Tableau For Data Science Full Course | Tableau Projects For Data Science | Tableau | Simplilearn

hey guys welcome to simply learn's youtube channel today we will be learning cable u for data science so we will get started with a brief introduction to w followed by that we will understand the fundamentals of w where we will be covering the overall tools and functionalities available in table u later we will dive into the practical part where we will have hands-on session and try to design and develop real-time data sense projects and dashboards i hope i made myself clear with the agenda before we get started make sure to subscribe to our youtube channel if you haven't already don't forget to hit that bell icon to never miss an update from simply learn so what is w so before we understand what exactly is w let us imagine a simple situation imagine that you're an office worker and you get some loads of data maybe like millions of rows or billions of rows and you are supposed to extract the insights of that particular data so what do you do you basically load that data into a database and try to write the sql commands and then try to extract the insights of that particular data so this kind of approach is basically time consuming and you get exhausted now what if you had a tool which could write all the sql commands for you in the background and all you had to do is just to drag and drop the data sounds interesting right so tableau is just the same all you have to do is just drag and drop the data and it will automatically write all the sql commands you ever wanted to write on that particular data and it will give you live data interactions and advices for the future now with this let us understand the definition of w so basically tableau is a business an analytical software tool developed in america w helps people to understand visualize and make data driven decisions in real time with extreme agility and accuracy now with this let us continue with the next topic which will be about the various versions of w so at first we have the tableau desktop so tableau desktop is a data visualization application to facilitate you to examine virtually any kind of structured data and generate highly interactive beautiful graphs dashboards and reports within minutes once a quick installation you can tie to virtually any data source from spreadsheets to data warehouses and display information in several graphic perspectives designed to be easy to utilize you'll be working more rapidly than ever before next we have the w server it is a business intelligence application that offers browser-based analytics anyone can utilize it is a rapid-fire alternative to the slow pace of traditional business intelligence software it is an online solution meant for sharing distributing and collaborating on content created in w what makes w different it is proposed to everyone there is no scripting required so everyone can grow to be an analytics expert you can grow your deployment as you require it train online for free finances in minutes and not in months that's the speciality of w now followed by the w server we have w online so w online is a business intelligence application that offers browser-based analytics anyone can utilize as discussed before it is a rapid fire alternative to slow-paced traditional business intelligence software so tableau online is a secure cloud-based solution for sharing and collaborating on tableau views and dashboards next up we have the w public so now i want to give you guys a serious heads up if you're a beginner in w w public is like an open source whatever the data you choose to work on using tableau public it goes to public so kind of like wpublic is not preferable if you want to work on your company's sensitive and confidential data w public is a free software to facilitate anyone to get connected to a spreadsheet or a file and create interactive data visualizations for the web it is delivered as a service that permits the user to be up to and running overnight with tableau public users can construct amazing interactive visuals and publish them quickly without the help of programmers or id it is designed for organizations to facilitate their websites with interactive data visualizations there are higher limits on the size of data you can work with and among other features you can keep your underlying data hidden and lastly we have w reader w reader is a free desktop application that you can use to open and interact with data visualizations built in tableau desktop with tableau reader you can filter drill down and discover humongous loads of data now moving ahead we have the features of w so these are the few important features that you might want to consider those are the first one robust security tableau takes special care of data and user security it has a foolproof security-based authentication and permission systems for data connections and users access w also gives you the freedom to integrate with other security protocols such as active directory kerberos etc an important point to note here is that the tableau practices low level filtering which helps in keeping the data secure followed by that we have the collaboration and sharing feature tableau provides convenient options to collaborate with other users and instantly share data in the form of visualizations sheets dashboards etc in real time it allows you to securely share data from various data sources such as on-premise on cloud hybrid etc instant and easy collaboration and data sharing helps in getting quick reviews or feedback on data leading to a better overall analysis of it another extremely useful feature of w is the use of time series and forecasting easy creation of trendlines and forecasting is possible due to tableau's powerful backend and dynamic front-end you can easily get data predictions such as a forecast or a trendline by simply selecting some options and drag and drop operations using your concern fields next up we have live and in memory data tableau ensures connectivity with both live data sources and data extraction from external sources as in memory data this gives the user the flexibility to use the data from more than one type of data source without any restrictions you can use data directly from data source by establishing live data connections or keep that data in memory by extracting data from a data source as per their requirement tableau provides additional features to support data connectivity such as an automatic extract refreshes notifying the user upon live connection fail etc next we have informative view and even the mobile view one of the key features of w and the one that got its popularity is its wide range of visualizations in w you can make visualizations such as bar chart pie chart gantt chart bullet chart motion chart tree map box plot and many more like you name it w got it you can select and create any kind of visualizations easily by selecting the visualization type from the show me tab apart from that it is capable to represent data in mobile view as well tableau acknowledges the importance of mobile phones in today's world and provides the mobile versions of tableau app the next and the last feature is that being capable of accessing data from various kinds of data sources tableau offers a wide range of data source options where you can get connected and fetch data from data sources ranging from on-premise files spreadsheets relational databases non-relational databases online cloud data to data warehouses and many more so followed by the features now we will discuss about the advantages of w so following are the advantages of using w first one it has remarkable visualization capabilities of course the unparalleled capabilities of visualizing information is on top of the list of tableau's software benefits followed by that we have the ease of use the tool's intuitive manner of creating graphics and a user-friendly interface allows non-developers to utilize the basic apps functionalities to the fullest users arrange raw data into catchy diagrams in a drag-and-drop way which facilitates information analyzing and eliminates the need for the help of it department and patent building next high performance apart from its high visualization functionality uses rates its overall performance as robust and reliable the tool also operates fast on big data which makes it powerful performance on an important point on the list of the advantages of w and next is the mobile friendliness one of our best advantages out of the tableau benefits is its efficient mobile application which is available for both ios and android it adds mobility to tabular users and allows them to keep statistics at their fingertips as well as supports their functionality that desktop and online versions have and finally we have the thriving community and forum w has a rich community the number of w fans who invest their expertise and skills in the community is increasing rapidly business users can beef up their knowledge on data passing and reporting and get many useful insights in this community also forum visitors are ready to help settle any user issues and also share their experience next up we have the disadvantages of w the first major disadvantage is the high cost the tableau is not the most expensive visualization software especially compared to such business intelligent giant such as oracles and ibm solutions all the same the license is quite costly for small and medium companies which makes it one of the considerable tables disadvantages next is the inflexible pricing tableau sales team is not flexible enough to provide case-by-case approach for their customers ignoring the fact that each company has its own unique requirements for visualization tool package the tableau sales model requires clients to purchase an extends license from the start as a result a lot of companies that use w arrive at the conclusion that they don't need all their license features they would prefer to buying a set of requirements and scale them if necessary followed by that the next disadvantage is poor after sales support on multiple message boards users complain that tableau software lacks proper after sales maintenance if customer has software performance problem the support team does not settle the matter by investigating the problems root and eliminating it next we have the power bi capability or the poor business intelligence capability as previously mentioned the tool provides best-in-class information visual interpretation however it lacks the functionality required for a fully fleshed business intelligence tool such as large-scale reporting the building of data tables and statistical layouts and lastly the poor versioning only the reason tableau versions support revision history while for the older ones software rolling back is impossible if getting your learning started is half the battle what if you could do that for free visit scale up by simply learn click on the link in the description to know more so tableau is a business and analytical software tool developed in america w helps people to understand visualize and make data driven decisions in real time with extreme agility and accuracy to better understand what exactly tableau does let us imagine that you're given some data in the form of excel sheet that has thousands or even lacks of rows and some hundreds of columns or even thousands of columns and you had to kind of filter or kind of apply some operations