Excel Hour - Learn to Excel with the FP&A Guy

Welcome everybody. Really excited to be here with you. We'll get started in just a moment for Excel hour with the FP and a guy. In the meantime, let me know where you're coming from in the chat. I appreciate it. So please go ahead and put your name and where you're coming in from in the chat, so I know who's out there. Very excited. We'll get started here in a minute or two. You'll see a scroll ticker down at the bottom that will tell you where you can get the file. And also just ask what to let us know where you're coming from in the chat. If you have not downloaded the file, go to my website, the fpnaguy.com/resources there's an Excel file section and it's the first file today. So again, I know there are some people out there, so if you can just go ahead and throw in the comments, what where are you coming from today? Would be appreciated. And we'll get started here in just another minute or so. We're just going to let everybody join and then we'll get started. So excited to have you here with me today. Everybody should be seeing my screen now, except for I shared the wrong screen, so give me one moment. Everybody should be seeing the Excel New Features file. Welcome Benjamin from Sierra Leone, West Africa. Excited to have you here with us. Alrighty, we're just going to give it one more minute. Let whoever else out there that's joining join us and we'll get started. So as we're waiting to get started, just a few things. This is the fourth or fifth time I've. I've done one of these. I don't remember the exact number, but we've covered in the past things such as dynamic arrays, Excel tables using the NA function in graph. In the future. Some things people have asked for is a little bit about modeling, which is something we'll hopefully cover some design principles around financial modeling in the future and also looking at covering some things about Power Query. Alrighty, well, we're going to go ahead and get started, but please, if you're out there and it looks like I'm showing there's about 12 people out there just in the webinar, plus those on YouTube or LinkedIn. Let us know where you're coming from. Thank you, Marcos. Welcome from Sweden. Alrighty. Well, let's go ahead and jump into today's Excel hour. What I thought would be fun to cover is some of the new features in Excel. We'll talk about some of those that are in beta, but we'll also talk about many that have come over to come out over the last couple years in desktop. And so I'm focusing on desktop. There are other things that have come out. Some of these may have come out earlier online or in the mobile, but really focusing on the desktop version of Excel. So we'll jump into it here. Again, if you haven't downloaded the file, you can go ahead and download it using this QR code as well. Just go ahead and click on that there and you can download it. So a Little bit About Me My name is Paul Barnhurst. I'm known as the FPA Guy. Name of my business is literally the FP and a Guy and I have a website called the fp&aguy.com. i studied, did a Bachelor's degree in Business and then did an MBA and a Master of Science in Information Management. I spent about 12 years roughly full time in FP and a working for companies such as Celera, American Express, Digicert. I also did some work as procurement and for the last two plus years I've been running my own business. I'm an FPA influencer. I create a lot of content around fpa. I'm also a trainer, had the opportunity to work with companies around the globe, Dollar General, Walmart, Four Seasons, Highliner Foods and many others. And I'm also a podcast host. I have three popular podcasts. So please if you're if you don't subscribe to them, would love for you to subscribe to them. We have Financial Modelers Corner which is all about financial modeling, Future Finance, which I host with Glenn Hopper who is a true global AI expert worth listening to. And then we have FP&A tomorrow that's all about FPA. So welcome Yurmi from Brazil and I'm hoping I didn't butcher that, but welcome. So here's what we're going to cover. Today we did the introduction of the FPA guy. We're going to talk about new Excel features. We're going to do walk through several examples of the new features. And then I just recently got the beta version of Excel, was doing some playing with Python. So I'm just going to show a few things there and talk a little bit about Python as well. So here on this page this is a list of some of the new things over the last couple years that have come to Excel. And you'll see all these listed in my file with a link to learn more about these and some images for each of them. So there's things such as analyze data. We'll walk through that today. Navigation pane One of my favorites. Finally we have the ability to search and drop down lists. We could search the menu. We can actually show changes. You see Python which is in beta. The last four on this list are all in beta. Regular expression functions, group by, pivot by and percent of functions Checkboxes in Excel, some others Image function Lot of great things. Every month we get Updates with Office365. If you're not using 365 I highly encourage you to get a copy of it. I believe it's worth it. I know it comes with a monthly subscription, but there are a lot of benefits. So now we're going to go ahead and jump into the Excel file here. So I'm going to minimize that and open the Excel file and welcome Demir from BiH. Again, if you're out there, just let me know where you're coming from. I always love to see the different places people are joining us from. So what we're going to talk about, like I mentioned is new Excel features and this first page is for reference. This has some information. What's the status? Is it general release? Is a beta? The name of the feature, a description, a link for you to learn more about these new features as well as an image. And not everything's here. I realize there are other, you know, things that have been made, but this is a good list. This is avoiding some of the most popular dynamic arrays let lambda and focusing on those that people may not be aware of or have used. Welcome Zainab from Nigeria. Glad you could be here. Welcome Justin in Orlando today. I think you were somewhere else last time, so good deal. Sounds like we get to travel. So what we're going to do is we're going to review a couple of these. So these are the ones I want to focus on. And I don't know if we'll get through all of these. We'll see how we do time wise. But these are some of them I want to show you that are new features in Excel. So where we're going to start, if you have the file, go to the tab called Analyze Data and I'd love to know, put it in the