The Jack Benny program, presented by Lucky Strike.  My cigarettes with care, yes, I demand perfection, and luckies are so round and firm they're topped in my affections. Column full of news and I've a scoop for you, a lucky is a happy smoke so mild and so rich. Buy your cigarette, enjoy a truly fine tobacco that combines both perfect mildness and rich taste in one great cigarette, Lucky Strike. For only fine tobacco gives you both real mildness and rich taste, and LSMFT, Lucky Strike means fine tobacco. So friends, be happy, go lucky, try a carton of Lucky Strike.  Rochester, Tennessee, the Thoughts and Quartet, and yours truly, Donwells. Gentlemen, it is morning, and as we look into Jack Benny's home in Beverly Hills, he and Rochester are going over the bills that have accumulated during their absence in Europe. 850. Electric bill, $9.75. $9.75. Here's a bill from the telephone company, $6.40. Wait a minute, why do we have to pay the telephone company? They couldn't get in to open the coin box. I wonder how much my share will be this month. Now let's see, I paid my cash and writers for the first show. Oh yes, I have to mail a check for commission to my agent. I've been meaning to ask you about that boy, how does your agent get to the bank? He doesn't, the warden deposits it for him. Yeah, but he gets 10% off for good behavior. What else have you got there? Here's a bill from your dentist, he wants $100 deposit. My dentist? Oh yeah, send that bill to my sponsor after all it was his idea. Your sponsor?  Well, what's wrong with your five front teeth? He wants to put LSMFT on it. But I don't know whether I'll do it or not. He's smiling commercials. Be happy, go lucky.  I'll get it. Hello? Who was that? Your parents. He'll be good to see Polly again. What bills? I don't want to waste all day. Yes, sir. Here's one for your automobile insurance. $93.50. No, no, no, that's not the premium. That's what the car is insured for. That's right, I was up there for three days. See, my room was $10 a day. That's $30. Pay it, Rochester. What's the 20 cents for? I gambled a little. I was up all night trying to break even. You know, sometimes... I'll get it. Hello? No, no, the address here is 360 North Camden Drive. Not 350. Goodbye.  Some bird can't find the way to Capistrona. She can't even find her own house. Now, Rochester, take all these bills and... Come in. Hello, Dennis. What are you doing here? What are you doing here? Every time I come to your house, you ask me the same thing. What? For ten years, I've been coming to your house and it's always... Hello, Dennis. What are you doing here? Look here. Just once, I'd like you to say hello, Dennis. Glad to see you.  Dennis, why should I ask you to stand on your head? You know it's a long walk. My feet hurt. Well, that's ridiculous. Dennis, you only live two blocks from here. Why is it such a long walk? I always get lost. But there's nothing to it. Why didn't you just come down Rexford and walk up Sunset Boulevard? Oh, I'm afraid to pass Gloria Swanson's house. What?  Look, Dennis, do me a favor, will you? Yes. Come outside, I'll close the door and ring the bell again. Okay. Well, hello, Dennis.  Now leave me alone. Yes, sir. Now maybe I can... Not on the piano! Look, I didn't ask you over here, but if you came to let me hear your song, let's hear it and then go home. Okay. Hold it a minute. Yes? How do you do? I'm a telephone company. Oh, it's right over there on the wall. Thank you. When the Shriners were in town. I'll dump them out right here on the tape. Follows Nichols. Here I go to divide the dough and when I'm through I'll scrammy. One for me and one for you and five for Uncle Seth. Yes, mustn't forget him. My agent didn't look where he is. Now look, Mr. Would you mind counting those coins in the other room? No, no, not at all. Thank you. Go ahead, Dennis. Let's hear your song. Yes, sir. You can go home now if you want to. Dennis, I said you can go home now. Dennis. Oh, isn't that cute. He's sang himself to sleep. He must have walked a long way to be that tired. Hello, Jack. Hello, Mary.  I mean, come on in. Talking about. Nothing, nothing. Dennis, wake up. Huh? Oh, hello, Mary. Hello, Dennis. By the way, Jack, I haven't seen you since last Sunday. Did you read all the reviews on your opening program? Yes, most of them. I thought they were nice. The reporter in Variety said you were better than ever. I know. The Wella Parsons said you got loads of laughs. Yes, yes. Heta Hopper said you were dynamite. Yes, yes, I know. Erskine Johnson said you weren't the least bit funny. Him, I'm suing. What other write-ups were there? Did you read the review in the Herald Express? No. You can take that one to the Supreme Court. No kidding. Was it that bad? Oh, what? I thought you went home. How can I? My shirt's in your bending. Mary, getting back to those reviews, I can understand it. Everybody seemed to like the show. Even my mother.   She liked it? Yes, I got a letter from her yesterday. Oh. I brought it over. Do you want me to read it to you? Yes. I mean, if she liked my show, certainly go ahead. Okay. My darling daughter Mary, just a note to tell you, we heard Jack's opening program and thought it was very good. Wow. It's about time. We'll soon be able to see Jack, too, as we have a new television set. Hopper didn't want to pay all that money for a set, so he built his own. He went wrong, though, and when it was finished, the screen was one inch high and seven feet wide. It works all right, but Hop along Cassie looks like he's riding a snake. That's silly. A screen one inch high and seven feet wide. I wonder what Faye Emerson looks like. Read on, Mary. Here's some good news about your sister, Babe. About Babe? Oh, goodie. Goodie. Babe is very upset because she wasn't selected to go to the Atlantic Sitting Baby Beauty contest in Miss Plainfield, and I don't blame her. Even though I'm her mother, I must admit that Babe has the prettiest pair of knees in New Jersey. It's a shame they're in the back. Lucky her feet are on backwards. She'd look awful. Jack. Oh, I'm sorry, Mary. No other news except that I'm very angry at your father not speaking to him. What? Last month was our anniversary, and I told him I wanted to see South Pacific, so he took me to New York and shoved me on a banana boat. Good, good. Have to close now, but we'll write again soon. Your loving mother, Valley High Living. Well, Mary, if your mother lived here in Hollywood, I'd give her a job as a writer. I'm not kidding. Excuse me a minute, will you? Where are you going? I'm in the kitchen. I want to get a glass of water. Answer that, will you, Mary? Okay. Hello? Well, how you live? What are you doing at Treasure Island? I had nothing to do, so I dropped in at Jack's house. Social or Bendix? Social, Phil. Where is Jackson? He'll be right back. He's getting a drink. No.  