on that and get some insights of that particular data so basically if you do it in a brute force method it could be really time consuming but what if there is a software that can write all the sql queries possible on your data and all the data you wanted is readily available or all the information you ever wanted on your data is readily available just by a single click yes exactly that's what exactly tableau does it automatically writes all your sql queries in the background and it can provide you the information in the form of a variety of charts like the bar charts pie charts and it can even give you some live data and also the advices based on which you can move ahead and improve your business now let's go through some sample data and understand how it exactly does it so on my screen you can see some excel data which is based on some store in america so here you will be having different regions of america that is south north east and west and the category of furnitures subcategory bookcase and etc etc which kind of category is selling most in which kind of region and what's the discount what's the quantity and what's the profit etc etc in this particular excel data so you'll be using this particular excel data to get some insights of this sales happening in america so this is how business intelligence works basically so here we should use the microsoft excel to get the necessary insights of this particular data now just select all these cells of this particular excel and select insert and on the left corner you can see pivot table select that and here if you had an existing worksheet you can select the existing worksheet or if you don't have that you can select the new worksheet option and then just press ok now we have our pivot table over here and we have our fields in the excel data on the right side part now just select a region and push that into the columns and now let's select sales and push that into the values now we have the sum of sales options so we have the east zone central zone south zone west zone and the summation of sales happening in that particular section of america or region of america now we can also make some changes to the values like we have summation and we can select some value field settings and inside that you can go through count average maximum minimum and select few more options based on which you have to calculate it now let's push the rows or let's push the regions from columns to row so that we can have some good data in a more understandable form of view so there you go you have the central region east south and west on the left side and on the right side you have the summation of sales happening in that particular region and the grand total of the sales now let's try to do this in the table so there you go your table you just got started so on the left side you have got the connect option and the various types of files it supports that is the microsoft excel text file json file microsoft access and more on that in the next upcoming part where we'll have a tour on that now let's select excel so we have already an excel file on the downloads path just select that one and just open it and there you go you can see all the rows and columns here now let's go to our sheet so on the screen you can see that on the left part we have the data which is connected to the w that is sheet one the store data and these are the dimensions and these are the measures so basically tableau divides the data into dimensions and measures automatically and you can see some options provided on the top row which is the file data worksheet dashboard story analysis map format window help etc and here you can see some marks which is the color so he here you can just imagine that you worked on some bar data or bar chart so that you can use color options to provide different colors to your bus and you can also select the size of your bars add some text if you wanted to add an and you can some add some details if you wanted and some tool tips etc and on the right side you can see show me option and this particular tray helps you to get different types of charts you wanted to keep on your data for example you want to select pie chart you can just select pie chart if you wanted to go with bar chart you can go and bar and some area charts and you can see maps etc and the best part is when you hover over this particular chart or any kind of selection you wanted to make then table tableau automatically helps you for having the dimensions and measures for that particular chart you can see in the bottom part where it is highlighted for pie charts try one or more dimensions and one or two measures so if you hover over the bar chart you can see that w tells you for side by side bar charts try one or more dimensions and one or more measures so basically it is telling you to have one or more dimensions or one or more measures in order to use the side by side bar charts now let's do the same thing what we did in excel so here we'll just select the region and pull that over the columns and now we shall select these sales and push that over the rows and there you go you can see the bar chart over here and it's automatically telling you the kind of sales happening in that particular region now you can even select the region part and drag that over to color so that it gives you different colors now if you see on the right side a show me tab you can see different types of charts available for your data so you can have a pie chart you can have the bar chart you can have few more map chats etc etc so that's how tableau gives you automatically all the types of options that you can work on the data visualization by using different types of charts so that's how tableau basically works now we will go into the next step where i'll help you to install tableau into your local system once the installation is done we will get back to w again and we will understand each and every part of w in much more detail and we'll also work on each and every type of chart present over here and we'll work on multiple sheets and finally we'll enter into the dashboard so far so good i hope you have understood the basic introduction to tableau and basics of the w fundamentals how to use rows and columns what are dimensions what are measures and what does show me and how do you change colors of your bar charts over here and you can highlight this so we'll work on everything after we finish the installation process and get back to worksheets if getting your learning started is half the battle what if you could do that for free visit skillup by simply learn click on the link in the description to know more so before we go any further on tableau installation let us understand the tableau products first so there are multiple types of w products so here we will be having table use desktop w public w server w online and the tableau reader so let us understand tableau desktop first tableau desktop is a paid desktop application it is also called sw desktop professional edition this is where the developers create charts formula dashboards actions and everything it has a 14-day trial too the dashboards we create here can be published on any server listed above the data can also be opened from tableau reader moving ahead we shall understand the tabular desktop so for beginners let me tell you w desktop is like open source data whatever the data or whatever the sheets whatever the dashboards you work on using tableau public will be available for public so keep this as your reminder and it is not preferable if you want to use w for your company's confidential data because it might go public and it might be risky so tableau public desktop is a free desktop application it is the developer place for tableau public server it is free and has to come with some limitations like cloud save only no live or database connection there are widely used by learners bloggers and public information related institutes like media etc now moving ahead we have the tableau server so w server is a free server in the internet this is the youtube or blogspot in tableau data visualization world it is free and people post their ideas and visualizations here we call it the visual blog it has no user management or folder management options you can hide your work though it cannot have live data source but only extract so many people publish their ideas and custom visualizations here we could find the inspiration from here now next we have the tableau online w online is a paid server application too but it is already hosted by tableau software and so no need to install it on any windows server it is better you need the tableau dashboards to be accessed from anywhere it has almost all the features of tableau server but only on the internet not on your local system and finally we have the w reader so w reader is a free desktop application which can help us to view the tableau dashboards created by tableau desktop it supports only extract connection files it can help new people to try tableau by getting one license for tablet desktop and installing this free software on their end user's machine it can open the dashboards interact with them like filtering tooltip and parameters we cannot edit the formula or charts here now i hope we have some good understanding of w its introduction and the various products of tableau available for users now let's begin with installation so the third segment tableau installation into your local system now here we'll be trying the windows operating system now to install avenue into your local system all you have to do is open google and type in download tableau public and you have the first option that reads download now w public i would recommend for beginners to select w public because it is free now let's go back to google once now on my screen we have open google just now type in download w so once you type in download w you can see various options the first one though is tableau desktop which is a paid version as i said you you have to select tableau and it is free of cost and you can try out your sample data over here for free and once you select the tableau public option you have this particular web page open and if you go back to the presentation you can see that i have written something called abc gmail.com this is basically your email address for getting registered and downloading the application so you can write in your email over here which can be anything like i have written abc there gmail.com just make sure that the mail id you provide is an official one or it is an operational one as you might have to confirm your download once you write in your mail id just select the download app option and you can see on the bottom left corner the application will be getting downloaded now i have already downloaded the w public desktop exe file into my local system so i'll just cancel it for now now we are back on the presentation mode and we were in this particular stage where the tabularpublicdesktop.exe was getting downloaded once the file is downloaded just run the file from your downloads part and you can see this particular screen on your windows which will greet you welcome to w and here you might have to select i have read and accept all the terms of the license and just install and there you go the w public 2020.4 is installing into your local system and that's how you install tableau into your local system now we have entered into our next segment where we will be