comments if you've utilized this feature before. If anyone's used the Analyze Data feature in Excel, let me know. I'd love to know if you've utilized it. Alrighty, so let's show you what the Analyze Data feature is. This is a pretty cool feature. It can get you started on your analysis and kind of hopefully allow you to quickly get an overview of your data. So on the sheet Analyze data, click anywhere in the table here. And then what you're going to do is you're going to go to home and there should be a button called Analyze Data. If you click on that, it's going to bring up this sidebar that says Analyze data. So we're going to walk through what's here first. First thing it has is ask a question about your data and it gives you suggestions like which is the power source for the product category, total quantity by power source as a column chart and other ideas. So that's the first thing you'll notice I'm going to escape out of that next. It has some suggested questions here. If I click on them, we'll provide an answer. We'll get to that in a minute. Then it has this Discover Insights. And over to the right, you're going to notice it has a gear icon. If you click on the gear icon, that allows you to select what data you want to include in the analysis. So are there certain fields you're most interested in? Like if I didn't care about product type, I could just eliminate that. Or power source. If I really cared about count or average instead of sum, I can do that. So there's different things I can do here. I'm just going to hit cancel. And then next it gives us some insights. So I can look at this first one, it said, hey, this might be helpful for you. Price by product category and product name. Then next we have product name has noticeably higher price. So that's the observation and it's showing us all the prices and saying, hey, look, this one's price is way higher than the others. If you go through, there's going to be about 30. You can see 35 if I click all of them. So almost 40 different observations and you can go through and read about every single one of them. But what's nice is let's say I like one of these observations. Say, I really need a pivot chart that shows this. This would be valuable. If you click the insert pivot chart, it creates a sheet at the back of your workbook. So I can see it now and if I click on it, it's a, it is a pivot table. I can see what they put in the product, you can see what they put in the price, and I can adjust it. I also get a, an image. I can adjust that image. So I now have a sheet that shows that information. I can increase you know the size of this graph. I can, you know, edit it however I want. So neck, maybe I want. Let's just say I like this scatter plot and so I can insert that chart. Notice, because it was only a chart, for whatever reason it inserted it on this page. I could always cut it and put it on a new page if I wanted. So I could come here and, you know, stick it at the end and I can see this chart. What's interesting to note is right here in the title, it gave us the outliers. Price and revenue appear to form a cluster with two outliers. So we can see there's a pretty good correlation between the price of a product and revenue. Except for there's a couple out here that have a super high price but, you know, really low revenue, which means we just don't sell many, even though we charge a lot. So there's that. And then last, let's try asking it a question. What is the max revenue for product name? Question mark, hit enter and it's given me the max of revenue by product name. So I can insert that pivot chart and I can see, oh, the 18 volt brushless trim router had the highest revenue I could see what had the lowest revenue. I can also see the chart and play with it. So that's a relatively new feature. It's not Copilot. Yes, it's using, you know, AI, not necessarily generative AI. I imagine that will be incorporated more and more as we move forward. But it's a quick and dirty way to start analyzing your data where you don't have to create the pivot table. So if you have any questions as we're going through these, please let me know. And who's ever out there let me know where you're coming from. I know there's several of you that haven't done that yet. So again, if you have any questions, please just put them in the comments and we will keep going. So that's the first one that's analyzed data. That's a really valuable one to be aware of to do some quick and dirty analysis. Is it going to do all your work for you? No, but nor is generative AI, nor is really any anything, but it will get you started. So that's the first one. The next one I want to go over real quick is I'm going to show you the navigation pane, which is a relatively new feature in Excel, so you could be on any sheet in the workbook. You're going to come up here to view and you'll notice under show, you should have a navigation pane. It will say, hey, welcome, Jacqueline from Tanzania. Excited to have you. So you should see a navigation. It says, use the navigation pane to find data, chart tables and other objects in your workbook. So go ahead and click on that. And I'm going to again, it's going to bring up a sidebar, which is pretty common in Excel. A lot of these new features and things use the sidebar to show them. So here in the sidebar, notice it's highlighted the sheet we're on, but I can click that up. So I have a list of every single sheet in the workbook. And on each sheet, it's going to tell me what's there. It's like, hey, there's a Chart 1. Here's the name of the chart. There's a Pivot Table 1. If I click on it, it takes me to that object. If we look at this sheet here, notice right here it says sort by icon B1. That's text. So it's letting me know, oh, there's text in B1, there's text in B3 to B9, there's text in B11. Then there's text in C13 to 916. And you know, here. So it's going to use different icons here I can see there's a picture. If I click, I can see that picture. Notice if it's an object, not text, but an object, I can right click on it, rename it, delete it, or hide it. So I could change this to say picture for importing if I wanted to, whatever I want to call it. Other things you can do. So like you can rename any sheet, you can delete your hot. You can hide, you can't add comments. And you can also search. So I could say search picture. And it's going to show me everything with the name picture or a picture object. I could search for tables. So I can see, oh, hey, there's table three. There's pivot table. The one thing I wish it had, I could rename any sheet here. I could also reorder them and not. Sorry, you can't reorder. I mean, you can delete them, you can rename them and you can hide them. What I wish