watch the video

[pygemssoftware]

What did you viewers expect from a professor.

But i still say fantastic. Wonderfully explained. Hope to see more advanced videos

[kamrankerim]

Chanin, you are great! I am doing Bioinformatics M.Sc. and this video helped me a lot. Streamlit is fun.

[FunDumb]

Been searching night and day for a tut like this. Stellar!