having the table you tour so once you open your tableau your screen will be looking something like this so this is the tableau in my local system and you'll be having the screen which is similar to the presentation one and here you have various options to connect to your data file which might be an excel text file json file microsoft access pdf file spatial file statistical file or if you had to download some data directly from the server you can even do that so now we'll be working with the local data or the local excel file in your local system just select that excel file and open it and there you go you're on your first worksheet just select the go to worksheet option and you'll be having your screen redirected directly into the worksheet and you have the dimensions and measurements on your left corner and you have the show me tab on your right corner and some marks in here and filters pages and various options on your toolbar now we have finished the introductory tour to our tableau and we'll understand more about all the options provided in this particular w screen through our worksheets as we start with our first worksheet so far we have understood what is business intelligence and the tabula's role in improving your business followed by that we have understood what exactly w is then we have understood how to install tableau into your local system and we had a brief introduction our brief tour on w now we will move ahead and continue with making our own worksheets and the dashboards based on the worksheets we have worked with so advancing into the fifth part we will be working with the worksheets and followed by the worksheets we will be working on the sixth part which is the dashboards now without further ado let's get back to w so we have successfully booted up our w and we are on the home screen of the w and on the left bar we can see that we have various connect options to the microsoft excel text file json file microsoft access pdf file spatial file statistical file etc and if you had to connect to a server this particular option is not provided in the public w it might be available in the server w and you can see that if you had to connect to the server in just in case then you're provided with various options here like you can connect with google sheets or data web data connector etc etc so today we'll be working with local data that is present in my local system that happens to be an excel file so you can see that in my downloads we have a set of excel files so we'll be selecting car sales updated data file now you can see that the data has been connected to the tab view and the rows and columns have been presented on the screen so before getting started with tableau let's have a quick update on the data so many times it happens that you download a data from google and sometimes one of the other rows or columns might have some incomplete data as you can see there is an incomplete cell over here which is a curve weight of a particular vehicle that happens to be cadillac's valley you can either try to remove this row or you can add some value over here like i'm going to add some value i'm just going to drag this one because they both look a little bit similar they have a same wheelbase and the kind of scene but so might be the curb weight might match so we'll just drag it over here or we'll just write it okay i forgot to enable editing fine so i'll just drag it here and i will have some values let's change it a little bit okay so you can see that we have filled up the cell over here let's just check if anything else is incomplete yeah there is another one incomplete over here let us just add some random values because this is just for practice here everything else seemed to be fine so the important point or the update i wanted to give you guys is that when you save this so when you get into a file and save as sales updated so when you save it make sure that you select the excel workbook if you don't select the excel workbook you might face some troubles while connecting the data to your table here that was the important update i wanted to give you guys so just select okay and your data has been saved now and let's get back to w now let's connect the data again by selecting the connect data option you can see the dialog box come up on my screen so you can just select microsoft excel and car sales updated open and you can see the data got connected just now again and you can see the rows and columns over here so everything looks fine and now let's get back to our sheet so this is the sheet we'll be working on we'll be creating multiple sheets so we're creating multiple sheets because we have some options over here you can see that right so this is the sheet and this is the new sheet option and this is the new dashboard option and this is a storyteller option so basically we'll be working on multiple sheets and then we'll start a new dashboard and we will drag all the sheets that we have worked on onto the dashboard so that we can have a view on all the sheets in one single screen so basically that's what dashboard is there are multiple operations on dashboard like connecting to multiple dashboards together and applying some operations like filter etc on the dashboards we will learn more advanced topics on dashboards in the advanced part which is the next part two of the w tutorial so we'll have a basic understanding of w functions in this particular part one right now no worries on that so you can see that we have uh options or the row names written in two different colors you can see that the manufacturer model vehicle type etc are written in blue and we can see that there is some sort of abc text represented on the left side and similarly on the other half you can see the curve weight engine size fuel capacity fuel efficiency horsepower length price etc and you can see that there is an asterisk written just besides them so why is this difference because w automatically categorizes your data so it will categorize the data into two forms that is the dimensions and measures so the dimensions happen to be the unique values of the data and uh the values are the numerical values used in your data so basically the curve weight is a numerical value engine size is a numerical value the price resale values width wheelbase car sales etc are the numerical values and in the dimensions you have a manufacturer model vehicle type this happens to be the non-numerical values so the manufacturer might be audi bmw etc etc and the model would be some 320i from bmw s-class from mercedes etc etc and vehicle type might be some just a car or off-roading vehicle something like that so these are the non-numerical values so these are categorized into uh dimensions so sometimes there is a chance that you will also find the numerical values and measures like just imagine that you are in a college and the name address and your percentage etc etc are your values and the percentage will be categorized into the numbers which is the measures and if you have a student id which happens to be a number that will not be in the measures that will be in the dimensions but why roll number happens to be a numerical value because the student id will be considered as a unique value and w automatically considers it as a dimension if if you want that to be in the measures no problem in that you can just track it down into the measures and it will lie in the measures from dimensions so that's about the left tabular column where you can see the dimensions and the measures used in your data and these are the filter options these are the page options this is a mark sheet where you can make some modifications onto your chart by making different colors sizes of the charts adding text to your results and adding some details adding some tool tip tooltip is basically something which explains you about the data which you're working with we'll we'll work on that we will see everything in detail no worries on that and now coming on to the right side you can see the show me tab which will help you with the various kinds of charts available that you can work with so you have text tables you have heat maps you can have pie charts you can have single maps and just maps pie chart and side by side bar chart stacked bar chart horizontal bars line graph etc etc you can have scatter plots you can have histogram you can have box and whisker plots and many more now you will be working with various types of charts over here and the best part of tableau is that if you wanted to use a specific chart then it will automatically help you with the kind of data you need for that for example if you wanted to go with text tables you can see that it is providing you the prescriptions over here so it needs one or more dimensions or one or more measures together on the rows and columns in order to you to use this kind of text table kind of uh chart to represent your data with and if you want to go with a pie chart it says you need to have one or more dimensions and one or two measures that is a must if you have these kind of data's on your rows and columns only then you can use a pie chart so this actually helps you out in real time and now let's get started with that data now let's try to identify which is the manufacturer with the highest pricing now when you double click on the sheet you can actually edit it or you can actually right click on that and just select the rename option and you can rename it uh now let's select the or just write in the highest pricing yeah there you go highest pricing is the name of our sheet right now and now let's grab the manufacturer and drop it down under the columns and now let's select the price from the measures and drop it down into the rows yeah there you go you can see that we have the data output on our screen so this particular bar chart helps us identify that mercedes benz has the highest pricing amongst the other manufacturers now you can actually make some modifications onto this chart like you can increase the size of the bars it is automatically selected over here you can just scroll it to the right and left by manually and you can make some changes to the bars and apart from that and apart from that you can even choose an option here which says the sort ascending by sum of price with manufacturer basically it sorts it out so if you select this particular option you can sort it from the least value to the highest value in the ascending order and if you choose this one it will be arranged in the descending order and you'll get to see the highest one on the left and the lowest one on the right so this is how it works and you can see that the first highest pricing manufacturer is diversity spends and the least manufacturing pricing is the infinity and you can see the beamer over here the bmw personally i'm a fan of bmw okay now um and now it's just looking um you know kind of uh plain without some any additional colors or without a vibrant way of representing your data i think you know what i mean so for that you can just drag the manufacturer onto the color option and voila you can see different colors for different manufacturers and this one basically tells you the highest manufacturer or this color basically tells you the highest pricing manufacturer that is the mercedes-benz and yeah and another option is the chart type so basically when you chose the manufacturer and the sum of price the tableau automatically chose the bar chart but you can change