 Hello everyone Okay, I think you're all tired already Okay, I'm from JetBrains. I'm part of JetBrains team based out of India so How many of you heard of JetBrains? Wow that motivates me now Okay, and how many of you tried PyCharm? Okay, I'm in front of the right audience then so not just PyCharm. We have multiple products for Multiple languages and we have a Kotlin language itself and Team tools this is how we grew from IntelliJ starting with IntelliJ idea the company was known then IntelliJ and then we grew with multiple products and PyCharm if you see that was in down the line and So we have multiple Tools IDs for different languages for your favorite languages. That's how so quickly. I'm just how many of you try used Jupyter notebooks Great, so I'm gonna talk about I'm gonna show a quick demo of Jupyter notebooks integration with PyCharm so Here you go. So First we'll launch a new project And name it Say PISA because this is the the data sets which we are gonna use is of PISA company PISA outlets in US So have you ever tried checked out this tip of the day? No, okay couple of folks Great, so this is a pretty Useful feature from PyCharm many of us avoid it But you know every day choose a tip every time you open it shows a tip which is very useful It shows the shortcuts multiple shortcuts and everything, you know, right when PyCharm We don't need to use moms at all. We just need to use the keyboard for the demo purpose. I'm gonna show the The mouse I'm gonna use a mouse So here's a notebook which we are creating. We are gonna create a new directory which is notebooks and gonna have a file created PISA Python file and if you see immediately it shows the Jupyter packages not installed So that's what PyCharm does so it helps you when you code so it asks you suggests you to install a Jupyter package when you type IP YNB and The file name and then immediately it helps you with the package. It directly downloads to the PyCharm So I'm just taking a data set couple of data sets from Kragel so I'm just Defining so and then now we are let's investigate the data sets which we have so We'll use how many columns and how many rows and it is it shows that So for the quick reference, I'm taking the codes from the Already recorded one so if you see here, it's a 10,000 lines rows with 24 columns And if we go through the columns, there are many unnecessary Columns which we can eliminate that's the most important thing is of cleaning the data set which which we have right So if you see the you the country, I believe it is since we took it from the US US market probably the country should be everything should be US so we can probably ignore that remove that so that's what we are trying to do We are checking the count and it does if you see it's thousand So that means that we have thousand rows that means everything is US so we can simply remove that and Then if you and also we can clear Some unnecessary sets like IDs and price range US USD the price the currency we can remove those and Then we'll add We'll expand the abbreviation for the states and then if you Next we'll just Try to get a plot it in our in our pizza chart and if you see it doesn't work Because that's when you need to use the magic word Matt plot library. So that's what I'm trying to do and then Okay, the most and again if you notice we can use cells different cells in in pie charm You just need to use command shift and enter automatically creates a new cell and every cell is Compiled at the time so you don't have to compile everything together run everything together It is just that cell can be run separately and then We see here. We use this And we have the chart So not just a chart. It is Pie chart, but also we can what we can do is we can plot it on a map. So what we can do is We can take help from plotly So we use it but still it shows a panerra, but again It helps you with all the information saying that hey plotly is missing just you need to import and then it immediate immediately it imports that and This is how it looks the chart looks Right, so that's a very quick demo of how pie charm works and how we integrate a Jupyter notebook and You can find all the information here and thank you so you can find the data set the codes and If you need an evaluation, I mean if you want to try with the Jupyter notebook You can mail us will help you with a couple of months Evaluation license and for students that you have the free license. Thank you. Look forward to meet you at the booth. Thank you