it had is I had the ability to comment on cheats. You could provide kind of some instructions right here, but it's still really helpful. Welcome, Antonio. And so that's the navigation pane. That's the second thing I wanted to show. Third, I think we'll go here real quick. This one is a fairly simple one. I'm going to go to the Value Preview tooltip. Okay, so I have this really ugly formula here, right? It's an ugly nested if I would never recommend writing it, but it will work for what I'm showing. So if you go to this sheet with me, I don't know how many of you have ever highlighted a section of a formula and hit F9, but if you hit F9, it calculates the formula so it could say, oh hey, that one's false. If I come down here, it's going to say true because it's greater than or equal to 80. But if I exit right now, this will be hard coded. Excel ran it in the background. That's not very helpful for troubleshooting. I got to hit Escape because if you forget and if anyone's used it, they've probably forgotten it causes an issue. Now though, I can highlight it and notice and it's really small right here where my arrow is. It shows me what that argument is, what the answer is. So what it converts to that converts default, you know, this one here, if I highlight this whole section, you'll see it doesn't, it doesn't work. It's not the whole section here, but if you highlight just this section, it will perform the operation. It will say true. And you can do that with any part of an Excel function, formula, anything that's in your formula bar. And so that's a, that's really valuable because I can't even tell you how many times I, I have not hit Escape when I hit F9 to process an argument and see what the answer is. And then I screw up the formula and I have to rewrite it. So I find that incredibly helpful. There'll be differing opinions on how helpful it is. So that's one I want to show. We'll do a couple more here and feel free to ask questions as I go through these. So we've done analyze data. We showed the window, we've showed the tooltip. What I want to show next is one I can just do right on this page here. So right click with me on your. On your menu bar. If you haven't noticed, there's two things I want to show here. There's a few new things. You can see these links linked to this range. But what I want to show is show changes. If I click here, it, you know, right there where I was, there's no changes. Now let's highlight the sheet new Excel feature and you can see it showed shows. 22 minutes ago I edited cell C26. I changed. I had a misspelling there. You know, I could also click on a different sheet and it shows no changes. Not every change is shown in the desktop version. I will say if you're using show changes, I recommend opening the file online. It does work better online, but it at least allows you now to start seeing changes that were made. So if I go sheet. Let's see, if I look at sheet one, you could see, hey, it in. I inserted the sheet 10 minutes ago. Right. And so that show changes. The second one I wanted to show you, that's at the bottom. At the top, if you click on search the menus, what I'm going to do is I'm going to highlight this right here. I'm going to right click and I'm going to say insert. Sorry, I'm going to right click right in here. Type the word insert and notice it gives a bunch of different options. I'm going to keep typing pivot. So there we go. It's going to say summarize with pivot table instead of insert. If I click on that, it's going to perform that operation. So if you couldn't remember the shortcut or where to find something, you can type it in the menu bar and perform that operation directly from there. So I'm going to click ok. And now it inserted the, inserted the pivot table. So I could put the student and maybe I could put, you know, grade right here, whatever. I could put test here, which I think is just the test score. Yeah, right. And so now, now I have that pivot table that I can work with. And again, I could do other things like group pivot. And so it says group selection. I got to highlight a couple things for it to work. So let's say group selection C. I could now group these cells. I'll say group cells and it created a group. So anytime you're in pivot table table, you know, formulas, you can search something and perform that operation. You can bold things, italics, whatever without having to go to the menu bar without using the shortcut. I don't use it very often. I generally know the menu bar well in the shortcuts. But if you're trying to remember something, it can be helpful. I want to show that one. The next one I want to show is I'm going to copy and go ahead and do this with me. I'm going to copy the names from this table or even I could just come over to. We'll do it from Value Preview tooltip. If you copy these names here, go ahead and do that with me. We're going to copy it down here. What I want you to see is let's say I want to create a drop down list. I come here to data, I come to data validation and we're going to say list and our source is going to be this range right here. We'll click ok, now what I did is I put it in this cell. Probably shouldn't put it in the cell for the list. Let's just redo that. We'll do it right here. I'm going to click Data Validation, we'll select List, we'll select this range and we'll do it again. What I want you to notice if I start typing a name like I type the letter P, I now get a drop down list. That used to not be the case. You used to always have to filter through the whole thing. Recently they created an automatic dropdown list. If I type H, type E M, I get a list of all the names and if I keep typing it reduces down each letter you go in. So please, if you have any questions, let me know and if you're new out there, let me know where you're coming from. But that is the dependent, the new dependent drop down. So what we've talked about so far, some of the features we've covered is we've talked about Analyze Data, navigation pane, Value Preview, tooltip, and on this page we covered the search menus. We'll, we'll take about another 15 minutes here and go through a couple more of these. Why don't we next show the image function. So the image function is a relatively new function in Excel. Here's the syntax for it. Equals image, the source of the image if you want and then everything else is optional. You can give it alternate text sizing, height, width. So it's a URL link that it wants. So if you come here you're going to see this is the URL link. You just have to put quotes around it. Let's say I go out to, go out to Google for a minute here and I'm a big Utah Jazz basketball fan. So I'm just gonna type Utah Jazz basketball logo. Who knows what I'll