that you can just select a line over here and you can see the complete data has been represented in the form of a line and you can even select density and you can select area so this is how you can change the way you can represent your data so automatic was the best one over here so basically the w automatically chose the best way to represent your data which happened to be the bar chart you can even select the shape though and you can make some changes to the shapes so that's how it is now let's get back to automatic again and it's it's got the bar chart again now let's try to create a new sheet and this time we'll be working on the horsepower so which manufacturer offers the highest horsepower yeah so we are on the sheet 2 now you can see that we have named it to highest horsepower and yeah when you come back to this when you can see the name over here you can even edit your table by just double clicking on the name and you can reset some things over here and that's how it is and now when we come back to the horsepower which is the second sheet i think you remember right we are making multiple sheets just so that we can work on our dashboard so now on the second sheet we'll be taking up uh the model name we are going to identify the car which is having the highest horsepower okay those are a lot of cars now just select the sort option and there you go we have the dodge viper yeah dodge wiper happens to be a muscle car and yeah it should be having the highest horsepower in the manufacturing model or what do you say it the basic model without any modifications to it extra modifications so the production model of the viper will be having a 450 brick horsepower that's really huge now we can actually make some modifications since we have different manufacturers like mark and any other manufacturers you can actually categorize the models over here you just need to drag the manufacturer over here and you can bring the manufacturer to the first position and then the model okay another trick i would like to tell you guys is if you wanted to switch the manufacturer with the model then all you have to do is just drag the model and place it on the manufacturer this will automatically switch them okay i didn't place it correctly i hope so when you do it it will actually switch it yeah that's how it's done so we're going to categorize this models based on the manufacturer now let's bring back our manufacturer now let's drag it to the second place and now we have the manufacturer first so you can see that the data got automatically categorized based on the manufacturer you can see we have acura which happens to be the american version of honda so we have integra rltl what happens to be the car or model names so these are the cars offered from acura with the horsepower 255 oh no it's 225 and 210 and 140 so this is actually the tooltip which is giving you the data according to that bar chart and now we have the dodge viper here with the highest horsepower in the production model you know the dodge and the ford are known for their muscle cars with highest horsepower and here we have the merck and mitsubishi nissan and some other plymouth porsche etc etc now we'll go ahead and create our next worksheet so let's name it the fuel efficiency now let's select the manufacturer and the field efficiency on the rows now let's select a different type of chart over here i think you remember the color option and if you close the show me option and then you can see the manufacturer over here now you can just make some changes for it you can actually select a manufacturer and you can either keep only or you can remove it so in in table you have the control set option which will undo the changes you have done you can actually exclude if you want someone to be excluded from the list so i've excluded buick so this was the one we excluded so that's how you can do it so when you press on the tool tip you can see that we'll be having the manufacturer and followed by manufacturer will be having the fuel efficiency provided by the manufacturer so you can see that we have the good fuel efficiency from chevrolet and the considerable efficiency from jaguar so basically jaguars are the luxury cars which provide you the maximum comfort and maximum drive feel so it will actually consume a lot of fuel now let's get back and create another sheet and let's name it as highest resale now let's select the highest resale value and model now let's arrange it see according to that carrera cabrio has the highest resale value that's good let's drag the color and there you go let's have the manufacturer here so that we can have a good idea of which manufacturer has the highest resale value so mercedes has the highest resale value and also we have the model names over here you can remove a model from marks this is the reason why we have multiple cars from single manufacturer so we have all the cars from a single manufacturer if you remove this model from the marks sheet you can just see the manufacturer here now actually we can make some changes to the sizes we have the size option in our mark sheet right so you can just drag and drop the manufacturer on the size and then you have various sizes for the various options and when you come to the rows you can see that we have the sum of resale values basically you can make some changes to it uh you can just select measure and inside measure you have various options of providing average median count minimum maximum so let's go with maximum and now let's try to drag the manufacturer again onto the size and this time you have the different sizes so you have porsche over here mercedes-benz over here so this is how the categorization takes place now let's create a new sheet and understand the filter option now just let's name it as filter and now let's drag the manufacturer so we have the manufacturer in our columns and now uh yeah we discussed that uh the highest pricing is from mercedes right so if we wanted to find the next leading one uh actually you can see it on the screen but just imagine that we have a lot of options rather than the few options which are available on the screen then what if you wanted to find the second leading highest pricing car so in that case you can just make some filters onto it right you can add or remove options using filter so i would like to drag the manufacturer into filter and select all from the list okay and apply now you can just select the filter right click it and edit filter and you can see all the options over here just select ok now let's right click the manufacturer and select the show filter option so that you can have a filter bar on the right side so now you can actually remove some options by selecting them if you just click on the mercedes fence you can actually see the mercedes-benz got removed from the list so you can see after the most dispense the highest pricing is from dodge and lexus so this is how you can use filters let's bring back mercedes-benz again yeah there you go so so far we have dealt with the bar charts and the overlapping bar charts or what do you call it this is the stack pass here i forgot and uh line graphs now we will deal with the scatter plots and pie charts now yeah so for that let's create a new worksheet let's name it as scatter plot there you go okay spelling mistake so when you had to use the scatter plot the special thing about scatter plot is you need to select both the axis that is row and column and when you're selecting the values for rows and columns you need to select the values from this particular segment which happens to be the measures so you'll not be selecting anything from the dimensions so for now let's select the engine size for columns and horsepowers for rows so we've selected the engine size for columns and horsepower for rows so once you have selected the data you can see a dot over here which happens to be the engine size for 70 and horse bar 28 000 for 28 this is some random value now let's take a bit more detail into the scale plot now to know the exact details of all the models and all the engine size and horsepower let's drag the model name into the detail now you have some good uh you know a more representative or the more readable form of data so you can see that we have the highest horsepower engine that is torch viper and the engine size is eight liters and the horsepower offered as 450. now if you have dragged the manufacturer into the details then you can see that we have the manufacturer name as well so the wiper belongs to dodge and if you kind of select the manufacturer into shape then we can actually have different shapes for different manufacturers so you have the shape option over here so you can see that we have various shapes for various makers for example we have the plus symbol for bmw so if you can just select keep only bmw then we have two cars from bmw which happens to be the model 320i and the engine size is around 2.8 liters and the horsepower as 193 brake horsepower and another car we have from bmw is the 323i with the engine size 2.5 and the horsepower 170. now if you want to bring back all the cars the simple step is just press control set and you have all the cars back in here and if you want to highlight a specific car then select the highlighting option and then let's select dutch you can see the dodge cars got highlighted over here so just select dodge viper and then we have dodge durango i don't know how to spell that if i'm sorry if it's wrong and then dodge ram van and we have the dutch enterprise over here so if we hover on to the highlighted parts we have the dodge over there so that's how you highlight it now we have worked on the scatter plot now let's create a new sheet and let's work on the pie chart now i'm just writing pie and it's done so for a pie chart uh you need to select an option and hold ctrl and select another option together and then we can do a pie chart so for that let's follow the steps open show me select pie chart okay uh i forgot to say actually we need to select the dimensions first so let's select something from dimensions okay let's select manufacturer and hold control and let's select some value from the measures so let's select the sales so now open show me and there you go you have the tab so i'm in the pie chart in the tab so we have the pie chart over here now i think we can increase the size of the pie chart so you can just drag it manually and you can see that the pie chart size is getting increased so here we have the manufacturer and it has the sales the ford has the highest sales and uh followed by ford we have dodge and then we have honda and chevrolet toyota so so far we have understood the types of charts you can make the types of options that are color size label detail tooltip etc etc and filters and the show me tab etc etc now we will move ahead and try to understand hierarchy in w so let's kind of make a new sheet let's rename it as hierarchy now we know that the model and manufacturer can be considered as an hierarchy because a model comes under manufacturer so we can use these two from dimensions and use them as hierarchies now let's try to drag model onto manufacturer and this should automatically show me a dialog box on my screen now let's rename it as manufacturer model hierarchy or just let it be as h so that it's a bit more readable now you can see that we have the manufacturer model h hierarchy and inside that we have the manufacturer and model now we can like drag the manufacturer model hierarchy onto columns and we can drag the car sales into rows and we have the hierarchy values over here let's rearrange them and now if you press the plus option it's really mind you don't know how to expand the screen let's try control plus r shift plus it's not working so i think you can see the my new plus option over here now let's try to press that plus option and there you go you have these sales according to the manufacturer and the models and that too in hierarchy let's remove the car sales and try to put in the horsepower over there yeah you can see the horsepower of each and every car which is categorized according to the uh manufacturer so infor we have various types of cars available and similarly in toyota mercedes-benz chevrolet mitsubishi etc etc so that's how the irrq works now i hope we had a sound understanding of how to create various types of charts and we have the filter option scatter plot pie chart hierarchy everything discussed so far i think you have a brief idea how to work with w now let's go through an example of dashboards now let's rename this dashboard as car dashboard now dashboard is no rocket science the only thing you do is just select the charts you've worked on and drag them onto your dashboard that's all now let's select the scatter plot and drag it onto the chart and now let's try to drag the horse bar and now the fuel efficiency so you can see the horsepower and fuel efficiency and highest number of sales and the horsepower compared to engine size all together on one dashboard so you can see the dashboard name over here which is a car dashboard now you can have some options over here like you can download the dashboard image and much more you can even make multiple dashboards just like we made the worksheets and then you can interconnect the dashboards and you can work multiple operations on multiple dashboards i hope you had a good understanding of tableau in taboo tutorial for beginners and now let's get back to the presentation so today we'll be dealing with the tableau project so the first data set that we will be using for the tableau project is based on covet 19 data followed by that we'll have another project based on the airline data and finally the third project will be based on space missions data now let's begin with our first project so in this first project we'll be dealing with the covert 19 data set and using that data set will be getting some insights so what are those insights those are what are the total number of confirmed cases in different nations what are the total number of recovered cases in different nations so we'll be using the map chart for these and we'll be finding out the insights about how are the cases going on in the current situation or in the current date or year followed by that we'll also look into the insights of the confirmed and recovered cases in india as well followed by that we'll enter into the next query where we'll find out the trend line of code 19 in the international level like how it started how is it going on and moving forward will create a group of indian states and we'll find out the covert heads there and then we will discuss about the death rates so highest death rates at international level and the least death rates in the international level then we'll enter into the next segment where we'll find out the variation in covert 19 cases around the world and then finally we'll discuss the future of covert 19 in the international level basically we'll create a trend line which will give us the forecast levels of the covert 19 like is it going to increase or is it going to decrease or what's going to happen in the near future so i hope i made myself clear with the queries or the insights that we're going to take from the covert 19 data set using table u so without further ado let's get started with the w so we are on tableau right now so we'll be using an excel data file so we'll be using the covert 19 data file so this particular data set is available on kaggle and if you don't find it there don't worry we'll be attaching that particular data set in the description box below you can use that as well now let's just select open to get connected with that particular data so you can see that we just got connected with that data and there will be some minute errors in the data or there will be some problem with the data which the table you might identify and when it identifies something messy with the data it will show you an option maybe you might want to use the data interpreter so i prefer using that so whenever i see that particular option on the left hand side i better use it for the safer side for being for being on safer side with the data and let's also select these not a problem yeah so the data got clean now you can see that over here so to do that you can also check the review results so when you click that review results option then you'll get into this particular excel document which will help you with the changes made to that data set so you can see that the orange color one sees the data is interpreted as column headers or field name and the green box suggests you that data is interpreted as values in your data source and now you can see that there you go so now we'll get back to w now you can see that the data has been interpreted successfully by the w and everything is uh as expected by the table every every data element in the data set is as expected by the table and it's really fine now now we'll check the columns what we have in our data set right over here so we have the serial numbers observation dates province state and the country or region last update and confirmed death recovered so basically these three columns will be telling us the confirmed cases in that particular region country or state and the debts happen in that region country of state and recovered rate and the last update when was the last test done the latest tested done and in which region and what's the observation date what's the observation results on that particular date and the serial numbers etc etc so we have the clear understanding of our data set now let's get started with the first sheet what we have over here so according to our first query we had to find out the total number of confirmed cases in different nations so for that we might want to select the country or region and then the confirmed from measures so for that we'll be selecting the map chart for this so that we have the data shown in a more appealing format so now we have the blue color of map on a screen right now where the darkest color shows the maximum number of cases confirmed and the lighter ones represent the lower number of cases confirmed now let's let's make this look a little more interesting so for that we can select the edit color options and inside that let's select the red to green diverging yeah this is it red to green white divergent and uh uh as you can see the colors are a little opposite right now so we want the greener one in the lower side and the red colored one on the higher side this should be good so let's select okay and apply and okay so you can see that the red color now represents the highest number of cases and a lighter red one here you can see the a little touch of red which shows that the india's got some good amount of cases as well and in the brazil and et cetera et cetera so even russia has a little light green so this shows it also has some good amount of cases not not completely green though yeah so this is how it looks now let's rename the sheet as confirmed cases at the international level now according to our second query we are supposed to find the total number of recovered cases in different nations so now let's create a new sheet for that now for that we'll be selecting the country or region and then we'll be selecting the recovered and uh hover over to the show me icon and let's select the mac for that now you can see that we have a lot of recovery happening in india so according to the stats we get to hear that the virus which we have in india is a little you know kind of harmful than comparatively what we had in china and other states of the world or the other nations of the world so yeah we have a good recovery rate in india now let's rename the sheet as recovery recovered cases international level yeah so i'm naming these sheets separately because we'll be using these sheets to create a dashboard at the end now let's get into the third query what we have right now is find the total number of confirmed cases in india and what are the total number of recovered cases in india so for that let's create a new sheet and let's select country or region and confirmed now we'll be selecting the text table and we have the complete data set right now we have all the nations over here so what we are looking for is just india so for that now we'll drag the country or region into filters and inside this you can see we have an option of selecting india now let's search for india g h i so we have india over here let's select apply and okay so we have the total number of cases in india now we can drag the state of province into a rows add all members so in india we have all the states and so all the states have their own confirmed cases so this is the total confirm state or confirm count in india let's rename this sheet confirmed cases in india similarly let's find the recovery cases in india let's create a new sheet for that rename it as recovery cases in india so now let's select the country region recovery and then let's close the show me icon and now let's drag the control region to filters then none select india apply okay and let's drag the state of province here at all numbers yeah so you have the text chart here which represents the total number of recovered cases in india according to the state wise now yeah this looks okay but we can make it look a little more appealing so that it's it's more you know visible and understandable readable so we can make that happen so let's make a duplicate of this and recovery cases as well now i would like to change the confirm cases in india into a pie chart which looks a little bit more readable and understandable let's select the entire view so that we have a bigger pie chart and a little bit understandable or readable let's increase the size a little bit and let's select the label and select the show mark label so that we have all the numbers over here we can even select the uh province of state and drag it into detail so we have the state's name as well or should we tag it into label yeah now the recovered into label again yeah there you go we have this state and we have the confirm number over here so this is how we can make the data look a bit more appealing and understandable so we can see that maharashtra has a larger number of confirmed cases it's the biggest state of india so maybe yeah that's true and now we'll get back to the duplicate sheet of recovery cases in india and now let's make it look a bit more appealing by changing the way the data looks so for this we can select the packed bubble option now we can see the bubbles which show the uh recovery states happening in the indian states or the recovery cases so you can see that everything is looking in blue color a bit difficult to understand so for that let's drag the province or state into color so that we can have different colors for different states yeah now this is good we have the country name and