There he is now. Oh, Jack. Jackson, it's a niffin of it, huh? Yes, Phil, I had a glass of water, nice, plain, cool water. Water? Yes, water. What's in your swimming pool? Remly, we're playing Sunset Boulevard. All right, all right. What did you call for? Oh, I want to find out about rehearsal. Oh, you do, eh? You want to find out about rehearsal? Well, Mr. Harris, for your information, rehearsal was at my house last night. Was I there? No. Well, I can cross that one off. I think we ought to get something straightened out right now. This is the start of a new season. When I call a rehearsal, I expect everybody to be there, and that includes you. Now, this is your last warning. Agent. My agent needs a tuxedo. Hang up, and I'll see you tomorrow. Goodbye, Phil. Good night, Irene. Hey, Mary, it's getting kind of late, and I'm hungry. Would you like to stay for dinner? Sure, Jack, I'd love to. Where's Dennis? Well, he went out while you were talking to Phil. Good, good. I'm going to get Rochester started with dinner. Okay, I'll just sit in here and play the piano. This thing is out of tune. No wonder nobody puts the nickels in it anymore. You'd think it, at least. Oh, Jack! Yes, is he expecting you? Yeah, Jack brought me a gift from Europe, and he wanted me to drop by and look at it. Just look at it? Well, he said he'd give it to me today if I promised not to expect anything. I must say it was exciting, Don. We had so much fun in London, Paris, Rome, Venice, and... Venice? Jack didn't tell me about that. Well, he wouldn't. Well, you laughing at Mary? Well, Jack will never tell you, so I will. Well, go ahead, Mary. I'd love to hear it. Well, after Jack finishes engagement at the London Palladium, we went to Paris. From Paris, we went to Rome, and while in Rome, we decided to go to Venice. All right, those canals must be fascinating. Oh, they are, Don. Anyway, we arrived at night. Jack's in the Grand Denali Hotel, and the next morning I met Jack in the lobby. Jack, did you get the tickets for the sightseeing tour? Yes, Mary, and the gondola will leave in a few minutes. See, I'm sure looking forward to it. Senior Benny? Yes. I am the belly captain. The gondola for the sightseeing tour, she's about to ready to leave. Oh, good. Well, we'll be right out. Grazie. Oh, bell captain, should I bring my coat? A senior in a living stunt. This is a sunny Italy. We have the same climate you have in the California. Bring me your coat. I thought so. Come on, Jack. First time I've ever been in a gondola. Yeah. I didn't know it helped so many people. I'm sure gladly came on the sightseeing tour. Oh, Jack, the guide is getting up to point out the places of interest. Yeah. Come on, Mary, let's get closer to him. There's so many interesting things in Venice. I don't want to miss a word he says. Excuse me. Excuse me. Jack. Excuse me. Jack, you're close enough to him. Just a little closer. Excuse me. Excuse me. Is it that, or not so distraught, the famous stories of the Palazzo, but this man is a stone in mine? What did he say? What did he say? What did he say? In the 20th century, a gondolier has never seen an animal like this. He still thinks he's a stone. What did he say? What did he say? What did he say? Yeah. Just a minute, Mary. Say, mister, do you understand Italian? Yes, I do. Oh, good. Good. What did he say? He said, you're standing on his foot. I'm sorry. I'll step back. Jack! Help me get him back into the boat. Or did you push him? Thanks, mister. Oh, boy. Am I wet? What did he say? What did he say? Huh? What did he say? What did he say? What did he say? What did he say? What did he say? What did he say? What did he say? What did he say? What did he say? What did he say? Huh? What did he say? He said, you're dripping on his leg. He thinks I'm going to step back again. He's crazy. In a son of Progando, Artista Cale is concertinalto, the Europa son of Vista. Wait a minute. I thought you couldn't speak Italian. What did Mr. Benny say? He said, he was a sensation at the Palladium Theatre in London. That he could say in Chinese. Poo, han, wang, poo. What did he say? What did he say? What did he say? He said, we are now approaching the Plaza, which is famous throughout the world, for it's singing gondolier. Oh, yes. Yes. Look. All those people sitting out on the pier. Where else would you see anything like this? Down our gondolas, starting to move again. Gosh, I wouldn't have missed this trip for anything. It's so picturesque here in Venice. Oh, Jack, look at those signs along the side of the canal. Signs? Yeah. I'll see if I can read them as we pass. What does it say? Burmese. On their last sign, Bermuda Radera. That's Burmese. Burmuda Radera means Burmese? Holy smoke. I better learn what these Italian words mean. Why? I had that on my strawberries this morning. See, I'll just have to... Jack, sit down, you rockin' a gondola, and we're getting into heavy traffic. Yeah. Just look at all those gondolas going down the pier. Well, that is a problem. Why didn't he try watercolors? This is gonna happen. Miss, are you sure you didn't push him?  See, I'm cold. I'm cold. I'm cold. I'm cold. I'm cold. I'm cold. I'm cold. I'm cold. I'm cold. I'm cold. I'm cold. I'm cold. I'm cold. I'm cold. I'm cold. I'm cold. I'm cold. You fell off the Queen Mary's. See, I'm cold? I think I... I... thank you. You said break a leg. I'm nice and Italian. Enjoy the ride like everybody else. OK, but gee, I'm so wet. Like your own car. Signore, signore, you know you're part of the famous aspartio for qualcastesa in Venezia. The guy just said we're passing the shopping center of Venice. And Mary, look at that straw on the end. It specializes in gondol accessories. Manny, Moe, and Luigi. The plate in Los Angeles must have stolen its name from this one. Oh, senor, senor, senor.  The guy just pointed out the famous American rendezvous in Venice called Harry's Bar. Oh, yes, I've heard of that. See, that's where all the Americans in Venice come for cocktails. We must go there, Jack. Yeah, and say, Mary, did I tell you the wonderful joke I made up about Phil Harris? I'm gonna do it on our first broadcast. Oh, look, Jack, you're on a vacation. Forget joke. No, no, Mary, this will be sensational. Now, get this. I'm gonna say this on the first broadcast. I'm gonna say that when we were in Venice, Phil Harris went into Harry's Bar and sat down at a table with one of the natives. Phil took a drink, and then the native took a drink. Get this. Then Phil took another drink, and the native took another drink. They kept drinking and drinking till the native couldn't see anymore. What's funny about that? Mary, don't you get it? Phil is the first guy in the world ever to drink a Venetian blind. You'll find luckies always give you perfect mildness. In fact, scientific tests prove lucky strike is milder than any other principal brand. But mildness is only part of the enjoyment luckies give you. You get rich taste, too. All the deep down enjoyment that comes from truly fine tobacco. Because LSMFT, lucky strike, means fine tobacco. So, friends, be happy. Go lucky. Try a carton of lucky strike. Wait, so good night, folks. This is CDS for Columbia Broadcasting.


and the MRIs, and she put to the best of her understanding everything she could from those into chat GPT and asked chat GPT for a diagnosis. Chat GPT came back with the idea that the kid had what's called tethered cord syndrome. She then went, she did some research about tethered cord syndrome. She found other parents with kids that had the syndrome. She found that the symptoms that their kids had was similar to the symptoms her child had. She then found a neurologist who specialized or had some expertise in this field. She took her child there. The doctor took one look at the MRI and confirmed chat GPT's diagnosis of tethered cord syndrome.


