 a business up yourself, in your company's environment. so like now, let's say, you need to do- there is only a request from the office and let's say you have to take in your line manager after signing. then and another person after sign before everything is accepted let's say that request, it can be eSели, for paper- ay one electro paper the you take the paper, they signed, anlat sauce avoin an ad we celebrate he pinch you need jan staff Jazz ca 👂 grand edition brushed prison this it it meant not  Sage  lacks  aperture  는 琵琵  dreg  asse  plenty                                                                                 �eko  SEÑ csak  sayin �cesso � colored ᴄ домой ᴄ iron dream Ṛ sĀ damping 柈a palt Ṛ jĀト...... 食 � bugs ത Emergency Ṛ sĀ BudENT నసికుచేలిలా Çok కిరెకుభెరికిందారైఆకలా చ్ల౑ంఽ� Grape మuvo� wheరునేకుదారేలి ఒగొస్ట్ల్లిరూఽనినారిలేదుకార వెడిారిా cheesecake                                                          .   ,  ,               . ఝవనీమాడర చానీఆక్లి కంట౉తీకునీటకి చాణ докум筓 Craft gracias ​​​యంఠిెటీ కఎలిలు వంటీ astronomy and it is the meaning of owners. novo app that will be used for Microsoft. So not Microsoft everybody Microsoft like now the bed of an app now the app will have to be used for Vicky Blan. onton ఘtaa Several school soon yes ఙ్రంది Mā Unter ⋪ mistressó ల్నizado ౰఼డి car మోచి the Bayern ర >>: న Crossing త Bead ల్మో 20 తంతికిని . రిదినికికితాం. మార్ ంరికాటాం. మా మారం పబెట్లలి టినాబనాం. మారం దికికినిటిం. మారం మారం కింటినికా.  strangers  dur   everywhere   y వితోనికోలికిపెటరంటరింవవిలినియాఊింటూ. వింటికలంటికాటిక౿టా. దలి దిలికి. న౿ న౿ పంటీ ని ఉిరికికోటనెటికిలి. సౘినిమోటలా నించి కిమ౔ాసాంచిమాఖి. సారసియాశి కాంంచి. వౄంవౚలిని వ్యến వారకా వైవిం్వానాధ౜దషని లుపారిక౜దకమULL蛋 of автомоб � turn down మోథ్టొఠరకక మ్నే. To analyze. So this is another part of the వాతిటో공 of the power platform that we call it. This power automate. So anything you wanna do, you can do them here. So that will flow with Power BI data driven a lot. So do you now see how all of them are entering inside each other? So that is how you can actually work with it. Anything that you wanna do, anything that you wanna do, you can create it here. This power automation. This power automation. Now, Power Virtual Agent was now giving a general, it was not January, I believe it was last month. So I've not really touched much on it. Was it last month? No, this month. Early this month, you know what I mean. Early this month. So now, what is Power Virtual Agent? Do you notice if you open a website? A website, you're going to a website. They're going to see a chat booth, the right-hand side. They're going to chat to you. That is Power Virtual Agent. So you're going to create a chat booth. Yeah, exactly. So if you feel you need, because of your sales, CRM, guys in sales team, you need to create a chat booth to help you explain to customers or anything like that. Power Virtual Agent is used. So this is for application. This is for automation. This is for chat booths. And this is for analytics. And we therefore, we have standard vision that same thing. Power brand. Power and power to be the same thing. Do you think they are the same thing? No, no, no, no, no, no, no, no, no, no. Our commission is trying to save the automation. This is not creating half at all. This is just a commission. It's a commission process. They're just automating the process. So you don't think that's happening? No, it's going to be different. So let me see something for you. Let me just do something here. I've created one, but let me just see. See, send myself a reminder in 10 minutes. Let me just use this. This is not an app at all. So flow and delay. Okay, cool. I create a flow. This is not creating app now. Do you see it? Create a flow. So now immediately your flow hasn't won yet. So now what I'm trying to tell you Give me a reminder in what? 10 minutes. So now look at my flows. Yeah, I have edited it. So let me go to edit. See it. Manai trigger a flow. But click it. I want to add an input. Any input I want to add, yeah, I can add it. Yeah, email, text, what type of thing that I wanted to send to me. Then I click delay. How many minutes? You said how many minutes? 10 minutes. Again, this is not an app. This is just a process that I'm trying to automate. If I'm done with it, I did tell you that I want to edit. I click save. I am done. So the next 10 minutes, I should expect a reminder. Simple. It's totally different from this guy. Okay. This guy wants to create an app out of nowhere. So if you want to create an app, you should have a data set somewhere. So when you have a data set somewhere, you're just dumping it and you're bringing it in. When you're bringing it in, you're just trying to create something for you. And to help you create it with low code application, we call it low code. And maybe you have heard that word maybe on Twitter too. Low code apps. That is what we call the power apps. Low code apps. Whereby you don't need to become a software developer to be able to create it. What about data security? Security there too. Even created the white paper as yesterday that explains everything on security of power apps. Everything on security