Build and share your own data analysis app quickly and easily using Streamlit!
Building a Data Analysis Web App with Streamlit
Data Visualization with Streamlit
Implementing Streamlit Web Apps Using Various APIs
Learn quickly and easily with projects,
Developing Streamlet web apps for data analysis!
Streamlit is a tool that allows you to quickly implement a prototype-type web app using data . Its biggest advantage is that you can quickly and easily create a web form that can be visually verified by a data web application with simple functions.
Streamlit uses Python . Since it is a familiar Python environment for handling data, there is no resistance to using it, and it is simple because you just need to call the appropriate function after installing the Streamlit package.
Streamlit reads your Python script and runs a simple web server. You can see the results right away, and you can also see the changes in real time as you update your script.
You can easily create web apps with the widgets listed below.
Build dashboards using simple yet powerful charting features.
You can learn quickly and easily, from installing and configuring Streamlit to building various data-utilizing web apps using Streamlit.
📖 Check out the services created directly with Streamlit and learn how and what the process is like to create them!
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Automatically mass-produce blog posts with ChatGPT
📌 Demo Page (Go)
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File sharing service
📌 Demo Page (Go)
Drawing stock charts
Create your own chatbot
Create a lotto number generator
Creating an MBTI Encyclopedia
Instructor's Key Background
Operating Sites and Books
Who is this course right for?
If you want to quickly create your own data analysis web app
Anyone who wants to effectively visualize data through a web app
Need to know before starting?
Python
Pandas
All
14 lectures ∙ (1hr 49min)
2. Text component
04:43
9. Add sidebar, tabs
05:41
All
21 reviews
4.9
21 reviews
Reviews 3
∙
Average Rating 4.3
4
The delivery is good and clean, but it feels a bit hectic in the latter half. (I thought the flexibility of fast distribution was the advantage of Streamlit, but I wonder if it would have been better if you explained the distribution using GitHub in a little more detail so that it could be done better in practice.) Still, overall, I think I was able to learn about Streamlit quickly.
Thank you. We will improve the shortcomings you mentioned and update the current lecture. Thank you for your valuable feedback!
Reviews 27
∙
Average Rating 4.9
5
I am in charge of platform operations, and I was able to somehow handle the backend, but I had a lot of concerns about the frontend. After learning about Streamlit, many issues were resolved, and the instructor's lectures were especially helpful. Thank you very much.
Thank you for the good review^^
Reviews 1
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Average Rating 5.0
Reviews 1
∙
Average Rating 3.0
3
-The installation and environment setup parts were difficult. The lecture content wasn't detailed enough, and because of that, I had to search Google or Naver to fix errors. -It would have been good if you had mentioned at the beginning of the lecture that signing up for Naver Clova Studio or ChatGPT services incurs charges... You mentioned it later, so I had the hassle of having to cancel the payment. 😭..😭 -From lecture 9 onwards, the difficulty level suddenly increased and I couldn't understand the class content well. Especially the part at the end where you automatically complete and deploy a blog... -Overall it was helpful, but it seems there's still some distance to go before being able to create something with streamlit using python.
$8.80
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