What's going on everybody welcome back to another video today. We're gonna talk about why data analysts hate using Excel Now some of you guys out there may be really confused right now because you love Excel and you kind of assumed everybody else loved Excel as well But you would be wrong because I think the people who really love Excel are the people who are just getting started in Excel And they just really love it because you can do so many things and it's really easy to use as a really nice UI I think those people are just people who haven't used Excel enough because when you use Excel enough You start finding a lot of things that are wrong with it And that brings us to the very first thing that I hate about Excel And that would be the data limitation and the performance issues that you have within Excel If you've used Excel long enough, you know that you can encounter a data set that is so big It's except every single row in the entire Excel spreadsheet and when you do this God forbid you try to actually filter on something and You could be waiting there for literally hours or it will just completely not respond and it will check out It'll be like you are never going to get this filter put on your data It is probably one of the most frustrating things because what happens is I exit out of the Excel I pull the Excel back up and then for whatever reason I try it again and again And it just keeps not working and I think that Excel is somehow gonna fix itself or get better But it doesn't and it just every single time frustrates me to no end So for smaller amounts of data Excel is really great But when you start working with a lot more data Excel just really cannot handle it. Well, it becomes extremely extremely frustrating The next thing that I hate about Excel is version control now I didn't really get into version control or really start using or understanding version control until about three or four years of being a data analyst But now that I've been using it for a while I honestly am really mad that Excel hasn't come up with a way to really handle version control well Yes, Excel does have this thing where you can kind of revert back to a previous thing But it doesn't always work and if you save it in a different place It doesn't always save that previous version control. So it's not a perfect system whatsoever Although it does have some version of version control There are times where I start digging into data and I start doing all these things and I save in a different place And I send it to somebody and I do all these things and then I realize I did a bunch of this stuff wrong I want the raw data And I just I completely forgot to save that raw data in a different file And I just overwrote all of that raw data It has happened way too many times and then I can't revert it back and it frustrates me to no end And so I guess what I am saying or nay pleading is that Microsoft fixes this And if anybody knows how to actually get better version control in Microsoft with another tool or anything Shoot me a message. I would love to hear it before we go any further I'm going to give a huge shout out to the sponsor of this video and that is Rapids by Nvidia Rapids is an ecosystem of GPU accelerated libraries made specifically for people like you and me There are even libraries made specifically for pandas within this cootief library There is something called the pandas accelerator mode, which is going to speed up your code 50 to 150 times It's original speed if just using pandas So if you're using pandas in your actual workflow or you're working with a large amount of data This is going to speed your processes up dramatically and Rapids is so easy to install You just come right over here select the method select what python version you are using Copy this command into your command line run it and you are set to go So if you want to install their cootief library I will leave links in the description and they even have this github repository Which explains everything that you could possibly want to know about it again Huge shout to Rapids by Nvidia for sponsoring this video The next thing that I personally hate about excel is having to use it to work with other team members In other departments or just anybody in general It is great when I can just use it on my computer and save it as weird names as I normally do But then when I try to start working with other team members or other people It does not work well. This isn't google sheets This isn't something that is online that I can actually type something and they'll see it or they'll You know be able to know what I'm doing. I'm doing my own work over here They're doing their own work over here and then when they send it to me I then have to say oh geez they did something else I have to completely change my file to then merge it with their file And it honestly has taken years off of my life the amount of stress and frustration that that alone has caused me At this point I might as well fax a physical copy of the spreadsheet over to them have them mark it up and then fax it back That's essentially what we're working with with excel when talking about collaborating with others The next thing that I hate about excel and this is something that I kind of learned to hate over time Is the automation piece of excel now with vba and macros you can automate things But I've become accustomed to a certain level of automation with python and other programming languages Where I want to actually automate just about anything I could ever want But with vba macros you can only do so much and so when I'm working within excel I'm doing most of these things manually I'm clicking and dragging and dropping and I can't automate every single thing like I could in a different program language Or another tool and honestly I try to automate as many things I possibly can so I've tried to automate a ton of things within excel I just haven't been super successful in it if I'm being honest the very last thing I'm going to mention that I hate about excel and honestly this list is probably a little bit longer Is that the data visualization is definitely lacking within excel? There really aren't some good basic charts and graphs that you can use within excel to get basic visualizations But if you try to go beyond the basics, they're going to recommend that you use some 3d stacked pie chart Which makes absolutely no sense for what you're actually doing So what ends up happening is I have to go to some other tool that has better data visualization And then in the end they want it in an excel file And so what do I have to do sometimes I have to print it out or sometimes I have to integrate it into excel That's just a lot of extra work that I don't want to have to do So microsoft if you are watching I'd be more than happy to come and help you with the data visualization side of excel free of charge Well, maybe a small charge now with all that being said excel is still a really great tool There are just some things that just really get under my skin when using excel and I've been using it for many many years But excel is a fantastic tool and you still need to know it for data analysis And I think as you get further along that's why people start really not liking excel is they start using it at the beginning It's great But then they find all these different use cases why it doesn't work And everybody else in the business world everyone else that they're working with wants everything in excel And so since not everything is super native to excel you have to figure out little workarounds and little ways to get it into excel Which gets super tiring and really frustrating So excel is kind of that one thing that does really well in a lot of areas Just as an excel in every single area And so you have all these specialty tools and all these different plugins that you have to do Outside of excel and then bring it back into excel And that's I think the part that makes people the most frustrated. So thank you for listening to this venting session I just needed to get it out there I think it was kind of therapeutic for me to just talk about it And hopefully some of you guys will agree with me in the comments because it would make me feel better So thank you guys so much for watching if you like this video be sure to like and subscribe I'll see you in the next video