get because it feels like every year they're changing their logo. All right, so here's an image we have. What I can do is if I right click here, I can say copy that image link. Now I can come back in here and I can say equals Image, open it and you'll see it gives me the argument down there, source, copy in that link, close it. And I now have the image and I could resize it. I could also add a height and width at the end if I wanted to. So I have different sizing options, but you can pull any image and import it. You'll notice on all these new Excel features, everything right here is an image that I just created to give you some ideas of what these different things look like. All right, so that. That's the image function. You guys can kind of play with that. I imagine you could see where that's helpful. Maybe we have some products you want to show images. You're doing a competitor analysis. You want to bring in a logo. You don't want to copy and paste and download all the images. You could link to something out on the web. All right, give me one second here. Are there any questions from anybody? So far it's been relatively quiet. Please let me know in the comments. Is this helpful? Are you finding the information useful? Any other kind of questions you have? It's always good for me to get a little bit of interaction. There's that one. The next one is import data from a picture. We're going to do that one together. So if you know I have an image right here, you want to click on the image, click anywhere in this image. Justin, why is this better than just posting an image? It's not that it's necessarily better, Justin. It is. It's a different way of doing. Means you don't have to download it and upload the image. So it's going to use less size in your file. It also sometimes can be quicker. It's not. It's not necessarily better or right or wrong. Google's had it for a long time. A lot of people find it really helpful as a quick way, especially if you already know, like, let's say you have a bunch of links you're already aware of. Instead of downloading 30 pictures, just import all the links. You could set it up automatically. Somebody just sends you all the links and you're done. So it could be more effective. It's not necessarily better. Hope that answers the question, Justin. I still often download images and import them. It is another way to do it. Welcome Veronica from Bolivia. Thanks for joining us. Now, what I want to show is this is something that's been available in mobile, but they brought to the desktop recently. If you come right here, I'm highlighting this image. If I come to the Data tab, you'll Notice there's this opportunity. So I'm going to click on the image, I'm going to copy it, click off the image, come to from picture and say picture from Clipboard. So what I did is I clicked on the image, I click copy, I clicked off the image and on this from Picture, I select from Clipboard. And it's going to analyze the image. You see, it takes it a minute and it brings up what it was able to discern from it because it has these little down arrows. It kind of confuses it and sometimes it thinks they're its own column. But you can see in general did pretty good. Brands are all right. Ryobi, you can see this outside of right here. They got and they highlight in red the ones they recommend you check. They got Power Toots instead of Power Tools. I could fix that. I can click on Review and I can go through and review all of them. I can accept it or change them. And then when I'm ready, I can go ahead and say insert data. I'm going to say insert anyway. And you'll notice it inserted it where I was. I'm just going to drag it down here and you can see it got a few things like wrong. This column didn't get aligned with this. So I could move that over. Power Tools here was capitalized. But on the, for the most part, I'd say it's 99% there. I, I make a few little tweaks and it's done. Now it is only going to be as good as your image. Right. And so that's something to to remember is if you have a bad image, it isn't going to do a great job. It's just OCR type scanning. It's analyzing it. You can do it from a picture that you've downloaded. You can do it from the Clipboard. I did it from the Clipboard to be quicker. Yeah, you could copy you. I don't think it has to be in Excel. I honestly haven't tried Justin, but I don't believe it does. But you could also just take a picture from a file. You can go open any image, any file you want. So a PDF you can open. If you're trying to do a PDF the way I recommend you do it. And I'll just show one example here real quick. Under Get Data there is an option to get something from a PDF. So I'm going to diverge here for a minute. I hope everybody will indulge me and just show this example. And this is just so you know, this is in my Power Query course that I. That I offer. So if I come here, we'll go to training clients and I'll find. Let's see. Bell course, Power Query, loading data via a PDF. So let's say I bring this in. I'm going to say sales rep data. Why is it not letting me import? Oh, it's because I'm using OneDrive and it's in the cloud right now. I need to go download it. So give me one second. I gotta go to the folder. I think this will be worth it for those who have never done this to see this. So just bear with me one moment. What had happened there is I have a lot of my files only stored to the cloud and so it's saying, hey, your file is not really there, you haven't downloaded it to your computer. And it looks like I'm having an issue with OneDrive right now. But normally you can bring it in through the Power Query editor. I apologize about that. But Justin, you could bring it in there and then you can edit it. The fact you can edit it, you can make changes. I recommend if you're trying to get data from a PDF, to always do it via Power Query. I'm going to just kick off my. Me one Second here, my OneDrive, see if I can figure out why it's not working. All right. It's reconnecting. So if there's time at the end, I might be able to show it to you. But for now we'll keep going. All right, so we've talked about the image function. The other nice thing with the image function is you can resize the images as well. You can choose what size you want and it's all from the web. So again, bigger size isn't necessarily bigger memory and some of those things. So we've covered import picture. I want to go through two more here. One, I'm just going to show you that you now have the ability under sort to sort on conditional formatting icons. So if you click that, we could say score. We want the green on top and it will sort that first. I could come here as well and sort. I could sort by red. So I could put red first. I