state name this is fine now we can make it a bit more readable by dragging the recovered icon into or the recovered pill into the label so we have the count of recoveries happening in that particular state and that particular country now it's a bit more readable now we have maharashtra at the leading place we have a good recovery in maharashtra yeah that's fine now let's get back to the presentation mode and see our next query so can we forecast the trend line of covert 19 here so how it started how is it going on so we can do that let's get back to w again so let's create a new sheet we have the new sheet over here let's rename that as trend line yeah the sheet got renamed now let's select the observation date from the dimensions since you're making a trendline so let's keep it observation date or you can even select the last update let's go with the last update now let's select the confirmed fill from measures let's select a line chart or we can do that from here as well okay so we're not getting the line chart so there might be some problem with the date format over here so we have to change the data type of so i think this might be something with the date yeah let's select the date pill and change the data type to date or date and time from string so you can see we had a string first so now let's change to date and time now we'll be getting a proper trend line so now we have it according to the year so we can make it according to quarter and uh even even even in the form of months and so if you see this a little bit readable you can keep it that way or you can even change to days so yeah i think there is some problem with dating time value so let's keep it in the form of months it's it's more readable in one screen so yeah it's good let's remove this so we have the month update now let's go to analytics to create a trend line and you can select the trend line and drag it over here and select the linear option so you can see here we have the trend line over here which reach the r squared and p values and confirm and we have a formula for that so basically tabulate creates a formula to create a trendline so which is 5.280 exponent to the power of 8 into month of last update so very pretty pretty complex formula yet understandable so this is how you create a trend line so according to the trends we have january february the quartus q1 q2 q3 q4 and this is the first month of january so here it is so in in january we find one okay this is in billions maybe yeah maybe even trillions who knows but but based on the data we have in the last year we have a decrement of the confirmed cases in january so it's basically indicating that corona yes basically are slowly decreasing that's a good sign now now let's try to find out the trend line for india let's duplicate this so for that let's drag the country into filters we have the filter option and let's select all no no not all we might want to select uh the indian icon yeah let's select apply okay so now we have the trend line for india let's kind of rename it yeah even even you can see a gradual drop of corona in india as well so the number has decreased in india as well in the earlier year we had a lot of cases uh above 30 crores now we have nearly 20 crores that's a good sign in india as well now let's get back to the presentation mode and try to select the next query so according to the next query uh can we group indian states and find covert 19 hits yeah we can do that now let's get back to tableau for that let's create a new sheet and let's rename it as grouped so the sheet got renamed now we're going to select the country or region or province now for that uh you can see the create option over here now inside that let's select the group now we have to create a group of indian nations so select andaman and ecobar hold control select andhra pradesh now let's select a couple of states we know which are in india arunachal pradesh assam don't forget to hold the ctrl key for this or else the options might vanish we have bihar we have chandigarh we have chapter we have dadar and nagar yeah we are going to just select a couple of uh states uh just to show how um group can be done so fetching all the states in this particular column would be a little difficult or we might even miss a few we have got we have haryana we have islamabad we have karnataka we have kerala the dark dream we have madhya pradesh maharashtra nagaland we have punjab we have rajasthan we have tamil nadu with telangana we have the pradesh we have west bengal and let's rename the group as indian states group let's select apply and okay so uh after selecting the apply option and clicking ok so we can have a new pill in the dimensions section that happens to be indian states group so what we're going to do is drag that bill into detail option so that we can have the results on our screen so there you go the states what we selected are right over here all the jammu kashmir and punjab maharashtra gujarat et cetera et cetera and our lakshadweep and the andaman and nicobar islands right so we have all the states of india right on our screen okay um let's expand it a little bit scrolling on tableau is a little bit difficult i don't know how to select the default option for the screen yes um we can see these states i don't know where this crawler is at yeah we can always undo what we did in w so that's the best part now let's drag the state spell again so that we can have a perfect map in the screen right now yeah i would like to not to mess with it again it's it's pretty good right now let's keep it as it is now let's quickly get back to our presentation and check out our next query so find the highest death rates at international level so we we are basically going to find which nation or the country has the highest death rates and which is the country with the least amount of death rates so which is the safest country now let's get back to tabalee now we're not going to mess with this particular sheet let's create a new sheet let's rename the sheet as highest death rates international i n t l let's enter so the sheet got renamed successfully let's drag in country and let's drag and confirm cases so we have a map over here so w basically kind of selected the map as default we can drag the depths and now we can actually change this to a text chart now let's drag the measure names into rows so we have a little bit more you know sorted kind of data so you can see we have the country cases over here and that trades here now if we kind of sort it in the descending order yeah so the uh order is being changed now so we have uh so we have our charts processed by tableau for a better visual so our chart got rearranged or ordered in the descending order so with that we have the highest you know uh deaths and confirmed cases in us so we can even do that using a parameter where you can create the top 10 or top five nations with highest confidence values so for that you can drag both oh no you need to create a parameter i think it's not required over here let's continue with the next sheet or you can just simply duplicate this since the data set is a little huge it takes a little bit of time now let's rename this yeah now let's rename this sheet it's still taking a little bit of time yeah now i think we can rename it least death rates so now for that we're gonna rearrange it in the descending order i'm an ascending order so yeah after sorting and changing some layouts we have the least number of uh cases or death rates in the country called makkah where we have least number of deaths and least number of confirmed cases so with that let's move into the presentation mode again and in the presentation mode we have our next query that says can we find the variation in code 19 cases around the world so for that let's create a new sheet again if getting your learning started is half the battle what if you could do that for free visit skill up by simply learn click on the link in the description to know more so after changing some arrangements or by making an ascending arrangement and changing the layout or the orientation and everything we have our final result which states that we have the least number of debts and confirmations of covert 19 in the country of afghanistan so yeah so we have the predictable sorted arranged data over here on the screen now let's get back to the presentation mode and in the presentation mode the next query that we have to deal with is can we find the variation in cobin 19 cases around the world yeah we can do that so let's get back to w and create a new sheet let's rename the sheet as a variation of c one nine yeah it's done so to find out the variation of covert 19 we might want to use the boxes and viscous chart let's select the country region pill from dimensions and confirm from measures let's arrow to the show me tab and select the box and whisker plot yeah so you can see that we just have one box of whisker over here when you see something like this happening on your sheet then directly head over to analytics and uncheck the aggregate measures so we have this kind of visualization maybe we forgot something so we've got the country or region to be placed in columns so when you place it in the columns section then you find out all the countries and the variation of kubernetes in their region now let's um sort it in the descending order so that we can find out the maximum variation which is happening in france so of course there are less number of confirmed cases but there is a lot of variation which states that they have something wrong with the climatic conditions or the weather conditions there yeah we have a larger confirmations in our larger cases in u.s but there is some uh some data which shows that france is leading in some variation yeah so um since we're calculating the variation of the confirmation of covert 19 presents we have france in the first place where it shows that there is a lot of variation in the confirmed cases in france rather than u.s yeah that's how we can find the variation of presence of covert 19 in a particular country so with that let's move into the next query so the next query is can we forecast the sheet of future and reference of code 19 presence yes we can do that let's get back to w for that let's create a new sheet and rename it as forecast of co with 19 presents so the sheet got renamed successfully now we'll select the observation date from the dimensions and confirm fill from measures so we'll use them drag it to columns and the confirm from yeah now we're going to change this okay there is something wrong with the observation date for that let's select the observation fill and change the data type to date yeah so far so good now let's select this to day oh we can change that to here now let's select four cat option yeah so this is how it's going to be so in the year of 2020 we had the confirmed cases around this number which is 767053464 so which is nearly 76 370 lakh and in the 2021 the number got a little decreased which is 17 130 lakh cases and uh in the end of 2022 which is the forecast we can see there is a little more drop so it's a good sign that the covert nineteen is getting decreased so this is the forecast of the covet 19 presence in india so we can change the path to a stepped one the line is okay the line is pretty good no worries on that so basically we finished the queries on our presentation mode so yeah if we get back to the presentation mode so all