I liked about that. So my next guest is Michael McInerney from the BCS. From BCS. BCS, okay, welcome to theCUBE. Business Critical Systems. Okay, I'm John Furrier with SiliconANGLE.com. We're here in Las Vegas, Nevada. HP Discover 2011 where we're on the ground with theCUBE, our flagship telecast. We talk to the smartest guys around. Executives, thought leaders, bloggers, anyone who wants to share their knowledge with us. We're going to have a conversation and go deep, expand those ideas. So Michael, welcome to theCUBE. So one, give me an update on what's going on. We've had some of your folks in talking about some of the changes in the products. We had Intel on, talking about the chip. Okay. Give us a quick update from your perspective on what's going on in your world today. Sure, no. So I'm responsible for building, essentially the mission critical products at HP. So all of the servers, integrity-based, and also some of the large-scale x86 servers. So Ben, as you've been mentioning and talking about, you know, a lot of the effort has been, excuse me, has been around driving the converged infrastructure, driving the mission critical systems in the converged infrastructure. So we've been investing a lot of time into that, so you'll see we have a common architecture from x86 all the way up through our sort of flagship Superdome, all built out on a common blade architecture. So our customers have a very seamless experience as they're deploying out their architectures, not get rid of the sort of islands of isolation in their data center. So a lot of people don't know this, but I actually worked at HP for nine years, from 1988 to 1997, and HP was an eight billion dollar company when I joined in the late 80s, and you know, there are hundreds and hundreds of billions of dollars, 26 billion roughly revenue. Give or take a few tens of billions here and there. So they're known for high performance computing. It's not a new DNA for HP. No, absolutely not, right? So we're out there running billions of credit cards, hundreds of millions of dollars of transactions on these mission critical systems, stuff that you'd never see, but you know, how many of you used your cell phone today, likely that you were actually touching one of our integrity systems or one of our high end, high availability systems. So we continue to see that out. We see some interesting things happening out in some of the emerging economies where they're out trying to deploy this infrastructure that here in the US were sort of, we expect, like we have credit cards, we have banking infrastructure, we have customers coming to us and saying, you know, I need to go out and deploy 7,000 new banks over the next two years. You know, how do I do that? And we say, ah, we have an idea, all right? And so, you know, we have that sort of trusted mission critical architectures out there that we deliver in the marketplace. Yeah, obviously the press, I mean, mostly in the blog's blog side, in which we do have a blog, but technically we're bloggers, we consider press, but even on the mainstream press, they love to talk about the death of something, right? The death of, you know, the death of the mainframe, death of the mini computer, death of the land, death of client server.  If they invest in cloud, their business is growing, there's great investment, so the world really never changes. It's kind of the same pattern and movie all the time. So we still have a need, even though there might be federated clouds and, you know, distributed network out there, it's still the same distributed network. Computing and high performance computing still is a big part of that. So just for the folks out there that aren't on top of the whole, you know, high end, I don't want to say mainframe class, as a kind of mainframe is kind of old, but there is that high performance, it's kind of shrunk a little bit in size, but horsepower wise, there's still that massive nodes out there of high performance, and that's not going to change. So just share the folks, with the folks out there, that dynamic. Yeah, I think there's two things that go on there, right? As a lot of it is, there's some very hardened infrastructure that's out there that's deployed, right?  So, well, that'd be a big problem, right? Collecting money is an important part of business. So a lot of these applications and these infrastructures have been hardened over time, and people just are not going to replace those. The risk reward of going in there and saying, I'm going to change my billing application out because I think it'll be fun, isn't happening in the environment. So you continue to see that, and we continue to see customers looking at, you know, where is it that, you know, I have my cloud-based architectures, I have my sort of more general-purpose computing platforms, but there's some places in my enterprise that I still need better than general-purpose, right? I still need that, I need higher levels of reliability. What's changing though, I mean, so we still have the need for high performance. So a lot of people in the cloud side say, hey, there's an abundance of compute. So we've done a lot about the storage, talked about three bar a year ago. Storage has always been, is now sexy in the middle of the conversation as a subsystem, but there's been a conversation that people have been saying, oh, we have an abundance of compute, and we just, the old grid argument, I don't remember those grid days, but you know, I mean, is that true, is it false, is it kind of true? Can I just talk about these issues? No, it's a great, I mean, it's a great question, right? So I think the idea here is, you know, what is performance? Right, so when we start talking about mission-critical environments, what does performance mean to you? Is performance, so I'm a hardware guy, right, and so I want to talk about processors and cores and frequencies, but when you go out there and look in the mission-critical environments, performance to those customers is not necessarily how many cores do I have, it's what's the response time on my application? How often do I need to tear down my application a year to upgrade things? How do I, how many unplanned failures do I have in my architecture? And this is where minutes matter, right? If my billing application for texting goes down for a half hour, how much money does a large telco lose? It's real dollars, that's a real dollar. Real dollars.  Absolutely, I think that cloud and big data are just great examples of sort of an implementation, right? So I can go out and say, can I do these things on the cloud, right? Well, a lot of times for the mission-critical pieces, these will be the last pieces you'll see sort of go out to the cloud, not because of the technology, but more because of the sensitivity of the information, right, if it's in healthcare. This is actually my, you know, my provider data or my customer data, I just can't share that. Financial services, telecommunications, this is my core data, this is my company. You know, I can do some of these things on the cloud, but these other things I'm going to keep in. So you'll start seeing us talk about hybrid clouds and building clouds that are internal and external. That'll definitely happen in this marketplace. And then the question just becomes is, do you have those mission-critical clouds, right? Do you have the high availability? Do you have the scalability that you need within those cloud architectures? And that'll be the interesting thing I think you'll see develop out there. We're here with Michael McNerney with HP, runs the group Hardware for the Big Super Dome. I mean, this is the high-end performance, computing the devices, talking about all the things and why it's relevant to have all those high-performance dedicated machines from HP.   So, you know, when you design a system, a motherboard or whatnot, there's a lot of engineering involved. And you know, it's packaged up into a hardware machine. But now, we've been talking about the systems view and Dave Donatelli and I were chatting about that, yes, on Monday night around the cloud, in a way, as an operating system, or its own system. It might not be encased in a machine, but there's system elements involved. So, can you share with us the dynamics or kind of high-level philosophy around architecture around how your machines, your hardware, as a component of a new meta, higher-level system? Sure. It certainly has been true, and I think definitely, where do you define that layer of abstraction? Where do you define that layer of systems-ness? When we look at the mission-critical systems, this is what we're talking about, right? It's like, how do you build reliability in not just at the CPU level? So, my favorite story here is with the integrity systems, we have un, what are they called? Unconsumed and consumed errors. So, there's consumed errors in the processor. This means that a processor has a fault. But it doesn't mean that the system fails because the rest of the system is able to sort of solve that. So, actually the processor has failed, but the system hasn't failed. It's been able to back it out. It's been able to sort of either identify the application that that processor or that memory fault was associated with, and kill just that process or something like that. So, you see that sort of systems-level things are built in, and this is really where we drive things. So, if you look at like virtualization capabilities, having those tightly integrated into management so that then we can provision new servers, do capacity on demand. You know, I want to fail over a server. I want to move a bunch of workloads on it. I want to dynamically add capacity to that new server. I don't want to just have that sitting there. You know, how do you tie all these things together? How do you build out that system? That's really the key of what we work on. Talk about virtualization from your perspective. Obviously, virtualization's been the heart of a lot of the conversations. Paul Maritz, who's speaking, I saw on Twitter, actually, I think he's speaking here, talked at VMworld last year. We had theCUBE there. He said, first time in history, virtual machines, server shipments, surpassed the physical machines. Sure. That scares people, but it's a good technology advancement. Has virtualization helped your business on your end, or is it just you deal with it? So, two answers, really, and this is maybe one is sort of just showing my age is, you know, Unix systems have been virtualizing workloads since the beginning of time, right? We used to call this time sharing, and now we moved into, so virtualization is definitely sort of alive and well in the mission critical environment. A lot of things we do here is, we will do things like electrically isolated partitions. So what this means is I've virtualized the system, I've sliced it up, and nothing that happens into the system down to, you know, you putting a bullet through it, is gonna impact the blade sitting next to it, right? It's completely electrically isolated. So when we start talking about mission critical virtualization, you start talking about this higher level. How do we do things in a hardware level to guarantee complete isolation? How do we partition workloads versus sort of virtualizing with a hypervisor, you know, that a lot of people can't take the performance hits on, I've virtualized IO, now all of a sudden there's this intermediary in my IO causing delays, I need raw performance on my IO. I think most people, I would say to the folks out there, it helps your business because it puts an emphasis on some of those mission critical virtualization. I guess what I would say is, you guys are in essence in the mission critical business. Yes, absolutely. Whether it's virtualization or... Yeah, and so there's this sort of notion of a hardened virtualization. What does it mean in a mission critical environment? And I've had customers sort of have that conversation with me where it's like, you know, what do you think of virtualization and a little bit of a broken English conversation and they're sort of like, no, no, no, we want the UNIX partitioning, we want these electrically isolated partitions, not just virtualization with the operating environment. You know, I've been watching, obviously, working at HP going back to the day, actually met Bill and Dave when they were still alive in the late 80s when I joined the company when they first would welcome guests. HP's story, history around HP UX and the servers, when even the old mini-computer days, it's legendary, we all know that. But what's interesting that people might not know about is that HP is really the only mini-computer company to survive, you know, deck, you know, kind of she rolled into compact, which ended up ending up into HP, data general went to EMC and so, you guys have transformed and reinvented yourself. That was helped with the commodity server side of the business within, et cetera. So you guys have successfully always innovated on that. And when we talked to Intel, we asked them a question about their innovation challenges when a year or two years ago, and Cloud was an early investment for them. So the question, and it's been paying off for Intel. So my question for you is around investments. How are you, what are you guys investing in now that you see paying dividends down the road on the roadmap? So I think, you know, we continue to invest in, you know, it's not super exciting, right? It's continue to invest in availability, continue to invest in scalability, so. The boring stuff that keeps the lights on and keeps the lights on. Keep the lights on. And yeah, and so people, yeah. We sit around in marketing meetings for a long time and come up with what's our value proposition and it comes back to RAZ like every time. And sometimes we, you know, we change the letters around and try to create some new acronym. But ideally it really is the scalability to system. So today, in this show, we're announcing we're gonna scale Superdome to 32 socket. So we're gonna take 16 sockets, essentially two chassis, wire them together, turn it into a 32 socket system. You know, sort of really sort of upping that level of scalability. You'll see us continue to drive that with Pulse and we'll go up to like 256 cores on that system. You know, single image system or, as you mentioned, a lot of people partition that up into different workloads to drive that. So we'll see a lot of the scalability, a lot of the availability and then just keeping all of the virtualization capabilities and other pieces sort of built out. So what's the price tag for a 250 core machine, just ballpark or something? You know, I don't know the number off the top of my head. It's not cheap. I mean, it's not 5,000. It's not 20,000.  It is, absolutely. What solar system is it in? I think the, I think it's hundreds of thousands of dollars. Absolutely. And I think when you look at those costs, right, what's really interesting about that is what is that compared to your total solution cost? So if you're talking about deploying a large scale SAP environment with, you know, help from outside, essentially services, consulting, you look at the software costs, you look at all these things, the actual hardware cost is fairly minimal in that equation. So a lot of times I think one of the conversations I have with people is, you know, how much does it cost for a Superdome? Well, how much does it cost you not to have a Superdome, right? So what does it mean when your APOs, SAP APOs goes down? It's a big purchase because of the mission critical. I suppose it's going to get a feel for the, for the device component and see the services wrapped around it. And I think you also have to look at what is the cost of building that equivalent architecture, right? So you sit there and say, I have Superdome. It means I have this cluster of servers built into this fabric. Can I do that with an x86 environment? Can I take x86 boxes, put them together, with let's say Infiniband, cluster them, do all of these things and put that whole package together. You know, what does that cost me? What does that cost me to actually operate and run? And I will tell you, we have those conversations with customers who are saying, I'm going to go build this out in a x86 architecture. And we say, okay, what is your sort of core value? Where do you want to invest as a company? Do you want to be a server vendor? Do you want to be a bank, right? And so Superdome can come in and build you a turnkey mission critical environment. And when you start looking at those costs, you start looking at the TCOs, you know, that will still come out on the positive side. And you're dealing with a very sophisticated, very savvy audience because you've been selling to these environments. It's just your standard big investment houses and they're big companies, multinational companies, right? It's not like, it's not SMB as everyone would think, hundreds of thousands of dollars. If they want to buy a Superdome, we're glad to sell it to them. Law firm, buy Superdome, you know? I guess my final question would be around where the action is right now. I'll see cloud big data, all that trends going on here. Where's the action for you guys in the marketplace and use cases in particular? Because it's a high-end machine, it fits into the architecture. You got the conversion networking group with all the Lego blocks from entry level all the way scaling up to the low end. We just had Jeff Miller on from, or Paul Miller on from the ESSN group talking about the Lego blocks and appliances. What's the use case that's sexy right now or hot for you?  Adding all this extra data, having the ability to analyze and drive all of these data. In most enterprises, everything sort of always comes back to a couple of core systems, right? So you still can do a lot of analysis, you can still have a lot of opportunity, but it's that core that you have to make sure is going to scale to meet this demand. That core has to be flexible. So how do I take my core data? How do I take my core business applications? That it's great to have these new capabilities like big data and being able to do analysis where you never could before, but a lot of times you're still going to be pinging on those core systems or still dependent on those core systems. And so as an IT manager, how do you make sure those aren't going to become the bottleneck, right? How am I going to make sure that core is going to scale when I need it to, expand when I need it to, to meet all of these tremendous opportunities out there? So basically what you're saying is, no matter what people talk about, the game is still the same. Whatever architectures they roll to, cloud, big data, core systems are at the heart of any infrastructure. I just think it's a, you want to make sure, for our customers, a lot of them are focused on how do I make sure my core data doesn't become the bottleneck, right? I can go out and do all these things with big data and make all these things happen, but I still have to be able to get to customer, these five facts about my customer in sub millisecond time. Okay, how do I do that? And that's where they build out these mission critical architecture for. Final question, I'll let you go. For Superdome and the super monster machines that you have there, horsepower integrated in, what's the future for you guys? What can people expect from Superdome and some of the new advances you guys are coming out? Sure, no, it's a great question. So again, boring is hack, right? We're going to get bigger, we're going to get faster, we're going to get more reliable. Betcha you talked to. Yeah, exactly. And you know, this is what we do, is we'll eat for lunch, you know, breakfast, dinner, and that's what we're going to see from us is just continuing to drive that envelope. We think the mission critical requirements of today are going to pale to what we need to do to deliver that for 2020. So how do we keep building and driving that new limit? Okay, okay, Michael McInerney, thanks for coming inside the Cube, Superdome BCS, which stands for? Business Critical Systems. There you go. Okay, thank you so much for coming on the Cube. Thank you so much. Thank you.


So far we have been talking about this situation where the client is either a child or an adult or a teenager but it's an alive client. Now we have to talk about confidentiality issues even when a person is being died. So it's a mental health professional's duty to maintain the confidentiality of a client even after his or her death. It's not a simple material that if you say that an individual is not in this world then its information can be easily provided to others. Often mental health professionals will encounter circumstances in which their solution must rely on ethical principles as well as legal standards. So even to protect and safeguard the secrets of dead people is an ethical and legal and moral duty of a therapist. Consider the following actual case. Now this is a case which is being happened in real that after the death of the client the therapist made unsolicited disclosure regarding the deceased former client. Now he probably didn't have any idea about this rule and the therapist has released some confidential information about the client who had passed through the world. Commenting in public that the client has allegedly reported experiencing abuse at the hand of some person. A court subsequently barred the therapist from seeing the patient for 90 days and placed her on three years probation. Now he was accused of seeing the patient for 90 days because he had released a statement about the abuse of the patient and he reached the client's confidentiality. Courts announced a decision commenting. Now what were the actual words of the court? Therapy is based on privacy and secrecy and the breach of confidentiality destroys the therapeutic relationship. So because that very therapist has destroyed the therapeutic relationship even being the client is dead he is being punished for that. The key to resolving such issues with involving remembering that clients to do some rites of confidentiality even after their death. So this is very important to remember that confidentiality just by dislocating an individual's individuality and ending their therapy even after their therapy is over even after they leave this world their rite remains sustained. These rites guard them from defamation and other issues and also give due consideration of the welfare of the survivors. Sometimes the disease that we are protecting confidentiality is basically giving protection to its family members. If we open those things sometimes it can be a threat for its family members. So a therapist needs to make a reasonable assessment of when and where it is appropriate to maintain the confidentiality because confidentiality is a ethical point of view to which the treatment has been given and it's the key to the success of the treatment.


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Hello everyone this is Amit Dan of Amitdan.com you're watching one of my New Zealand travel videos and today I'm taking to the Pernel Village, an upstill server in Auckland. Pernel is Auckland's oldest and one of the New Zealand's most affluent neighborhoods. It has lots of specialty and antique shops, pubs, cafes and restaurants. Auckland is the largest Polynesian city in the world and one of the world's most livable cities. The most multicultural city in the world has 180 plus different ethnic groups. A third of New Zealand's population live in Auckland with a 1.5 million population 39% born outside New Zealand. Thank you for watching this video. Forget about subscribing to this channel. Forget about liking this video. There will be more videos coming up so I'll see you shortly.


Hello there everyone and welcome. This is Melissa Arma with a stock swash and a review in Amazon. I can't put some of this today and actually you still could be in a put that I called last week on this but this was one of the charts that I looked at after we had, after we had this sell off. It was at new highs, gap down fell, gap down here fell rally, gap down in here, gap up here, gap up here, gap up here, today it gap up but I ended up, you know, saying wait a minute here and now this is obviously selling off here a little bit tonight. Well it was earlier, now this is not really, this is pretty flat. Look like it was down earlier now, looks like it's flat. Anyways, this was a trade that if you did this trade today when I called it you could have actually made more than 100% in one trade in one day in this option. It more than doubled from the cost of it which means you would have had more than 100% return and investment. This does not happen on every single option trade that I call where you can take it the same day, get out of it the same day with that kind of ROI but it does happen. And when you look at the size of the bar here actually I was looking for this to break $3,100 and it sort of did. Like it did a little bit but not really. Like I was looking for this to break it and this was just a beautiful sell-off here. Now it could have broken it today and if it had it would have gone down and broken it Friday's low which really wasn't that far away when you think about it. So this was $30.83 and we got down to $30.96. So 13 more points and this would have been poof done but nice trade today if you got it in and out of it you could still be in it. You could still be in it. Probably to expire on the 18th. But again it's nice also to take a trade book that profits quickly and what a nice move. And really when you look at the size of the bar today I mean to have it was just the price and the catching it at the right time and just just seeing it and just went. So sometimes this will happen if you're on the options newsletter you know you'll be able to get these trades. So it's been a good year 2020 getting ready for any season in a couple of weeks can't wait. If you're interested in the gap options newsletter at $69.99 a year you get all the newsletters emailed to you for one year and if you'd like to sign up email me at Melissa at the stockswush.com have a great day everyone.


