How to use Pandas Profiling on Kaggle

Key Takeaways

welcome back to the data professor YouTube channel if you new here my name is Shannon Natasha and Ahmad and I'm an associate professor of bioinformatics on this YouTube channel we cover about data science concepts and practical tutorials so if you're into this type of content please consider subscribing so a couple of days ago I have released a video on how you can install pandas profiling on your own computer and use stupid and notebook to run the pandas profiling to create the report and so some of you might have tried this on the Google collab and encounter some error and so in the previous video I have so in the previous video I have shown you how you can install the pandas profiling inside the Google collab and make it work by hacking it a little bit so in this video I'm going to show you how you can use pandas profiling right inside the cocoon notebook so without further ado let's get started so the first thing that you want to do is head over to the github of the data professor and click on the code scroll down click on Python scroll down and find pandas profiling example click on that wait for it to load a little bit and what you want to click on is the link right here to the capital notebook click on it and it essentially will be the one right here okay you guys my name is rather long and it might be a challenge to type this in to your url okay but if you want to do so give it a try cackle comm / tune in non cinimon / pandas - profiling - example okay so I might provide you a bitly link to shorten the URL so that you can type it easier okay so in this minimal working example I'm going to show you how you can get started in using pandas profiling alright so what you want to do is you want to click on the edit button okay so make sure that you have signed in into your cattle account and so for this you can but the first thing that you want to do is you want to sign in to your cattle account and if you haven't done so please sign up you can sign in using your Gmail using your github okay so before beginning make sure that you have already signed in to your kaggle account and if you haven't yet signed up for it please do so you can easily sign up the traditional way or you can sign in using Gmail or also your github account ok so let's get started so you want to click on the edit button here on the top right and then it will spin up a notebook for you ok and so before beginning make sure to support this notebook by giving it a thumbs up in the previous page I can show you again right right here give it a thumbs up please and so this will help keep me motivated and hopefully other people can discover this notebook as well so that it could be useful to them as well thank you for supporting okay let's begin so you want to import the libraries here and we have numpy pandas and pandas profiling let's run the cell okay and so here we're gonna create a data frame called DF and we're gonna use pandas to create the data frame and it's gonna populate that using numpy random number generator and it's going to randomly generate a hundred rows and five columns and the five column is comprised of ABCDE and let's run that and let's have a look at the generated data frame okay so it works now with the report okay so you might notice that I did not install pan that's profiling it's already pre-installed on Kaggle so you can get right into using it without installing it okay so that's the cool part and here it has to ready generated the reports and let's go down and let's have a look at the widget does it work here okay so the widget works perfectly here so the tabs are working without an issue and this is for the column a column B column C Island de column ye right so there the overall descriptive of the columns and the scatter plots here okay so you have 25 combinations and the correlation showing ask the heatmap okay and you also have spearmen candles and fig and the missing values and the matrix of that and the samples the first ten rows and the last ten rolls okay and similar to the last video let me show you how you can generate the so similar to the last video let me show you how you can generate the report after HTML file so that it will be portable and then you can email this to your colleague scroll down alright so in the saving the report you want to copy the code here and then paste it here and then you want to customize the name okay so in the last one I call it report dot HTML save it let's have a look it said generated yes it is let's have a look inside the file alright so the contents is shown here perfect so you wanna head over to the right panel here and in the data you want to click on it and then you're gonna notice that it has to drop down here and in the output you want to click on it here as well cackle working and notice the report dot HTML and then notice that on the far right you see a download button so you want to click on that one okay and let's click on the report and so similar to the previous video the report as the HTML file so the report here is interactive meaning that you can click on the various headings here and it will go to the appropriate sections okay and the panels here are working perfectly okay all right so you can share this to your colleague and this will allow you to do very rapid expert ory data analysis so hopefully this is helpful to your data science projects and if you find value in this video please give it a thumbs up and I appreciate if you also subscribe if you haven't yet done so and so as always the best way to learn data science is to do data science and so please enjoy the journey thank you for watching please like subscribe and share and I'll see you in the next one but in the meantime please check out these videos