don't love the sort by icons. Sometimes it takes a little while to play with, but it is nice if you need it. I haven't found a ton of use cases for it. Here's one you could do. You could create a star rating and then you could sort it by the stars. It is a nice feature. There are times it could Be handy. The last one I want to do and then we're going to spend a little bit of time on Python is data types. I'd love to know, has anyone used the data types in Excel? If you come up here and click on it, there's four data types. There's organization, there's stocks, there's currencies and there's geography. At one time there was going to be over a hundred data types. I'm not sure what happened. Excel had them in beta, but they never made it to release. There was things like weather, data types. There was Pokemon Diet, all different types of data types, but only, only these four made it. Organization is ones you can create in Power Query or if you bring in data from Power bi, they're going to be custom data types. We're not going to talk about those today. We will show the stocks and the geography. So here I have a list of companies, right? These are some of the biggest companies in the world. Apple, Microsoft, Nvidia, Meta, etc. First thing I'm going to do is I'm going to come up here and click on stocks. It's going to look at these and convert them to a stock data type. And on a couple of them you'll notice it figured it out for Apple, Microsoft. You can see these are all data types. If you click on them, three of them, it's like, hey, what do you really want? It didn't find Saudi Arabia Aramco. It's finding no results. I'm not sure why I could. Yeah, even if I turn, say Saudi, that should be a stock, but it's not finding it. Next one. If I come down here to Berkshire again, it did. It's not finding it. So I could go out and find the ticker symbol for it and put it in. I think it's bkh. We could see what happens. Nope. Look like that's Black Hills. So we'll just put Black Hills here for now. I'm going to select it and then let's see what happens with Nvidia. It wanted Nvidia Corporation and you'll see there's a number of different options for Nvidia. I'm going to select the nasdaq. So I'm going to click here and click Select. So I have nine data types here. I'm going to go ahead and delete this. Sadia, Ramco, Ramco 1 just for now. Now what I want you to notice is if you click on it in the background, it has a card. All of this data is now Available, the price, the extended, the official name, the last trade time, previous, close, high, low, etc. So what I can do is I could right click here and I can see data type. I can show the data type card and see if I can get here. We can insert different things. So I could say equals this if I wanted to dot and here's all the options. I could say I want price. So I'm going to come down here, find price and notice since this is a table by default, I'm not sure how, why some of those are white, we're going to change those all to black. But by default it spills it down the entire table. So I have the price here again I can this, I can type a dot and I can say give me the 52 week high. Now I got it. For each of these I'm just going to highlight this right here and paste so that we don't run into that white Again I could do this one now again I can do a dot. I could say give me 52 week low price. So I'm going to come down here, find price and notice since this is a table by default, I'm not sure how, why some of those are white, we're going to change those all to black. But by default it spills it down the entire table. So I have the price here again I can this, I can type a dot and I can say give me the 52 week high. Now I got it. For each of these I'm just going to highlight this right here and paste so that we don't run into that white Again I could do this one now again I can do a dot. I could say give me 52 week low and anytime I hit refresh it's going to refresh this information. I can actually come up here, click refresh and have it refresh the stocks. There's even a way to set it to automatically refresh stock. And I'm trying. I haven't done it in a long time so I'd have to research it. It's relatively new. Oh, there it is. Refresh settings for stocks. You can come in and you should be able to do some settings there on it. So right here, refresh automatically every five minutes. So I'll say oh yeah, that works. And it's going to re every time you open the file or when the file's open, it will refresh those prices every five minutes. If you want to see a list of all the different types available, here's the 20 different data elements. Price, earnings, Dividend yield, open, high, low, close, beta, shares outstanding. These are the different things that are available for that data type. So if we come back here, we could also go out and we could, we could insert the logos here. So instead of have a copy image and try to get them to fit in the cell, if I did image went out and found an image I could copy it in, it's automatically going to resize to the size of the cell. So that's an example where I could use the image function. Next, let's convert these so 10 largest cities globally. I'm going to come up here and I'm going to hit geography and notice it picked up every single one of these again. I can get a card with information about about each of them. I could come here and I can hit that and do a dot and I could add whatever I want. Abbreviation, population, time zone. I could even add it. There's an image here. So it's going to automatically bring in the images without using the image function. It's it. So it brought in images for each of these cities. If I didn't like them, I could find other images. Now I could come here and just do dot population if I want. Can also do time zone. So that's the data type function. I'll pause here for a minute and see any. I'd love to know any questions or as people are watching that, does anyone see where they might use some of these things? I'd love anyone to share in the comments. Hey, this could be really helpful here or no, I don't really see myself ever using it. Please let me know in the comments if you can think of any ways you might use this. And next I want to spend about 10 minutes just showing you a little bit of Python. I. I haven't had. I haven't had Python in Excel today. I was able to get it. Get it. It's still in the preview. I think Python and Excel will open up a lot of great opportunity, especially when you combine it with chat, GPT or copilot and use generative AI to help you write functions. I'm just going to show a couple basic things here on Python. Kind of more to whet your appetite than anything. I barely started playing with it. It's not like I know