of power apps. Everything on security of power apps. So the way Nest year itself will be diving a lot into this part. We'll be diving a lot into this part. So it's from Nest year. So according to what you see here, it will burst. So. So now let's go back to Power BI. Now, remember I said something that. Remember I said that all these things they come down to, if you want to analyze with the Power BI itself. Now when you go to, let me go to home. And you see get data there. If I click get data there. And I go back to more. Let me show you something here. Now, can you see the power platform? So now, power platform is new here. Before it was just two. This thing here. They added the power platform data flows. Anything from this thing here. You can analyze it down here. So from Power Automate, Power Virtual Agents. You want to analyze in Power BI. You can click here. You won't connect to any of the flow that you have. In Power Apps, in Power Automate, or Virtual Agents that you analyze. Imagine you want to analyze how many customers they chat with you concerning these social products. You can analyze it. So do you now understand how it's now a platform on its own. But the value into four. There are some people I met as I last month I went for a conference for the Power Apps with Microsoft. So there are some people who know only Power Apps. They know only Power Apps. They don't know Power BI. They are good with Power Apps. I was surprised. They were good with Power Apps. Median guys, good with Power Apps. You have seen the picture now. You have seen the picture. You have seen the picture. They are good with Power Apps. But they are not good with Power BI. So you will see some people who are good with Power BI but not good with others. You understand? But it's getting a process. It's getting a point where people cannot become a Power Platform as part of their own. On their own. So that is how you move. And that is how we move like that. So this is just introduction to how the Power Platform is like we do live lab every month and how you can really gain a real world. And I used to tell people when I train people I tell them that you should not always work because oh, I want to be understanding Power BI business and since I'm a banker, this type of data is what I should go used to know. When you come out into a live lab, you see a whole lot of different type of data that gets you into different type of environment of Power BI that you've not even worked, you've not touched. Same with Excel. Why is this somebody doing Excel? Where did you go to get this one? There is a Power BI is. There is a Power BI is. And they update every month. This new month is one I showed you whereby we can remove this one filter. It was just done two days ago. Was this moved ago? Yeah, two days ago. And I moved this filter less two days ago. Now also, do you know that we can remove visualization that we don't need? When I take this, I can open this visual and it lives. If I click OK, it's almost to live. So you can, have you, do you notice it? I don't want it. So it's now here. You want to take it back? I can put it back to my custom visuals. So if you want to update your Power BI, you have to go out and do the game. OK, so now there are two ways for you to update. For you to update your, so now if you go to Google, you want to take it to Play Store. Your Play Store, then it's updates. Yeah, your Play Store. Are you a Play Store? Yes, make a place then it's updates. Then the second one is the one that you have to now download. Wherever you download, I didn't find it and created something like that. Then you now install. That is the second one that you do. And that one is what you do every month. That you have to be with downloading, with downloading, with downloading and like that. So it's kind of stressful. But Play Store, for the one of Microsoft Marketplace, it's updates automatically for you. Update automatically for you. So but another thing is this, there are some updates that you would do that you, it won't just work immediately. This is where you should always go to when you notice that there's a new update and it didn't work immediately. You go to File, you go to Options, you go to Option again. Do you see this preview feature here? Always go there and tick. File, Options, Options again. I don't see preview settings, preview features. Then you just tick, majorly all of them. Even I want to do Spanish language support, you can't tick it too. You can't just tick it too. So now in the next 30 minutes, one want to talk about is data modeling. Before we go for our tip, data modeling. The one we have done when we come back will do an aspect, data modeling. Now, do everybody have this data? Have you downloaded the data from Power BI user group? You see the data from Power BI user group. Do it monthly. So just open the file. You have data? Power BI user group, Lagos. Connect, connect now. Internet, Internet, train, download it. Try, try. If Power BI is under, I don't have it. Connect it to Internet, connect your laptop to Internet, download it. Yeah, or my personal laptop. Your personal. So just try. Yeah, let me write