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Hello guys.

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So we are going to continue the discussion with respect to Python.

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And in this video we are going to discuss about a Streamlit app.

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Uh, if you don't know about Streamlit, it's a, it's an open source app framework for machine learning

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and data science projects.

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It allows you to create a beautiful web applications for your machine learning projects altogether.

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And the best thing over here is that you even don't need to know HTML, CSS, uh, just by using the

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components of Streamlit, you'll be able to create beautiful web pages, right?

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And right now, uh, since generative AI is becoming very much famous, Streamlit has been extensively

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used over here to create chatbots.

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Okay, so we'll be discussing all about this.

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Uh, as I said in this video, we will try to understand from basic.

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We'll see what are the important components with respect to Streamlit and how you can get started with

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Streamlit.

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Okay.

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So let's quickly go over here.

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Uh, so here it is.

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I've, uh, given this particular definition.

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So it is nothing, but Streamlit is an open source, uh, app framework for machine learning and data

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science projects.

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It allow you to create beautiful web applications for your machine learning and data science projects

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with, uh, Python scripts.

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Okay.

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So first of all, we will go ahead and, uh, you know, import this library.

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And for that I really need to install in the requirement dot txt.

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So I'll go ahead and update it over here.

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So let's quickly go ahead and do the installation.

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So pip install minus r requirements.txt.

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Over here you can see that the installation will be taking place.

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So here uh once the installation takes place you'll be able to see I will be able to start using this

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particular library.

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So here let me quickly go ahead and open one of the.py file.

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So here, uh, I will just go ahead and write streamlit.py or let me just go ahead and write app.py

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file.

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Okay.

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And this is where I'm going to write my code.

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So here you can see the installation has taken place.

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Now to start with Streamlit.

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Uh, what I'm actually going to do over here is that I'll go ahead and import Streamlit as st.

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Okay.

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So we are going to import this as SC.

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St is the alias and this is the library that we are using.

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Along with this, let's go ahead and import pandas as PD.

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I'll be importing pandas.

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I will also import numpy so that I'll be using some of the basic applications.

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And in order to start with the Streamlit web application or here, I will first of all show you some

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of the important components.

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One of the component is nothing but title, right?

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So let me just go ahead and write this title over here, and I will just use this s t dot title, okay.

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S t dot title.

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And let me just go ahead and write something like hello Streamlit.

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Okay.

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Now we will go ahead and execute this.

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So in order to execute it, you know that this app Dot Pi is inside your 14th Streamlit folder and it

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is, which is inside this entire Python folder.

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Right now I'm in my Python, so I'll go ahead and write CD 14 Streamlit.

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And in order to run this app dot pi file.

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Right I will just go ahead and write streamlit run app dot pi.

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So once I execute it here, you will be able to see that I will be getting this option, which is called

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as Allow access.

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So I'll click on this and my web browser will get loaded which will look something like this.

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So here is the default message that is nothing but the title.

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And the best thing over here is that I just used.

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I did not write any H1 tag or anything as such.

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I just use this h2.sd dot title component.

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Okay, and if I go ahead and inspect this, you'll be able to see that this will automatically get converted

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into an H1 tag.

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Right.

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And these are some of the Div containers which will be created by that same code that we have seen.

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Right.

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That is SD dot title okay.

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Now this is very much easy.

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Let me just close this.

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And here you can see by default it will be running in this localhost.

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And the port is 8501.

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So this is how you run the Streamlit app by just writing Streamlit run app.py.

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Okay.

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Now, uh, let's go to the next step and, uh, let's display a simple text.

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So here I want to display a simple text.

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Okay.

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Now this simple text I can go ahead and write it in my page.

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So I'll go ahead and write SD dot write.

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And I'll say, hey this is a this is a simple text.

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Okay.

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Uh, this is how we write in the page, uh, of the web app that we are specifically creating with the

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help of Streamlit.

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Okay, now let's go ahead and create a simple data frame, and we will try to, uh, print this data

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frame.

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Okay.

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So here I will just go ahead and write df pd dot data frame.

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So I have my first column, I have my second column.

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And these are all my information okay.

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Now let's go ahead and display this data frame.

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Display the data frame okay.

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Now displaying the data frame again I can go ahead and write SD dot write.

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And I'll say hey here is the data frame okay.

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Let's see how the data frame will get displayed.

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So I'll go ahead and write SD dot write again.

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So write is a function which will be able to display this particular data frame okay.

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So once I display this uh, the next thing what I can do is that I can also create my line chart.

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Okay.

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I want to probably go ahead and create a line chart.

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So I'll go ahead and create a line chart okay.

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Now in order to create a line chart again we have to use St.

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And then we have something called as st dot.

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Here you can see line chart link button.

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Everything is there.

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So we will go ahead and use my line chart and let's create a chart data okay.

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So this will basically be my chart underscore data I will create some data over here some basic data

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I'll go ahead and write hey this is nothing but PD dot data frame.

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And let's go ahead and create it okay.

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So PD dot data frame here I will say hey go ahead and uh use NP dot random dot rand n random numbers

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use 20 comma three.

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That basically means how much, how many rows and how many columns.

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That is three columns and 20 rows.

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Okay.

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And then I will just go ahead and create my columns also.

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So columns will be nothing.

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But since I have only three columns so I will go ahead and write a comma b comma c okay.

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So once I execute this uh I will be able to see this line chart.

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And inside this line chart, this will be nothing but my chart data.

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So let's go ahead and execute it.

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So I will just go ahead and delete this and let's save this.

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And here I'm just going to run Streamlit run App.py.

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So once I execute it uh, this is my web browser that has got opened.

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And uh, here you can see how beautiful chart it is being able to display.

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This is my data frame altogether, right?

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I can also expand it.

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I can also download it.

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Right?

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If I download it, I can download it in the form of CSV file.

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So here is also on my chart which looks really awesome.

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I can save this as a SMS or svg png file right?

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You can also open in Mega editor, compiled view source anything that you want.

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Okay, so this also looks, uh really good.

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And here you'll be able to see all this particular information.

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I can also zoom in.

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Zoom out okay.

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Now this is a very easy way of creating this quick application.

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And here I do not even have to use much HTML.

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Right.

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So this really becomes very much easy for a back end developer who really wants to develop a quick POC

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or interactive POC and probably show it in front of anyone.

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Right?

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So, uh, this was one example.

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Uh, let me just go ahead and play with some more examples.

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Okay.

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So I will close over here and, uh, this time I will I will just go ahead and create one more file.

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And this time we are going to work with widgets.

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widgets.py file.

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Okay.

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Now with respect to this widgets, uh we'll create uh some more widgets.

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We'll use some more widgets.

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Uh, so here uh, widgets basically means uh we will try to create some more interactive application.

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And for that Streamlit also provides some amazing basic widgets.

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Okay, so first of all I will go ahead and import Streamlit Streamlit as st.

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Okay.

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So once we define this uh okay then I will just go ahead and write my St dot title.

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So HD street dot title.

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Let's say Streamlit.

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Text input okay.

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Like we have an option of putting text input.

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So let's say I will create a variable name.

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And I will go ahead and write street dot text underscore input okay.

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So this basically means I can give an input in my text box.

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Let's say here I'm going to say end.

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Enter your name okay.

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Now, if I execute this over here, you'll be able to see that, uh, I will just go ahead and say if

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name colon.

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Okay.

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That basically what does this basically mean.

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Right.

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If name colon that uh, see when I run this particular uh widget.py file, right when it opens the Streamlit

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app, it will initially show me a text box.

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And if I'm putting some information and if I'm pressing enter, that entire information will get saved

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in this particular name variable.

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So if I go ahead and write if name then here you can see s t dot write.

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And here I'm going to just go ahead and call this okay.

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So let's say I'll go ahead and write hello.

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And this should be my whatever name that I'm actually giving.

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And it should display this right now.

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Let's run this okay.

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Here.

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This time I'll go ahead and write Python widgets.py file.

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Okay.

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So if I go ahead and execute it.

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Uh oh.

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Sorry.

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It should not write Python but instead I should write Streamlit.

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Run widgets.py.

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This is the command that we usually use in order to run this particular file.

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Okay, so let me repeat it.

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Streamlit run widgets.py.

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So once I execute this here, you'll be able to see that I'm getting this particular information.

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Now here when I as soon as I write my name Kirshnik I press enter.

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So here you can see that, uh, Streamlit has no attribute, right.

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So that is the problem because I wrote double two doubles, two doubles.

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Right.

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So I will quickly go ahead and fix this issue.

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Now, let me run this again.

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And here you have my browser.

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Now let me go ahead and write my name Krish Nayak okay.

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And let's press enter.

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So here you can see this is the message that is getting displayed.

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Perfect.

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Now let me do one thing over here.

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Uh, here.

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I'm not going to stop over here.

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Okay?

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I will also try to use some kind of slider.

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Now, in order to use the slider, uh, let me do one thing over here.

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Uh, I will just go ahead and say, hey, uh, let's create a slider.

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So for creating a slider, I will say, hey, let's create a variable called as age.

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I'll say TX dot slider.

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And with respect to this particular slider, this is again another component that we can use over here,

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which will be an interactive component.

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And here I'll say, hey, select your age and the age value will be between 0 to 100.

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And here you can see the third parameter that I have uh uh that I'm actually giving is 25.