the queries on the covet 19 data are finished now let's create a dashboard yeah we have the dashboard right now so we can change the layout of dashboard let me increase the width to 1320 and decrease the height to 70 or 760. so we have the entire screen right now now let's drag in the confirm cases of international level and the recovery cases of the international level yeah now we have it okay or let's keep it in the top and that in the bottom the trend line of code in the international level and the highest death rates in the international level it takes a little time it's still taking a little bit more time i don't know what's wrong okay it should be done in some time let's wait it's basically taking a lot of time because we have a lot of data in that particular sheet let's kind of change that a little now let's change the sheet to or we can just remove this from the dashboard and select the least depth rate or the top 10 least death rates so we have sheet right over here we have the top 10 ones only here yeah this is good so this is how we can have the dashboard and now let's create another dashboard for indian results so again let's uh change the dimensions of the screen yeah it's pretty good now let's take the confirm cases in india and drop it over here and recovery cases in india and drop it over there and trend lines in india over here and indian states in the forecast somewhere over here and if we get back to the dashboard one we can even add the forecast data or the variation data somewhere over here and we can always change the height so that it's a bit more visible so we can rename the dashboard c 1 9 international dashboard and this one has c one nine indian dashboard yeah so with that we have finished the first project based on the covert 19 data set now we'll continue with the next data set that is the airline data set so now we are in the second project and the second project is about the airline data set and in this particular data set we're going to take the insights which are as follows what are the total number of flights which are taking off in a day from the san francisco airport and followed by that we have the next query which reads out find the busiest day of san francisco airport we'll be finding out the top five busiest air days in the san francisco airport and followed by that will also find what are the total number of flights per day in a month then we'll find out what are the top 10 busiest flight routes then we'll find out what are the top 10 longest flight routes from san francisco airport then we have to represent the flights flying outside the san francisco towards different parts of the world using a map chart so these are the queries that we'll be executing in our second project without further ado let's get back to the w so now we are back on the w dashboard so let's select our data set for today so our data set is somewhere here yeah this is the air travel data set we were looking for now we got our air travel data set loaded onto w so remember i said about the interpreter i'll select that and show earlier okay let the query execute yeah so the interpreter query got executed now the data has been cleaned we can review the results by clicking on review results option over here we have another query executed now basically this query will take us to the microsoft excel sheet where our claimed data is readily available for us there you go we can see that the red colored data is the data that is interpreted as column headers or field names the green color one is the data interpreted as the values in your data source so it looks something like this so we have our data fine over here just looking fine now when you come into the root column you have san francisco to the other parts of the world for example we have los angeles here etc etc but we don't have a separate field for origin and a destination so what we'll be doing is we'll be splitting this particular column uh right away here so let's navigate to the last column which will show us the root so you can right click this and select the option of slit which will basically split it into two halves which will give us the from destination or the origin of the airplane and to or the destination of the plane so from to or the origin destination fields we have right now over here you can see that so far so good so let's quickly begin with our worksheet now we are on the worksheet right now so what was our first query so our first query was to find the total number of flights in a day so for that we have a simple step so basically we'll have a particular number of rows right for the data set what we've selected we will have some thousands of data sets so each and every row is actually a flight so what we will do is just create a calculated field and just name it as number of rows okay since we are trying to calculate the total number of flights let's you know kind of uh not name it as rows instead we'll name it as flights and inside the health related field just write one and it should be done so you can see the number of slides just over here just hover down the text and we'll have the number over here so this is the total number of flights per day which takes off from the san francisco airport let's kind of increase the text size so that it's a bit more visible yeah that should be it uh let's rename the sheet from here i would i i would do the renaming from here because it's a little simple total number of flights yeah that should be it now let's get on to the presentation mode again now let's uh you know execute the second query find the busiest day at san francisco airport so to execute the second query uh let's just simply duplicate the sheet and rename the sheet as um busiest okay we can actually schedules of flights or not schedules of flights number of lights or we can rename this as flights taking off so when we get the count of flights taking off then we can actually find the date which was really busy like the date with the maximum amount of uh you know flights taking off that would be the busiest day so the data type is date by default that's great now let's drag it to columns now the sum of numbers at this place analysis let's uncheck this to get a map let's make it by month or okay we don't need this we don't need this we all need this as well now we have a chart over here let's change it to scatter plot maybe yeah so we have the chart no worries on this caterpillar thing it's it's really a scatter plot and don't know what is on that so right now we need to find out the busiest days so for that we might want to drag the date into filter and let's select the individual dates select next and inside the top we have the oh yeah we need to select by field and now we have the top 10 number of lights on yeah we need we need the top 10 flies so let's select apply we needed top one but uh why not top then you will select top 10 for that now we have the scatter plot on my sheet right now so let's kind of uh arrange it in the descending order this shows the highest number of flights or okay we need to change this value to sum yeah there is some so uh yeah i got to know where we made a mystic so inside analysis we were supposed to aggregate the measures so that we can get the sum of number of lights now we have the total number of flights now let's quickly uh arrange this now we have the three thousand one hundred sixty six three thousand two hundred thousand two ninety five yeah so three thousand 3295 happens to be our you know busiest day in the year 2020 that is the sixth march which had the maximum number of flights taking off so we can actually make a set of these the set of these which happens to be in the march so much happens to be the busiest month for san francisco airport so with that we have finished the second query now let's create a new sheet for our third query let's get back to the presentation and the third query it reads that what are the total number of flights per day in a month so for that let's get back to w let's try to rename it total flights in a month done so for that let's select date and drag it to columns and let's make it to month let's remove this let's remove this let's remove this as well now let's check it to day and now number of flights so automatically we have a line chart and we have the flights taking off from march 1st to march 31st which happens to be the busiest month for san francisco airport now let's just take the show mark label so that we have the number of flights taking off every day so as we got the result in the previous sheet 290 or 300 3295 flights on the date of sixth march or is the third march maybe yeah that happened sixth march that happened to be the busiest day of uh san francisco airport let's get back to the presentation and check the fourth query so the fourth query reads what are the top 10 busiest flight routes for that let's get back to tableau again let's rename the newly created sheet busiest routes now the uh sheet is being replaced or renamed now to find out the top busiest routes we need a calculated field to remove the effects of san francisco airport first so clinton create a calculated field and we can name it as busiest route pc and now inside the calculated field we need an if condition then if route 1 split 1 is equals to sfo then route 2 split two else route one and yeah the calculation is valid let's apply and okay now we have the newly created calculated we field somewhere here now we'll drag that into rows and now we'll drag the number of flights to columns so there we go we have the bar chart over here let's um you know rearrange it in descending order so that we get the you know descending order now we needed the top 10 or top busiest routes with that let's drag busy into filters select top and by field we have top 10 let's just select apply and ok and we have the top busiest routes from san francisco airport or sfo now let's get back to the presentation mode and in the presentation mode the next query is which are the top longest flight rules from sfo so to find out the longest routes we'll create a new sheet and rename it as our busiest no not busiest longest longest routes yeah the sheet is renamed and you can see that we have geometry coordinates 0 0 0 1 1 0 and 1 1. so these z okay not 0 1 1 and 1 0 coordinates basically provide the origin information and 0 0 and 0 1 provide the destination information so we'll be creating a calculated field for that now let's create a calculated field so let's rename the calculated field as origin and inside the origin we'll make use of make point and inside make point we'll write geometry coordinates one one and geometry coordinates we'll need the geometric coordinates one one and geometric coordinates one zero separated by comma and done so we have the origin now let's create another for destination we are creating a calculated field destination and inside destination we are going to use the same make point and geo metric coordinates 0 0 comma geometric coordinates 0 1 and select apply ok now the origin and destination are created now we need to create another calculated field for distance so we'll write it as distance and inside that we'll use the distance function and we'll write origin comma destination and will represent the distance who using kilometers and select apply okay now we have the newly created distance measure in the measure section now we'll drag the busy into columns and uh distance into rows okay uh we made something oh there's no problem we can actually change the orientation and now let's rearrange it in the form of descending order now we have the um distance sorted in the descending order but there is a small change we have to change the sum to average so once you change that you want to arrange it again now we have the vlr bangalore as the farthest airport from sfo yeah now we might want to drag the crazy into fill this again now we have the top ten apply okay so we have the top ten longest routes from sfo so with that we have uh finished our fifth query let's get back to presentation mode and the sixth query represent the flights flying outside sfo towards different parts of the world yeah that can be done let's get back to w again now for the sixth query let's create a new sheet let's name it as map flights from sfo okay so for that let's select the latitude and longitude and select a map so we have the map right here now let's change that to map yeah it's in the map section by default let's create a calculated field called lines so we're basically using lines to represent the flights taking off from sfo so i'll name it as line or we can name it as flights line okay and inside the calculated field let's type in make line and so inside the field let's make use of make line function and inside that let's write an origin and separated by comma destination and the calculation is valid apply ok now we have the newly created flight line over here now we'll drag that flat line to detail now once we drag that flight line to the detail we have the lines our flights taking off from sfo to different parts of the world now we can make it look a bit more appealing or more informative by dragging the roads or yeah into detail so we have the details of roots and we can even drag the distance into detail so when we hover over to the line we'll have the root and the distance as well yeah so that's how it is done now we're basically done with all the queries now let's create a dashboard so now let's um you know kind of arrange the dashboard size convenient to our monitor so i'll increase it to 1320 width and decrease the height to 760. so that's the proper size what i was looking for now we'll drag the details into the sheet longest truths we have the flights taking off busiest routes longest routes and total flights into here now it looks more readable fine so we have the busiest routes we have the longest routes we have the flights taking off and the month of march the busiest month was the march and the busiest day was 6th of march i don't know what was so special on that day if you know it please let me know in the comment section below and yeah so totally we created a dashboard now let's rename the dashboard as sfo flight data dashboard and we are done so we are done with the second project now let's get back to our presentation and let's check the last project that happens to be the space missions data set so now we are in the third project which is based on space missions data set so using this particular data set we're going to get some insights which are based on the queries on my screen right now so we're going to find out what are the average temperature details of the launch sites what are the average wind speed details of the launch sites what are the average humidity details of the launch sites so we need all these to uh you know before launching a satellite or a rocket into space everything needs to be in ideal condition so followed by that we have what are the different varieties of laundry vehicles used by different companies so there are a lot many companies you are from government sector where you're from private sector for example uh usa military satellites belong to garment and private satellites like um spacex yeah and few others next we have what is the mission status of the company so we have a list of satellites launched already right so we need the mission status of that particular satellite is it a successful launch or was there some failure record or something like that next at the last query we have the track records of launch sites so what are the track records so what are the successful launches what are the failure launches what are the satellites launched by different companies etc etc we'll have a complete track record of that of all the launch sites which are available in our data set now without further ado let's get back to taboo and start the project so we are on tableau now we're going to extract the data set so the data set we need is the space missions data set you can get this in the kaggle or you can even have the access to this data set from the description box below select open to open the data so yeah the data got successfully loaded again use the interpreter and it's a good habit of using the interpreters to clean your data and make everything understandable or look understandable show all the asses everything is fine so we're good to go with the data set what we have in our tableau right now now with that let's get back to the first sheet now let's check the first query that we have in our presentation what are the average temperature details of launch sites so for that let's create a new sheet yeah it's created rename it as avg temperatures or launch site temperatures so now we need the launch site and select the temperature and hold over to the show me tab and let's let the bubbles chart now you can see the temperature is in the sum but we don't need the sum here we need to change that to average now we have the average temperatures of the launch sites now let's kind of select label show marks here so we can do one more thing we can drag the temperature onto the label now we have the temperature here now let's again change the measure to average now we have the average temperatures of the launch sites and fahrenheits yeah that's pretty well now let's get back to the presentation and the next query is what are the average wind speed details of the launch sites let's get back to w again let's create a new sheet launch site wind speeds now let's drag the launch site into columns and wind speed from measures into rows and you can see automatically we have a bar chart but to make it a little bit more readable let's select the boxes and viscous chart yeah you know what to do now go to analysis uncheck the aggregate measures options and let's drag the launch site again onto columns now we have the different box and whiskers for different sites so let's kind of arrange it yeah so the wind speeds at uh kennedy space center are here 20 miles and 23 at vandenberg and marshall at nine yeah so this is the wind speeds at different launch sites now let's get back to the presentation mode and now we have to find the humidity details of launch sites so let's get back to tablet and we are back on tableau let's rename it humi dt launch site now let's select the repeat now let's select the launch site and humidity then a pie chart the pie chart is really small so we can select the entire view now we have the sum of humidity but we need the average humidity and now let's drag humidity onto label and launch site to label now we have the detailed humidity now we need to select the measure to average again and here to average again yeah so we have the humidity percentage of launch sites on the pie chart over here so with that we are done now let's get back to presentation again now our fourth query which states that what are the different varieties of launch vehicles used by different companies for that let's get back to tableau now let's create a new sheet launch vehicle details yeah now this query is pretty straightforward select company and vehicle type and we should be done so there we go we have the company name and vehicles used for the launching of satellites process now let's get back to the presentation mode let's select the next query what is the mission status of companies now let's get back to tableau let's create a new sheet and rename it as mission status now we are back on tableau now let's select the company drag that to columns and mission status to columns and well select one [Music] parameter from measures so that we can get a good bar chart side-by-side bar chart and now we can drag the company to color so that we can have different colors for different companies so we have the mission details so spacex found a maximum success in the recent days and little failures and yeah boeing fun good success as well and some failures so these are the mission status of different companies and different satellites as well so we have even u.s air force here faced some satellites here some failures and some satellites it's okay so now let's get back to presentation mode now the sixth query is track records of lunch sites we had the payload as sum so we change it to count distinct count so now we have a better observation of failures and successes over here so as we discussed in the sixth query now we need to find the track records of launch sites now let's create a new sheet rename it as track records and now let's drag the company to columns and mission status to columns again and now let's drag the launch site yeah i think we might want to drag the mission status to rows yeah let's create click on text now let's drag the space mission scan to color and space mission counter labels let's use this one yeah now we have the um state stats or the track records of different space centers or launch sites and we have the failures and success rates over here yeah so basically we have done the last sheet or last query executed now let's create a new dashboard as we always do change the resolution according to the monitor we have so i'm gonna use 1030p and height as 760. now let's drag the sheets so we have the launch temperatures launch wind speeds and launch site humidity at one place now the launch vehicles used mission status and the track records so we'll kind of drag it here and this one over here this little bit over here and this one over here so now we can actually you know select the track records of cape carnival we have the site temperature we have the site humidity we have the site wind speed and the track records of that particular site and launch vehicles launched mission status everything on one single dashboard so that's how you make use of dashboards in real time with that we have reached the end of this w for data science tutorial i hope it was interesting and informative if you have any queries then please feel free to leave them down in the comment section below our team of experts will be happy to hear it from you and resolve all your queries until next time thank you stay safe and keep learning [Music] hi there if you like this video subscribe to the simply learn youtube channel and click here to watch similar videos turn it up and get certified click here you

Channel: Simplilearn

Views: 12,914

Rating: 4.9661016 out of 5

Keywords: tableau for data science, tableau for data science full course, tableau projects for data science, tableau full course, tableau full course free, tableau projects with solutions, tableau projects for practice, tableau training for beginners, tableau tutorial, tableau tutorial for beginners, data science, data science project, data science tutorial, data science course, data science projects for beginners, tableau and data science, simplilearn tableau, simplilearn, 2021, dashboard

Id: C116gs2Y1nU

Length: 134min 58sec (8098 seconds)

Published: Mon Mar 22 2021