it for you. So you go to Power BI user group, Lagos. You will see it there. Power BI user group, Lagos. Okay, they are dot com slash Lagos. So you did, when you enter there, you are going to see December files. The simplest form in Power BI is actually the visualization. The simplest is visualization. Ask anybody you use Power BI. Visualization is pamp pamp pamp pamp. But when we want to talk about the address, it's here. If you miss this one, your DAX2 is wrong. So if you like no DAX, if you miss this, your DAX2 is wrong. So DAX2 is wrong, we call the data analytics special is a coding language for Power BI. Power BI language is DAX. But this is very, very important when it comes to analytics, Power BI analytics. So now, relationship that are built here determines what we see here. Relationship that are built here determines what we see in our report view. If your relationship is wrong, what is there will be wrong. So now, there are some things that you have to get right here. And that people miss. That people miss. You have to get it right. So what is the first form? We call it, in Power BI, we call it the star schema. You have star schema. Now this is it. Now, this is how it works. So you have this in data modeling. Two things must connect. The fact file and the dimension files. Best practice. The fact file and the dimension file is the file that builds every day, every month, every week. Remember those your sales report you collect every day. Those your sales report you collect every month. All those ones are fact files. They build, they increase. But our dimension, we call it categories of imputes. How to see the sales report by different regions? Regions are dimensions. How to see a sales report by all customers? The customer information is dimension. It's just like a category. You know in paper table now what we used to do. You know in paper table is two things. You know your values or your categories. You are ticking values categories. Your categories always go to your role and column or filter. And your values always go to values. So that is just how it works. So dimensions are the things that give concept to your analytics. So I say Abu David bought laptop for 30,000 Nair. Now Abu David and David, Abu, Samar All those ones are just dimension of what? What we call names? Customer names, customer ID. Those are dimensions. But fact file is what we call the combination of this dimension and their value. Combination of dimensions and what values. Remember our sales report will not be a report if there is no value attached to it. Your time table or the time that people come in. What do we call that name now? And then that's shoot. The login shoot. It's not being an information or a fact file if you don't have the time they came in. If you don't have any names, I don't know when they come in. It can't be, you can't build on it. It's not a fact file. It's just a dimension of me. But when it begins to have, whether you have the time for Monday, you have when it came in Tuesday, Wednesday, Thursday, then you notice that it becomes a fact file because it's what? Building. That is it. So you need to understand those two things first. And that is why in our app query, if you go to our app query, if you go to our app query, I don't want you to go there because you have so many things that I've been, okay, let's go. So I want you to see something. We're going to start from there too. Go to transform data, you click, look up, you see transform data. Click it. Transform data. Edit queries, okay, edit queries. For those who are not using the most recent one, you are going to see edit queries. For people like us, they are using the G-wagons. Use transform data. Yes, just do it. Is it the new one or the old one? The old one, the old one, the old one. You are good at now. Do that so I say it's your book. Those options and look at it if it has been ticked. Yes, don't worry. I say it, don't worry. Now, if you go there, did you have something like this for us? Like this. If you don't have, it means that the data itself, you've not connected to your data itself. So that one is something I would do for you during lunch break. That one is just simple. For those who have been coming every month, you know how we used to do it now. You go to your source and connect to the file that you are fine. Go to source, connect to the file. Population, you have your data for population that you've downloaded already. You see population, they'll connect to it, you have this. Now, see. Population is a fact file because you have population for different year. Have you? You have life expectancy for different years too. Same thing. Life expectancy for different year. So I think I need to use my mouse. Okay. So, life expectancy for different years, you have it. Now, if you look at your income, income too goes the same way too. When you, if I click income, the same thing, the same country's information like that, like that, and it comes like that. Now, you don't have countries and continents, but poverty, same thing. So all these things that we want to be doing in different, different months in our life labs, for those who