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Okay.

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We'll run this and then you'll be able to understand it okay.

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As soon as I probably select this, uh, what I will do is that I will just go ahead and write SD dot

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write.

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Your age is something like this.

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Okay, now let's go ahead and reload this okay.

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So here you can see select your age.

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So once I go ahead and update this.

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So minimum is 25 that I can select over here.

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And uh initially if I reload this you will be able to see that it is pointing to 25.

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Right.

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I can also reduce it.

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But minimum first of all it shows 25.

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Then I can select any age and automatically this updation will basically happen.

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Now this is one of the amazing component that is probably present over there.

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There is also a component which is called as select box okay.

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Now in order to select box is just like using a drop down box okay.

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So here you will be able to see that to in order to use the select box, let's say I will go ahead and

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create this something like this okay.

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So I'll say hey this is my options.

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I want to go with Python Java C, C plus plus JavaScript.

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So this will be a list of options I'll say S3 dot select box.

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Choose your favorite programming language and I'll give the options over here.

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So this will basically be my choice.

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And here you can go ahead and write that particular choice.

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So I'll save it.

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Let's go ahead and execute it again.

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So I will reload it.

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So here you can see hey I can go ahead and select any of this particular language like JavaScript and

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automatically are able to write it.

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So this looks like a very good form because I'm, I'm not writing much, uh, much information over

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here.

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Right.

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It's it's very much simple.

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It's very much easy that I'm able to get this entire information right.

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Uh, let's try one more thing.

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Okay?

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Let's try, uh, uh, data frame, uh, in short, and, uh, let's see how it gets displayed.

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So here I've already shown you the data frame anyhow.

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So let me just take this particular data.

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I will go ahead and import pandas as PD import pandas as PD.

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Okay.

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So the main thing over here is that they are lot of interactive components that are available.

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So here I'm creating my data, I'm converting that into a data frame.

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And I'm writing S3 dot write okay.

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So again if I go ahead and reload it.

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So this is my entire data frame.

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And you can actually see this particular data frame right.

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So like this I can quickly go ahead and create my uh entire form itself.

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Okay.

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Um, I also have an option to probably create an upload button.

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Okay, for for the file upload.

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So here what I will do in order to create an upload button, I will go ahead and write uploaded underscore

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file.

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So this will be my another component.

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And I'll just go ahead and write s t dot file uploader.

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And I will say hey choose a CSV file okay.

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Choose a CSV file and I can basically go ahead and choose this.

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And I'll say, hey, let's keep that, uh, type as CSV.

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If I want different other files, I can probably keep this in the form of list.

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It is up to you.

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Okay.

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Um, and you will be able to do this right.

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So finally, if you go ahead and see if uploaded file is not none.

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Okay, I can go ahead and write.

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DF is equal to PD, dot read underscore csv and I will give my uploaded file over here.

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And I will just display that particular uploaded uploaded file in the same page.

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That is nothing but DF.

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Okay, let me do one thing quickly.

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Mhm.

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I will save this entire CSV.

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Okay.

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So I'll say hey DF dot two underscore CSV.

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And let me just save it as uh sample data dot csv.

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The reason is that I just wanted one sample data.

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That is the reason okay.

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So I will go ahead and execute it.

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So this may have got created.

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Uh let's go ahead and use this particular CSV file.

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So I will go to this particular website and I'll go back to over here.

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I'll click on browse.

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I will go inside this and let's go ahead and upload this.

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So once I open it here you can see that I'm able to display it right.

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Which is again good.

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Uh altogether.

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Right.

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So these are some of the important components.

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Again, I would suggest go to streamlit.io.

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I think this is the most easiest framework that I've seen.

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There are a lot of components which you can go ahead and check it out.

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And uh, as you'll be seeing that if I create any videos, right, let's say over here, I want to play

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with text, I can go ahead and play with text images, videos.

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So charts, widgets.

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So I've just discussed about widgets.

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They are also charts.

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You can use different different charts.

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You can use different different graphs.

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You can even use page navigation.

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So in short just by using this you'll be able to create your entire, you know, the web application

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that you actually require.

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So, uh, this was it.

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Uh, now in my next video, what I'm actually going to do is that I'll just try to develop a machine

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learning application and interactive machine learning application and show it to you.

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Okay.

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I know, uh, if you have not learned about machine learning, don't worry.

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But just to give you an example, how does the Streamlit app looks like with the help of a end to end

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machine learning project?

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I really wanted to show you that.

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Okay.

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Um, but again, uh, if you don't know any machine learning algorithms.

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So I would suggest please go ahead and check some of the algorithms and automatically you'll be able

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to understand it.

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Okay.

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So yes, this was it for my side.

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I will see you all in the next video.

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Thank you.