So here we are in our first video. We're going to look at Google Colab, the place that we're going to do all our analysis in. Now it's part of Google Drive. So if you've got a Google account, fantastic. If you haven't got one sign up, it's all free of charge. You don't have to install anything. You don't have to do anything. I'm thinking most of you have seen a Google Doc before and it's as easy as using a Google Doc.  I'll see you there. Google Drive Most of us are familiar with Google Drive. So I'm using my Chrome browser here, and I've logged into my Google Drive.  You can start a new Google Doc, a new sheet, a new slide. But if you go down to more, I see here Google Colab. I'm going to say Colab because there are various pronunciations for this full name. We'll just refer to this Google Colab. Now Google Colab is a Python development environment using or at least based on Jupyter Notebooks. I'm going to show you exactly what a notebook is. A notebook is going to allow us to write normal English sentences, write our code, do our analysis, create our plots and graphs. A wonderful environment. You don't have to install anything at all. So let me show you my first notebook. At the top here, you can see I'm in my Drive. That's where you're going to be when you start your Google Drive. Coursera is a folder I created. So it was just new folder. Inside of that, another new folder, Understanding Clinical Research. And inside of that, I've got week one data. And these are the files that are already in there. And you can see they're all Google Colab files. But let's open this first one, which is here. If I right click on it, I can say Open With. And Google is going to recognize that this is a Colab file. So it's going to open that Colab file for me. And here we go. A Google Colab Notebook.  I can give it a name. And I've given it a name 01, our first Colab Notebook. And you see the file extension there? All computer files have a file extension. It's .ipynb. That's done automatically by Google. Nothing for us to worry about. And just I'm just scrolling up and down this document. Have a look at it. I can make comments on the top just as you would do for Google Doc. On the left hand side, I have a table of contents. And as I start creating this document, it's going to create this table of contents for me. I don't have to worry about that at all. There's also some other stuff up here that we'll get to later. But on the right hand side, or the main part of the screen, we just see my document. Right at the top, there seems to be a title. And if I click on this little triangle, I can just open and close this little section. And I come to a next little section that I can open and close. And let's double click on this. And you see it's actually just this cell. We call this whole thing here cell. And I can write normal English sentence there.  You can decide how large you want the title to be. And what we do under these circumstances, if we want to know, if we want to tell Colab how big we want the sticks to be, we just use a number of pound symbols, or I think we'll call them hashtags these days. So one hashtag means the largest possible text you can. We usually use those for titles. And if I go to two hashtags, it'll mean it's slightly smaller. You can see a jump to something smaller. Three hashtags, it's even smaller.  So I've just written the word clinical research there. I can do bold, italics. I can insert a picture here, all sorts of things, bullet points, numbered bullet points.  And if I'm inside the cell and I hold down shift and I hit enter or return on a Mac, it's going to execute the cell. And it's just displaying to me to the screen exactly what I wanted. I wanted the title, the largest possible size, and I wanted to say clinical research as simple as that. Now I've put some of these little files here that display for me the logo there, another logo, another logo to remind you this is brought to you by my research group at the University of Cape Town and really in support of my course on course zero on understanding clinical research. We're going to use Python and we're going to do some coding analysis. We're going to follow the same chapters as we do in the course. But really, if you haven't done the course zero course on understanding clinical research, explaining to you what a P value is, what confidence intervals are, etc., you don't have to. You can just follow along here on YouTube and we can look at how to use Python to do some clinical data analysis, some biostatistics, if you want to call it that. Now to do these logos, I'm just going to double click on the cell quickly and you're going to see the code that I've written for this. It looks a bit difficult, but it really isn't. It's copy and paste and we're going to get to how exactly to do that. If you look closer, though, you see these little tags here, a diff tag and image tag. This is just HTML. HTML is the language that is used to create web pages. So I can even just write normal HTML. Again, don't worry about this. This is really, I didn't type all of this. This is copy and paste stuff and I'll show you where to copy and paste it and how to copy and paste it.  The next cell we have, and by the way, look at the right hand side. When I'm on a cell, I get some things to do. I can move the cell one cell up if I want to rearrange the cells and I can link to the cell from other places. That's a bit advanced. I can add a comment to this. If I'm sharing this document with someone else, I can edit the cell and that's exactly what we want to do. I can also just double click on it. Remember when we were up here, I double clicked on the cell and to execute that cell is to shift and enter, shift and return. So I'm inside of the cell. Let's click on it. Let's try to edit it. By the way, there's also deleting it. And look what I've written here. Load Colab to your Google Drive. And it's just a sentence that I've written and I've put a URL there, a link, and I can just write it. HTTPS, slash, whatever you want, and it's just going to appear as a hyperlink automatically. And there you go. And the reason why I put it there is you're going to start using Colab.  To have that just appear for you as if by magic, go to this website, colab.research.google.com. So that's what I've put in there, colab.research.google.com. If you go there, this little page is going to open for you. You can check out any of these Google notebooks, but you can also click off of it. And it's going to tell you all sorts of things about Colab that you can read on your own, see those beautiful plots there. We're going to make ones that look even better and that are interactive and some hyperlinks there, et cetera. So this is Google telling you what Colab's all about. But what I want you to do is click right there, copy to Drive. And that's going to copy this notebook, Google's notebook, onto your Google Drive. And once it's on your Google Drive, Google Colab's also on your Drive. So if you don't see Google Colab under New, More and Google Colab, go to this website, colab.research.google.com and just copy this to your Drive. And now suddenly Colab would be available to you. But let's get on with our notebook here. There's another title. So how did I just add these? You might wonder, well, it's beautiful to see all of these, but how do you add this? Well, there's two ways. If I hover in between two cells, look at that, it says I can add a new cell, see the plus there, in which I can write code or I can click on this one if I want to add a new cell into which I want to add text or these logos or pictures or whatever, I'll click on text. And wherever I am, I can also come up here, click on plus code there or plus text there, depending on what I want to add. So best place is just to hover between two cells right in the middle here and just decide what you want to add. Remember, you can always rearrange things later. I can move it down, I can move it up. Anyway, remember how to do this, single hashtag, space, title, hold down shift, hit enter. And there it is, beautiful subheading. I wrote the word subheading there, but I put two hashtags and you can clearly see the difference in the size of the text. So do whatever you like. This is an artistic board, almost design your documents, whichever way you want. What I did here though, is to add a code cell. So in this cell, we're going to write some actual code. Now don't worry about the code at all. I'm going to show you how to do all of this. Let's just look at these two lines of code. Now you're going to see a little hashtag there as well. Inside of a code cell, that hashtag has a completely different meaning. It's actually Python code. And it is Python code for please ignore this whole line of code. So it tells the Python interpreter, that's the inside of Python, which is just going to execute your code. It says ignore this line please. So why is it there? Well, it is there because it's always good practice to make comments on your own code. You're going to view your code months from now. And you won't remember what you're trying to achieve in that cell. Or you might share your document with others. And you want to let them know what your idea was behind this code. So leave comments for yourself and for others. And you prepend a comment by a hashtag, that hashtag space and then write. So it's only on that line. Once you hit enter, return to go into a new line, you can't just keep on typing. All of that has to be on one line. And Python is just going to ignore that line. And the next line of code, I've used the print function.  