have been coming since August, you see it. Now, we now have literacy also. Literacy. But what we now did is this. Since all of them are actually the same kind of sets, we have country indicator name. Indicator name is literacy. If you see, if I go to poverty, you see poverty there. Indicator name, poverty. The year, the values and the worth, the date. Now, what we just did there was to combine everything. What can I remember doing, we combine them. For those who is to come every month. How did we combine one, two, three, four, five into factor? Thank you, append queries. So there's something called append queries up there. So, can somebody tell you what is even between append queries and met queries? Merge is to add in columns, then one is down, so that is it. So now, we used append queries and everything comes here. So all this become one file, a factor. So what we now did is this. We now say that, see, you these guys, don't know to poverty anymore. Because you are already here. So don't load. So we remove the enable load and it becomes this. So this is what we did here. You come here, right click, you see enable load. There's nothing to be tipped here, but I didn't remove it. So I don't go straight to what power BI. So that's what we just did. So now since we have factor, we now say, that is our factor, but how do we get dimension that will make us to be able to create a data model? Now, look at this here. We have countries. It means that for us to be able to create a dimension, we have to go and look for a database that have only words, countries. They will now connect it to the fact file that is country also. That is where we can build relationship. This, this guy here, countries. So that is where we now went again to Google and say, okay, can we get countries and what continent? This is it. We have all the old countries and continents, but the number one rule you should always understand in data modeling is that your dimension file must be unique. It must not be repeated. Remember that in our fact file, it's built in every time. So you will always see and the news can come in one million times. You have so many countries there. So let's go to those. You will see them here. Can you see? These are all the countries inside this data here. These are all the countries. Now, but we now said that for dimension, it is not building. It's not increasing. It has to be unique. If it is not unique, it should become a problem when building our own data model. So we now went and said, okay, fine. Let's get the name of our countries and continents. Countries and continents. And this is where our dimension file came in from. So we now know that fact file and what dimension file, that is how we rise back to what power BI. So you just click close and what apply. Now we're here. The news are at all, are we? Okay, go away. It's just the same thing that we did now. The data itself. Go back to the source. Go to source. You see source, you apply step. Check your apply step. Yes, then click it. Go and connect your source from your data set itself. You know what you're done with right now? Your population don't fit there. We've done it before. You for that, it will do it though. It doesn't have a fact file, I imagine. When you're done with poverty and literacy, fact file will be cleaned. When you're done poverty, it is fact file will be cleaned. Yeah, good job. Okay, so now notice our fact file. Do you now see our countries and continents? Now do you see these dates? Somebody will now ask why are we having eight dates? Why should we have eight dates? So simple. You remember that we are doing eight dates? Now remember that we have an analysis that we are doing for over 40 years. From 1980s, if you can see the dates, you see it. We are doing from 1980s, we are doing a time series analysis. It means that we will need to add a date word calendar. Most of the time in your analysis, you always add date calendar because you want to see a report that's done month by month. You know the way we should do now is month by month analysis, year on year analysis, time series, year to date, all those things that we should do. Sales last month, sales previous month, sales last year, all those things that we should do. So you need to add a date data. And that's what we did here. So how did you do that? You come here, it's just a simple function that we did in our dates. So maybe if you want to write it down, this is it, date, calendar or two, open bracket, clear bracket 12. Go to your data view, make sure you're clicking on date. You're going to see it there. This is the function that we did here. So we went to, we just created a DAX formula here to give us a data of calendar. So what will that calendar auto do is this. Then you have to go and look at your data and look at the first tier of your data. Then from there, it's going to create a date. So you're not repeating it. Even when you get to the end, it maybe knows that you're going to another year, it's going to create another word calendar for you. So you're not repeating it at all. So calendar, that calendar auto, I will not touch it again. So that's one of the benefits. There's