it well yet, but I thought it would be fun for you guys to see this for a few minutes. Let me find my file I want here. Okay, so what I've done here is I just have a couple different examples. I'll share the videos. I pulled these from but basically I have a table here and what I've is I can reference a data set in Python. How it works is a couple things. First, you're going to see a Python section in your formula ribbon. You can click Initialization and it will give you some information of what, what types of Python are preloaded, like Numpy Pandas, things like that. There's a diagnostics where you could look at it and it will run diagnostic on your page if you have error. If you also click Insert Python, it's gonna bring up a tour you can do and several examples to get you started of things you could do. Like here's a pair plot, here's a scatter plot, this one's a linear regression. Obviously many of the, many of the things you can do with Python you can also do with Excel, but there are also some mixing and matching. There's things such as K means clusters and other stuff that you could do in Python that you can't do with Excel. Veronica, how could you find the tickers of companies? I would just go out to Google. That's going to be your quickest way. Sorry, I just saw the question. I think it sometimes takes a minute to come through. But Veronica, to answer your previous, like, if the ticker doesn't show up, I'd either look on my phone on a stock app or just go out to Google. And you should, once you put in the ticker, it should find it. I've found that pretty much almost always works. If you can't get it to work, then there's, there's some reason they don't have it, like the data set's not right or something. But I pretty much always found if I put in the actual ticker, it will find it. The linear regression, obviously many of the, many of the things you can do with Python you can also do with Excel, but there are also some mixing and matching. There's things such as K means clusters and other stuff that you could do in Python that you can't do with Excel. Veronica, how could you find the tickers of companies? I would just go out to Google. That's going to be your quickest way. Sorry, I just saw the question. I think it's sometimes and you're welcome, Ronnie. I see the. Thank you, appreciate that. All right, so how Python works, it's a little different, so I'm just going to show some basics. Notice over here, when I clicked on Insert Python, I have now three different sidebars I can pull up. So the first thing with Python how it works is you hit equals py and then if I hit tab notice, it changes my formula bar to be Python. I can now enter Python. I don't have to start with equals and if I hit Enter, it's going to give me more lines for code. You actually have to hit Control Enter to run things. The next thing I want to show is notice right here, a data frame is just referencing a data set. So I've referenced this first data set. If I takes a minute to come through. But Veronica could answer your previous. Like if the ticker doesn't show up, I came in here, I'll show you how I could do that. I could type py and then highlight this and it creates that code. Now if I want it to run, I have to control enter. I can't just hit enter. Enter takes me down to the next line. If I hit Control Enter, it thinks for a minute and it creates a data frame from a data frame. I can click on it and see the data. It's kind of a card. It will say anaconda. I could also come up here and it also gives me, it gives me two options. Do you want the Python output or do you want the Excel value? So I could say, hey, I want the Excel value. That is going to show the data. There was something in the way. So it's not working. So I'm going to hit Ctrl Z, go back to what I had, refresh it here and give me just one minute. I'm not plugged in on my laptop, my battery's running low. So give me 10 seconds here. All right, there we go. Other things you're going to notice with the card is you get this little plus similar to the stock data types and it has different fields. You can do an array preview. So right here you'll notice I said, hey, give me an array preview of the data frame. I could also do a string and it shows this data as a string. There are some, some things there not really very helpful. You can say, hey, what type of python? Okay, the data frame comes from Pandas. What is it? That's the very basic beginning of, of Python. Here's just a few other examples and I'll share the video here in a minute. I pretty much spent maybe two hours look on my phone on a stock app, or just go out to Google and you should, once you put in the ticker, it should find it. I found that pretty much almost always works. If you can't get it to work, then there's, there's some Reason they don't have it like the data set's not right or something. But I pretty much always found if I put in the actual ticker, it will find it and you're welcome, Ronnie. I see the. Thank you. Appreciate that. All right, so how Python works, it's a little different, so I'm just going to show some basics. Notice over here, when I clicked on insert Python, I have now three different sidebars I can pull up. So the first thing with Python how it works is you hit equals py and then if I hit tab notice, it changes my formula bar to be Python. I can now enter Python. I don't have to start with equals and if I hit enter, it's going to give me more lines for code. You actually have to hit Control enter. A little over an hour, maybe an hour and a half if that. With this today and watch to couple videos to learn on the Python and, and so many of the things you can do in Python you can also do in Excel. But here's the, here's some data to data, product, quantity, price cells right here. What I want to show is I've selected the data frame and I've typed the word describe. And just by doing that, control enter. Going to run here. All right, wanting to run a little slow, we'll give it a minute to run things. The next thing I want to show is notice right here, a data frame is just referencing a data set. So I've referenced this first data set. If I came in here, I'll show you how I could do that. I could type py and then it brings up information about the data, the count, the mean, the standard, the highlight this and it creates that code. Now if I want it to run, I have to control enter. I can't just hit enter Enter takes me down to the next line. If I hit Control enter, it thinks min, 25%, 50%, 75% and max. Yes, you could write formulas for each one of those or you could use statistical analysis, but that's really quick. Right? One formula it just spilled and gave me all that information about quantity, price and sales. Next I came down here and said, well, I want it for just the product column. So it said, hey, the product column has 26 for a minute and it creates a data frame from a data frame. Icare 6 unique, the top one, the frequency and it, it runs that analysis. As you start getting more comfortable, you can do things by, hey, say I want to group my cells by date and it, it's going to give me A summary by all the unique dates and some the cells. Yes, you could do that in Excel as well and click on it and see the data. It's kind of a card. It will say anaconda. I could also come up here and it also gives me, it gives me two options. Do you want the Python output or do you want the Excel value? So I could say, hey, I want the Excel value. That but it just shows what, you know, kind of capable here. I had some fun right here. These are the main, there are a couple others you can do, but these are some of the main graphs that are built in. And so what I did is I said, hey, take my data, group it by month and give me the graphs. And so if I click here, I can get an image and see what each of them look like. I can also export them as an Excel value. And so some of them I like are is, you know, histogram is going to show the data. There was something in the way. So it's not working. So I'm going to hit Control Z, go back to what I had, refresh it here and give me just one minute. I'm not plugged in on my laptop, my battery's running low so give me 10. Nice to do box plot. You could also, as you get more comfortable, you could do things like a K means so Python where Realiseconds here. All right, there we go. Other things you're going to notice with the card is you get this little plus is going to differentiate itself from Excel is if you want to do machine learning like so let's say you're doing forecasting and you want to use some kind of forecasting out there like profit is Facebook's. By using ChatGPT. You could say here's my data set. Give it details. You say, I want to use this algorithm, I'm using Python in Excel. And you could get the code to run a machine learning predictive algorithm based on your historic data. That would be really hard to do in just Excel. Here. Here's some examples of the. The samples from the tutorial of different things similar to the stock data types and it has different fields. You can do an array preview. So right here you'll notice I said, hey, give me an array preview of the data frame. I could also do a string and it shows this data as a string. There are some, some things they're not really very helpful. You can say, hey, what type of Python? Okay, the data frame comes from Pandas. What is it? That's the they did. So you Know here's where they're describing this data and it gives a hint here. Here it shows a scatter plot from the same data and it's very basic beginning of of Python. Here's just a few other examples and I'll share the video here in a minute. I pretty much spent maybe two out a little over an hour, maybe an hour and a half if that with this today and watched a couple videos to learn on the Python and and so many of the things you can do in Python you can just go through and shows some of the different things and tells you about them. This is a correlation matrix where it's showing the correlation between the length and the width the sepal length. This is an Iris Iris data set very common it's often used for K means it's a famous data set that a lot of data scientists will use to practice also do in Excel. But here's the, here's some data to data product quantity, price, sales right here. What I want to show is I've selected the data frame and I've typed the word describe and just by doing that control enter. It's going to run here. All right, wanting to so you could see the steeple length and the correlation. Well, is there a length, is there a correlation between the pedal length and the sepal length? Yes, there is. So you can do with one formula you could do a whole correlation matrix on your different variables. Again, that's not something you can click run a little slow. We'll give it a minute. It brings up information about the data, the count, the mean, the standard, the min, 25%, 50%, 75% and max. Yes, you could really and easily do with an Excel formula. Yes, there are add ins, yes, there are ways it can be done but I think what we're finding, what I found so far with Python in just a little bit of time write formulas for each one of those or you could use statistical analysis but that's really quick. Right. One formula it just spilled and gave me all that information about quantity. Ronnie the recordings will be available on on this site for a while. It's also out on YouTube so you could find it on my YouTube channel. Encourage you to subscribe there. So it is available but you can see there's also a very high correlation between the pedal witty price and sells. Next I came down here and said well I want it for just the product column. So it said hey, the product column has 26, there's six unique the top one the frequency and it it runs that analysis as you start getting more comfortable you can do things by hey, say I want to group my cells by date and it it's going to give me a summary by all the unique petal length and sum the cells. Yes, you could do that in Excel as well but it just shows what, you know, kind of capable here I had some fun right here. These are the main, there are a couple others you can do but these are some of the main graphs that are built in. And so what I did is I said hey, take my data, group it by month and give me the graphs. And so if I click here I can get an image and see what each of them look like. I can also export them as an Excel value. And so some of them I like are is you know, histogram nice to do box plot. You could also as you get more comfortable you could do things like a K means so Python, where it really is going to differentiate itself from Excel is if you want to do machine. Hey, I'm sorry about that. I know I missed a few of you. I got disconnected for a minute but I, I am back now. I think something. Let me just check a setting here. All right. For some reason I think it's my power source got disconnected for a second. Machine learning like. So let's say you're doing forecasting and you want to use some kind of forecasting out there like profit is Facebook's by using chat GPT. You could say here's my data set, give it details. You say I want to use this algorithm, I'm using Python in Excel and you could get the code to run a machine learning predictive algorithm based on your historic data. So if you're out there and you can hear me, let me know. But you could see correlation matrix. You know some other examples where this is a scatter matrix where it's using a certain type of chart, a pair plot, if you're familiar with that, where you can analyze the data and then this is a correlation. What you're gonna find is that would be really hard to do in just Excel. Here, here's some examples of the samples from the tutorial of different things they did. So here's where they're describing this data and it gives a hint. Here is there are a lot of benefits to learning the basics of Python. Do I think we all need here it shows a scatter plot from the same data and it just goes through and shows some of the different things and tells you about them. This is a correlation matrix where it's showing the correlation between the length and the width, the sepal length. This is an Iris Iris data set, very common. It's often used for K means. It's a famous data set that a lot of data scientists will use to practice on. So you can see the sepal length and the correlation. Well, is there a length, is there a correlation between the pedal length and the sepal length? Yes, there is. So you can do with one formula, you could do a whole correlation matrix on your different variables. Again, that's not something you can quickly and easily do with an Excel formula. Yes, there are add ins, yes, there are ways it can be done. But I think what we're finding, what I found so far with Python in just a little bit of time, Ronnie, the recordings will be available on, on this site for a while. It's also out on YouTube so you could find it on my YouTube channel. Encourage you to subscribe there. So it is available but you can see there's also a very high correlation between the pedal width and the pedal length. Sa hey, I'm sorry about that. I know I missed a few of you. I got disconnected for a minute, but I, I am back now. I think something. Let me just check a setting here. All right. For some reason I think it's my power source got disconnected for a second. So if you're out there and you can hear me, let me know. But you could see correlation matrix, you know, some other examples where this is a scatter matrix where it's using a certain type of chart, a pair plot, if you're familiar with that, where you can analyze the data and then this is a correlation. What you're going to find is there are a lot of benefits to learning the basics of Python. Do I think we all need to be heavy coders? No, I believe with Generative AI, an investment in some time we can learn the basics enough to be what I'll call dangerous. And let me reshare my screen. It shared the wrong one. Give me one second. Share my entire screen. All right, so that, that completes the new features what I wanted to show. Now I'm going to go back to PowerPoint and you're going to find in the PowerPoint, I provided a list of resources. These are some videos if you want to just start familiarizing yourself with Python. It should be in general release soon, it's nearing the end of beta and it should be available for use in the near future. All right, so that's that. And then the last thing I want to share for, for those that are interested, I Have two specials. I'm still running. I've done these before. I'm doing with the Excel hours. I have what's called my FPA Ultimate Course Bundle. It's about 10, 10 hours of video. It includes three modules on business partnering, financial modeling, design principles, driving value through smart analysis, the data analysis section, about three hours of content and then about five and a half hours on modern Excel, Excel tables, power query and dynamic arrays. That's on sale right now. If you use the Code Celebration, you can see the QR code there. It's 50% off. It's regular price, I think. So far I haven't found anyone who has complained about the value. So if you're interested in that, would love to have you. There's also just a modern Excel one for those who are interested that's also available at $60 for all three. That's 50% off right now, so $30. You can also the Excel tables one that is free for anyone. You can find that on my website. That module is available free. Anyone can register to take that course, but if you want to do the whole package it is, there will be a cost to that. So just sharing that so it's available. And that is what I had for today. Game over. As G said. So yes, we're pretty much done. I appreciate you guys joining me for today. Down at the bottom you can see the course bundle information. Also send out an email with this PowerPoint deck and the files from today for everybody who registered. And I'll hang on for a couple minutes in case there's any questions from anyone out there that they want to ask. I'm also open if you have suggestions on what you'd like to see for a future session. Feel free to put that in the chat as well. We got a couple minutes before the top of the hour, so I'll take any questions anyone has. I'm not seeing any questions. You're welcome to drop or you're welcome to hang on for a couple minutes. I thank each of you for attending. And again, I'll just be here for a couple minutes in case anyone has questions, specific questions they want me to answer. Yeah, I can go back to the Python reference. I'll also send this out. But Veronica, feel free if you want Snap picture everybody who registered for this. I'll have your email address when you registered for it. So I will send out an email of the PowerPoint deck either later tonight or tomorrow. Thanks, Rania. You want the previous slide? I believe this is the one you want. This is new Excel desktop features. So I'm pretty sure this is the one you want, Veronica. If I'm not on the right one, let me know. You're welcome. Exciting times for Excel. Also, for those who may use Google Sheets just. Well, you're still out there. If anyone's listening, I am doing a interview in the coming weeks on Financial Modelers Corner will come out with Dave, and he is an expert on both Excel and Google Sheets, and he talks about a lot of the new features in Google Sheets and when you should consider using Google Sheets over Excel. So if you're in, if you're a Google Sheets user, I highly encourage you to listen to that episode. I think you'll get a lot of really good information. All right, I'm going to hang on for one more minute and then I'm going to go ahead and close the event here. You're welcome, Benjamin. Ready? It will come out in the next few weeks. I don't have the exact release date, but if you look, if you keep your eyes open, Financial Modeler Corner, you can subscribe to it on any podcast platform. You'll get notified weekly it will be the one Google and Excel comes out later this month. Every Tuesday are when new episodes come out. All right, thank you, everyone. I'm going to go ahead and close the session, but I really appreciate you joining me today.