It's one of a keyword. It's a keyword inside of Python. And Python has many keywords like all other computer languages. And those are reserved words. And they actually execute something. They do something. You give it something and some input and it outputs something. And we're going to look at many, many functions. This is the print function. And it's just going to print stuff to the screen. And what I give to it, the input that I give to functions, we call arguments. And arguments go inside of these set of parentheses. So all functions in Python three and above, especially the print function, they have these parentheses. And you pass some input called an argument to the function. And it's going to output something. The print function outputs something to the screen. And you can already see, I've already run this line of code. It's just going to execute that. What you also see is a little arrow, a little run button here on the left hand side. So instead of holding shift and enter, I can also click on that button. And that's going to run that cell. Look what's happened at the top here quickly though. It says connecting. And that means we are connecting to the servers at Google. And they're going to spin up for us an instance of Python so that we can run Python. Now, depending on where you are connecting from, how busy the network is, et cetera, it might take a little bit of time. But there we go. We can see how much RAM is available to us and how much we're using and how much disk space Google is giving us, all free of charge, by the way, and how much we're using at the moment. And now it's connected and this line of code is executed. And you can see it prints there. This is a line of code, exactly as I typed here. We're going to learn in the next section just some simple arithmetic. So there's my line of comment. Simple arithmetic. And I wrote two space plus space two. You don't have to put those spaces, but it just looks nice if there are spaces. And if I hold down shift and enter, shift return, or I hit that little play button, it's going to execute that two plus two is four as simple as that. So this is right there own line of code. Four minus two, shift enter. Four minus two is two. And behold, it's two. It looks like it takes a long time, but it really doesn't. We can do much bigger stuff and it'll take exactly the same time. This is sending it to Google and it has to send it back to you. That's the delay, the actual calculation is very, very quick. So I've got some exercises for you. Remember, how did we do this? If I double click on it, it's just one, two, three hashtags. That means it's level heading three, three in HTML parlance. So it's a bit smaller. And I want you to do the following. Now, before you do it, let's just double click on here and see how that was created. I just typed one dot space, my line of code next line two dot space. And if I had shift enter, and well, it's just a numbered list there. Just as easy as that to create a numbered list. I want you to then create a title named arithmetic, create a subtitle named multiplication, write a line of code, following an appropriate comment always to multiply three and four, and then write a line of code following an appropriate comment to print this is easy to the screen, and write the same sentence as in four, but put it in a text cell.  Okay, I hope you've done all of that. It wasn't too difficult. Of course, if you have any problems, you can leave some comments down below. I'll answer those for you, even if it means making another video, perhaps someone else in the community can help you as well. But that's the solution file I've already created it. So I'm going to right click on it, open with Google Collab. Let's look at the solution to those exercise questions. So it's going to load a page, you'll see the connect there at the top, you can also click on connect. So before you start executing code, that first line of code that's already connected, and so really spun up. But you can see arithmetic there as a h1 header or title multiplication looks slightly smaller on the screen. So there was two hashtags, we've done our multiplication, we've printed something to the screen, and we've used a code cell to do that. What I'm going to do for you here is just redo all of this at the bottom here. So right at the top, if this was now blank page for you, you could just start at the top, and I'm going to start down here and just recreate all of those. So that first code cell that I want is actually not a code cell, but a text cell. So I'm going to hit on text, I can click in there and just start typing. By the way, I can also repeatedly click on this, the toggle heading 12345123, it goes to, but you can type up to six if you wanted to. So let's just do it ourselves. I'm going to use one hashtag and I'm going to write arithmetic. And I'm going to hold shift and hit enter. This is a PC, but you can hit shift and return on your Mac. And there we go. You can see it automatically made a new cell for us, and it is always going to be a code cell. So no matter, we want another text cell. So we're just going to hover there and put a text cell in there. Remember this time we want two hashtags. We want a slightly smaller multiplication, shift enter, shift return, it's there. Now, as I said, the next line, it's going to add a new cell for you. And it's automatically going to be code. So we can just start writing it. We're going to leave a comment for ourselves. So hashtag again, multiply three and four, enter. Nothing's going to happen when you do enter. It's just a new line of code. I'm going to say three times four. Now, we all know on a keyboard, there's no such thing as a multiplication symbol. So in most computer languages, that is shift star. So that's shift eight on my keyboard. So three times four. And shift enter or hit that little run button and three times four indeed is 12. The next was also a line of code. And we wanted to print something to the screen. And I'm going to say printing, printing a, let's correct that printing a string to the screen. The print function as always. And remember what I said, we have to put the argument, the input inside of parentheses directly after the print function. But you can see a little, a little tool tip appeared for me there. It said, well, we recognize what you're trying to do here. So if I click on that, it knows what we're talking about. If I hold down shift and the open my first parentheses, see it already did the closing one for me. I didn't have to do the closing one. But look at that. It gives me information about this Python keyword, this Python function print. It says prints the value values to a stream or to sys standard out by default, optional keyword arguments, files, separator, end, flush, all sorts of other arguments we can pass. We're not interested in that. We're going to pass a string to it. Now we're going to, we're going to tell you what a string is for now. A string is a character or a sentence, something that you want to say. And that those always have to go inside of a set of single quotes or double quotes. Now Python leans towards the single quotes, but I'll show you sometimes you have to mix single and double quotes. For instance, if you want to print something that has an apostrophe in it, like the word won't, and you want that apostrophe, but you're going to use single quotes for that. So you can't use single quotes and single quotes. And then we'll get around that by using double quotes and single quotes. Python has a way to solve every problem. But I'm going to say this is easy, full stop. But it is a string indicated to Python by the fact that I've put it inside of quotes. As I say, don't worry about all of this now. I'll show you, show you what all of this, what, what it's all about. So this is easy, no problem there. And the next thing I want to print, this is easy, but I want it in a text cell. So I'm going to open a text cell. And now I can just type, this is easy, because this is just normal English, I can just type like a normal Word document in there and shift and enter. And that is it. Now it's also printed to the screen, but not as code, just as normal, like a normal Word document, no problem at all. So that was your brief introduction to what a notebook looks like a co lab notebook. It is based on something called Jupiter notebooks. So if you install Python to your own system, and you don't use co lab on the internet, then you are going to see exactly the same thing in Python. And that's called a Jupiter notebook. So this Google co lab is this modeled on on those Jupiter notebooks. Jupiter notebooks are fantastic if you install it on your own system, because you can use other languages as well. But we can use Python, one of the most recognized and used computer languages for data analysis, for statistics for healthcare, medical biosciences, all the statistics involved with that. Well, any kind of statistic really, there's no limit to this, but we obviously going to look at healthcare statistics. Python is just probably the most used language together with R in this field, it's free of charge, even if you install in your own system, you're never going to pay for this. And right here on Google co lab, you're running it off of Google's computer, which is, I know, a bit more powerful than my own computer, I can tell you that. And you can just do this, you don't have to install anything. And I mean, just just look at it. If I click on the left hand side, it's going to open this table of contents for me. It's going to populate that no problem. And it just looks beautiful. And in the end, you're going to see we're going to create these beautiful research documents that we can share with each other, because we can write normal English, normal paragraphs, put in photos, whatever we want, and the code, and the analysis of that code, all our p values, all our standard deviations, etc. And we can even create plots. It's a beautiful, beautiful document that we are going to create. Just look at that for me. This is really, this is something special and fantastic.  No problem whatsoever. So I hope to see you in the next video. Please play around with Colab. If you have any problems, put it down in the comments, let me know, and we'll solve the problems as we go. Don't be worried about the code that you've seen here. This is not what this first section is about. I'm going to teach you everything about writing Python. The reason why Python is so popular is because it's so easy. It's almost like just writing an English sentence. You'll just see how easy it is, how easy it is to pick up, and it's going to love using it. It contains almost everything you need to do data science, healthcare statistics, even the new kid on the block, the favorite kid on the block, deep learning, part of artificial intelligence. So easy to do right here. See you in the next video.


Troops of the Nigerian Air Force have rescued scores of kidnapped victims in the Igabit local government area of Kaduna State. If I-to-jet and aerial patrols spotted the location of the kidnappers, before airmen rescued the victims, most of whom are women. The Kaduna State Commissioner for Internal Security and Home Affairs, Samuel Aruan, says bandits had earlier invaded two villages and abducted several people. And in another third case, bandits have killed the driver of the airmen of Beningwari. His name is Nasirul Muhammad.