another one called calendar. But that calendar, you have to not specify and the end period. That is it. But calendar auto is an upgrade level of calendar, calendar auto. You just have to meet that process for you. You get it? So this is it. So from here, I can also create. I can say I want to create month, I want to create week, I want to create all those ones. If I want to. You know we do it in Excel. Equals two tags, all those things that we do. Yeah, so that is just it. So now, let's now go back here. Moodle, the first thing I said is this. You need to know your factor, big boost every time. They need to know your dimension, which is what's unique. If it's not unique, it becomes a problem. Now the last thing I want to say here for the best part is this place. When you double click here, can you see this line? Everybody check your screen. Can you see this line? Continent is connecting to work. Continent. When I come here, that is connecting to work. If they are not connecting to the main thing they connect to, it becomes a problem. Now I want you to see it to check something. If I double click here. Yeah, these are our finish up. The lines, when you double click, can you see our factor? Can you see country and continent? If I click here, you see which one is greater? Continent is greater. Continent year is greater. I really want you to see what the cardinality is saying here. Many to what? Many to one. What do you think our many will be? Fact or countries are continent? Fact far, many. Fact far, many to one, which is what? Country and what? Continent. What is the meaning of many? Many is this. Let me give you a simple explanation of many to one. I have a son in a school and I have to be paying school fees every day. So if I pay every day I pay interest in second time, third time then the person promotes to another class and I'm still paying. Now notice if the proprietor wants to do analysis he's going to say how many times did Mr. A pay for his son? The many to many, many, many becomes the what? The fact far because I'm coming back, coming back. So you're going to be having a database and say Mr. A pay first time, pay second time, pay third time. That is many. One is the school that is receiving it. So it's just one, the child one is just collecting it, collecting it, collecting it. So your fact far is many, is repeating most of the time. The time that you are in your data that your dimension has to understand becomes not. You see a yellow big line that is telling you many to many cardinality as you see in one long sentence like that. There you have to clean it up. So if you have more than one child, maybe three children. Exactly. Now if you have more than one child you always notice that even in Asia, Asia has more than one country. It doesn't change it. But the lowest, because of the lowest granularity in Power BI that says that so if you're looking at our country, we have state and we have local government. Our state, local state has different local government. So if you're looking at our lowest granularity, our lowest granularity is which one? The local government. The local government is our lowest granularity. So now if you're even paying for my child, the child itself is not my loop head. Which one is our lowest granularity now? The what? The child or the children? So since you want to build on it, when you say, oh, who paid for this type of child is still the same father? Who paid for this type of child is still the same father? Who paid for this type of child is still the same father? So if you want to group, they are grouping them together in the first place. So each of the child itself is just like Africa. Africa, we have Nigeria, Ghana, Sierra Leone. They are the children, but it's still Africa, are they? Now if they are collecting here, which is many here, you'll be having so so many of Africa. You'll be having so so many of Africa. You'll be having so so many of Africa. You'll be having so so many of Africa. You'll be having in that we have this thing here, continent here too. Same thing that will say happen. Because Nigeria will be talking to Asia. Sierra Leone will be talking to Africa. The children will still be talking to their fathers. It still doesn't change. The lowest one must connect to the lowest. The lowest must connect to the lowest. Always remember that. Our lowest one here is what's country name. The lowest one here is one. If you have a customer ID and you have a customer name, which one do you think should be our lowest? Customer ID. With a customer name, you can be repeated twice. And different people. But the ID is always different. So it's always unique. So now if I'm building a relationship, I have to build it with the customer ID. So the customer ID of our fact file, you will be having customer ID, customer name, sales, region, what is the sales price, something like that. In this place, you have to have audio staff list. They have the customer ID and the what customer let's say name. Then when you create a relationship that's creating it, repeated and one is what's unique. Always remember, this has to be repeated. This has to be what's unique. Then it becomes our many to one. But there are different levels here also. If I click this drop down here, I know that we have to go for a tea break now. Thanks. So please clap your hands for Tewa. Tewa is the one that is taking, he's the previous lead. He's our previous lead. Is it always sad? I'm sad. Exactly, she's always busy. Okay, so many to one is this that we're doing. One to one is whereby we have analysis that our fact file is coming just one time and our dimension is coming a many times one. There weren't too many. It doesn't really happen much of the time. These are kind of advanced level most of the time. I've really not seen any project that is bringing these two. They're working with these two. They've always been the first two. So many to one is whereby your fact file is one and your dimension is coming many times. I've not seen it. The many to many is where both of them are coming multiple times. Now, this many to one is that it comes automatically or we have to like choose. Okay, so most of the time it comes automatically by default. It's many to one, by default. By default it comes. Exactly. Even sometimes, part of it is intelligent enough that when you even dump, maybe you load everything for parkway and you dump them there. It should be related for some of them for you. I don't know if you have worked with any data like that. It should be for you already because you have seen it already. It knows your fact file and dimension even before you are bringing it. So when it dumps it, it just creates it for you. There's even a place here that says auto-relationship, auto-detect relationship. Who have used that before? Sorry, I'll show you where it is. So this one made this relationship active. Please, if you're working, this one makes you extinct. If the relationship is not active, your data formulas won't work. It won't work. Even when you're clicking, it won't work because it's not active. How do you know if it's not active? Let me close this. Do you see this line? It's because if you see it as straight, it is. Straight. But if it's not active, you will see that it is broken. So let me see who notice kinds of differences now. One is active but is not active. So when you're creating relationship, it becomes usual. So you have to note this. Whenever you say anything like this, always remember where you will go and click it. So you have to make sure it is active. Therefore you have to work with other ones. These ones, you don't touch this. This has to be single. By default, as soon as it is single, by default, you click here. Now, property. One is one that loves property a lot. So what do we do with property? So imagine continent. If I click continent, I use a continent. So I can use my language. I can change languages on Power BI. If I want to do your Uber analysis, I can do your Uber analysis on Power BI. Uber analysis. How would I do? I'll just give it synonyms of names. So I don't know what is continent in Uber. Adbebe. Adbebe. Adbebe. Something like that. Adbebe is world. So I'll give it like that and I can just analyze what I want to analyze. Using different languages. So if you are working with somebody in French guy or something like that, you really love to work with. Because the person will be talking with French. And you will be talking with English. So you can analyze your reports. That way. You just change from synonyms aspect, right? Yes. You just change from synonyms aspect. Change from synonyms aspect. So this is property. You just talk about what I take. So now we talk about continent name. Same thing. I can work with it. So I can say whenever this Power BI see country, you understand, I'm talking country. So that is how you can work with this. So now whenever we have in what we call model view when you are trying to build relationship one of the best aspects of this place is that it gives you opportunity to understand where and why you are doing your reports. So you can understand where and why you are doing your reports. The end goal of your reports start from you understanding what your report will look like. Even your report won't look like once way. This is where you understand how you build it. Another most times even when I train when I say something that always do it in paper first always build your model in paper first. When you're in paper it's so easy for you to create them here. So easy for you to create them here. So easy for you to create them here. So easy for you to create them here. So that is how you do it in creating your data model. So data model is about relationship. And you need to understand your what dimension and you need to understand your many to what many to one. Whether you are also picking the right things that are connecting to your fact file and to your what dimension file. And also again making your relationship what active. You have to make your relationship active. It is broken, you cannot work with it. You cannot really work with it. So now when we come back from t-break we will go into dashboard, building of what dashboard. So thank you very much. The one in PowerPay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .