title
Tableau for Data Science and Data Visualization - Crash Course Tutorial

description
Learn to use Tableau to produce high quality, interactive data visualizations! Tableau can help you see and understand your data. Connect to almost any database, drag and drop to create visualizations, and share with a click. 🔗Tableau Public: https://public.tableau.com/en-us/s/ 🔗Kaggle dataset: https://www.kaggle.com/c/titanic/data Find more data science information: https://www.velocityanalytics.io/ Tutorial from Velocity Consulting. Check out their YouTube channel: https://www.youtube.com/channel/UCjWUocSV-slQnC64nQ1vVhQ -- Learn to code for free and get a developer job: https://www.freecodecamp.org Read hundreds of articles on programming: https://medium.freecodecamp.org

detail
{'title': 'Tableau for Data Science and Data Visualization - Crash Course Tutorial', 'heatmap': [{'end': 668.946, 'start': 635.622, 'weight': 0.714}, {'end': 829.089, 'start': 721.915, 'weight': 0.761}, {'end': 1294.647, 'start': 1271.835, 'weight': 0.737}, {'end': 1467.155, 'start': 1443.157, 'weight': 0.742}], 'summary': 'This crash course tutorial on tableau for data science emphasizes its role in efficient data visualization, data exploration, and reporting, covering topics such as tableau public installation, analyzing titanic dataset, and creating custom age bins and dashboards in tableau, equipping users with skills for efficient data analysis.', 'chapters': [{'end': 297.002, 'segs': [{'end': 59.953, 'src': 'embed', 'start': 34.085, 'weight': 0, 'content': [{'end': 42.612, 'text': "but generally you're going to have the data collection, data exploration, sort of the data wrangling, data munging stage,", 'start': 34.085, 'duration': 8.527}, {'end': 50.059, 'text': 'where you have to pull everything together and clean it for modeling, and then the next step would be modeling, validation and then reporting.', 'start': 42.612, 'duration': 7.447}, {'end': 59.953, 'text': 'So the way I use Tableau primarily is in the exploration phase and then in the reporting phase.', 'start': 51.707, 'duration': 8.246}], 'summary': 'Data processing stages: collection, cleaning, modeling, and reporting. tableau used for exploration and reporting.', 'duration': 25.868, 'max_score': 34.085, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/TPMlZxRRaBQ/pics/TPMlZxRRaBQ34085.jpg'}, {'end': 130.389, 'src': 'embed', 'start': 84.955, 'weight': 1, 'content': [{'end': 91.319, 'text': "Because if you feed bad data into this model, you're just garbage in, garbage out.", 'start': 84.955, 'duration': 6.364}, {'end': 96.182, 'text': 'So being able to explore the data, I find, is really helpful.', 'start': 91.399, 'duration': 4.783}, {'end': 100.884, 'text': "And sometimes that's really all you need to know if you should move forward or not.", 'start': 97.562, 'duration': 3.322}, {'end': 107.735, 'text': "you're trying to look to see if there's some kind of a relationship between variables.", 'start': 102.526, 'duration': 5.209}, {'end': 113.024, 'text': 'Sometimes a quick exploration in Tableau, a nice visual will help give you that.', 'start': 108.837, 'duration': 4.187}, {'end': 114.948, 'text': 'And then also in the reporting side.', 'start': 113.605, 'duration': 1.343}, {'end': 122.585, 'text': "So, once you've built your model, you validated it and you want to be able to share your results with others.", 'start': 116.161, 'duration': 6.424}, {'end': 124.807, 'text': 'Tableau is also ideal for that.', 'start': 122.585, 'duration': 2.222}, {'end': 126.208, 'text': 'They have great reporting tools.', 'start': 124.827, 'duration': 1.381}, {'end': 130.389, 'text': "It doesn't matter really what kind of organization you're in.", 'start': 127.829, 'duration': 2.56}], 'summary': 'Exploring data is crucial for model accuracy and decision-making. tableau aids in data exploration and sharing results efficiently.', 'duration': 45.434, 'max_score': 84.955, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/TPMlZxRRaBQ/pics/TPMlZxRRaBQ84955.jpg'}, {'end': 223.579, 'src': 'embed', 'start': 175.848, 'weight': 2, 'content': [{'end': 185.691, 'text': 'tens of millions of rows billions of rows potentially and being able to throw this stuff quickly into a tool like Tableau and look at it really really helps a lot.', 'start': 175.848, 'duration': 9.843}, {'end': 190.132, 'text': 'So here you have Tableau Desktop and then the server version.', 'start': 186.811, 'duration': 3.321}, {'end': 195.433, 'text': "We're gonna be using the desktop version today, specifically Tableau Public, which is free.", 'start': 190.312, 'duration': 5.121}, {'end': 197.394, 'text': 'You can download it for free from their website.', 'start': 195.633, 'duration': 1.761}, {'end': 200.892, 'text': "And that's just the software that you download to your computer.", 'start': 198.749, 'duration': 2.143}, {'end': 205.418, 'text': 'And then the server version actually is within the browser.', 'start': 201.453, 'duration': 3.965}, {'end': 212.428, 'text': 'You can create charts and dashboards and then upload that to the server for consumption throughout your organization.', 'start': 205.478, 'duration': 6.95}, {'end': 220.697, 'text': 'So the interface here for Tableau Desktop is really just drag and drop.', 'start': 216.434, 'duration': 4.263}, {'end': 223.579, 'text': 'It reminds me of a pivot table in Excel.', 'start': 220.757, 'duration': 2.822}], 'summary': "Tableau allows quick analysis of millions of rows, with a drag-and-drop interface similar to excel's pivot table.", 'duration': 47.731, 'max_score': 175.848, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/TPMlZxRRaBQ/pics/TPMlZxRRaBQ175848.jpg'}], 'start': 8.831, 'title': 'Tableau for data science', 'summary': 'Discusses the role of tableau in data science, emphasizing its usage in data exploration and reporting, enabling efficient data visualization and sharing of results, with a focus on identifying relationships between variables and ensuring data quality.', 'chapters': [{'end': 175.848, 'start': 8.831, 'title': 'Tableau for data science', 'summary': 'Discusses the role of tableau in data science, emphasizing its usage in data exploration and reporting, enabling efficient data visualization and sharing of results, with a focus on identifying relationships between variables and ensuring data quality.', 'duration': 167.017, 'highlights': ['Tableau is primarily used in the exploration and reporting phases of the data science workflow, enabling efficient data visualization and sharing of results, with a focus on identifying relationships between variables and ensuring data quality.', 'The exploration phase in Tableau allows for looking at different variables, data distribution, detecting outliers, and identifying relationships between variables, aiding in determining the quality and usability of data.', "Tableau serves as an ideal tool for reporting and sharing results, offering great reporting tools and the ability to share workbooks for others to view, regardless of the organization's type.", 'Tableau is described as a business intelligence and data visualization tool that aids in making sense of data, especially when dealing with large datasets, offering a more efficient and feasible approach than manually inspecting millions of rows of data.']}, {'end': 297.002, 'start': 175.848, 'title': 'Tableau desktop introduction', 'summary': 'Introduces tableau desktop, a tool that allows easy visualization of large datasets with drag and drop interface, and also explains the dimensions, measures, and filtering functionalities. tableau public, a free version, is used for the demonstration.', 'duration': 121.154, 'highlights': ['Tableau Desktop enables visualization of large datasets with drag and drop interface, allowing easy creation of charts and dashboards for organizational use.', 'Tableau Public is a free version that can be downloaded from their website, providing the same functionalities as the paid version for personal use.', 'The interface of Tableau Desktop is similar to a pivot table in Excel, with fields broken down into dimensions (categories) and measures (numerical values).', 'The software allows the user to apply filters and place columns and rows to create visual representations of data, making it easy to analyze and interpret data.', 'The end result of using Tableau Desktop is the creation of charts and dashboards for visualization and analysis of data.']}], 'duration': 288.171, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/TPMlZxRRaBQ/pics/TPMlZxRRaBQ8831.jpg', 'highlights': ['Tableau is primarily used in the exploration and reporting phases of the data science workflow, enabling efficient data visualization and sharing of results, with a focus on identifying relationships between variables and ensuring data quality.', "Tableau serves as an ideal tool for reporting and sharing results, offering great reporting tools and the ability to share workbooks for others to view, regardless of the organization's type.", 'Tableau Desktop enables visualization of large datasets with drag and drop interface, allowing easy creation of charts and dashboards for organizational use.', 'The exploration phase in Tableau allows for looking at different variables, data distribution, detecting outliers, and identifying relationships between variables, aiding in determining the quality and usability of data.', 'Tableau Public is a free version that can be downloaded from their website, providing the same functionalities as the paid version for personal use.']}, {'end': 493.378, 'segs': [{'end': 391.109, 'src': 'embed', 'start': 337.812, 'weight': 1, 'content': [{'end': 344.337, 'text': "It may take a while, depending on your internet speed, but it's generally pretty quick.", 'start': 337.812, 'duration': 6.525}, {'end': 355.887, 'text': 'So go ahead and install that on your computer.', 'start': 354.346, 'duration': 1.541}, {'end': 376.08, 'text': "I'm gonna fast forward the video here so that you don't have to watch this entire install,", 'start': 371.377, 'duration': 4.703}, {'end': 383.184, 'text': "but feel free to pause the video and hit play again when you're ready to go.", 'start': 376.08, 'duration': 7.104}, {'end': 391.109, 'text': "Okay, so now I've downloaded Tableau Public.", 'start': 383.204, 'duration': 7.905}], 'summary': "Installing tableau public may take a while, depending on internet speed, but it's generally pretty quick.", 'duration': 53.297, 'max_score': 337.812, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/TPMlZxRRaBQ/pics/TPMlZxRRaBQ337812.jpg'}, {'end': 493.378, 'src': 'embed', 'start': 413.363, 'weight': 0, 'content': [{'end': 421.427, 'text': "is that you're limited to just a handful of inputs here, just a handful of file types.", 'start': 413.363, 'duration': 8.064}, {'end': 433.954, 'text': 'The desktop version really has more options here and you can connect to a server like Azure or any sort of cloud environment, so AWS,', 'start': 422.888, 'duration': 11.066}, {'end': 437.596, 'text': 'Azure or Google Cloud and pull your data in directly from there here.', 'start': 433.954, 'duration': 3.642}, {'end': 450.091, 'text': "So we need to go ahead and get our data set and the data set I'm gonna use for this tutorial is the Titanic data set from Kaggle.", 'start': 439.468, 'duration': 10.623}, {'end': 458.412, 'text': "And I'll include links to Tableau Public and this data set in the video description.", 'start': 453.071, 'duration': 5.341}, {'end': 464.414, 'text': "You'll just click on that and you'll probably have to sign up if you don't have a Kaggle account.", 'start': 458.973, 'duration': 5.441}, {'end': 472.553, 'text': 'already and basically what this is is Kaggle is essentially just sort of the online Olympics for data nerds.', 'start': 465.508, 'duration': 7.045}, {'end': 477.256, 'text': 'You have competitions for machine learning, deep learning models.', 'start': 474.194, 'duration': 3.062}, {'end': 486.595, 'text': 'Companies can actually post their data sets on Kaggle and have basically the best data.', 'start': 478.596, 'duration': 7.999}, {'end': 492.218, 'text': 'scientists in the world compete to build the best model and the winner can actually earn money.', 'start': 486.595, 'duration': 5.623}, {'end': 493.378, 'text': "So it's pretty cool.", 'start': 492.458, 'duration': 0.92}], 'summary': 'Desktop version offers more options, can connect to azure, aws, or google cloud. using titanic dataset from kaggle for tutorial.', 'duration': 80.015, 'max_score': 413.363, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/TPMlZxRRaBQ/pics/TPMlZxRRaBQ413363.jpg'}], 'start': 297.342, 'title': "Tableau public installation and kaggle's titanic dataset analysis", 'summary': "Covers the process of downloading and installing tableau public, comparing its limitations to the paid version, and introduces kaggle's titanic dataset for competitions in machine learning and deep learning models, with the potential to earn money by building the best model.", 'chapters': [{'end': 437.596, 'start': 297.342, 'title': 'Tableau public installation and data connection', 'summary': 'Demonstrates the process of downloading and installing tableau public, and highlights the limitations of the free version compared to the paid version, including the restricted input options and the inability to connect to cloud servers.', 'duration': 140.254, 'highlights': ["The difference between the Tableau public version and the Tableau desktop, which is the paid version it's about $850, is that you're limited to just a handful of inputs here, just a handful of file types. The desktop version really has more options here and you can connect to a server like Azure or any sort of cloud environment, so AWS, Azure or Google Cloud and pull your data in directly from there here.", "It may take a while, depending on your internet speed, but it's generally pretty quick. So go ahead and install that on your computer.", "Once you're able to make a few charts, you could pull it together and make a dashboard like this, for example."]}, {'end': 493.378, 'start': 439.468, 'title': "Analyzing kaggle's titanic dataset", 'summary': 'Introduces the titanic dataset from kaggle, highlighting its use for competitions in machine learning and deep learning models, and the potential to earn money by building the best model.', 'duration': 53.91, 'highlights': ['Kaggle is an online platform for data competitions, including machine learning and deep learning models, where companies can post their datasets and have data scientists compete to build the best model, with winners earning money.', 'The tutorial focuses on using the Titanic dataset from Kaggle for analysis, providing links to Tableau Public and the dataset in the video description, and emphasizing the need for a Kaggle account to access it.']}], 'duration': 196.036, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/TPMlZxRRaBQ/pics/TPMlZxRRaBQ297342.jpg', 'highlights': ['Tableau desktop offers more options and can connect to cloud environments like AWS, Azure, or Google Cloud.', 'Installing Tableau Public is generally quick, depending on internet speed.', 'Kaggle hosts data competitions for machine learning and deep learning models, with winners earning money.', 'The tutorial focuses on using the Titanic dataset from Kaggle for analysis and emphasizes the need for a Kaggle account to access it.']}, {'end': 764.891, 'segs': [{'end': 591.004, 'src': 'embed', 'start': 531.341, 'weight': 0, 'content': [{'end': 533.222, 'text': "So we're gonna use text file input here.", 'start': 531.341, 'duration': 1.881}, {'end': 536.304, 'text': 'Navigate to the desktop, pull that in.', 'start': 534.463, 'duration': 1.841}, {'end': 549.19, 'text': "And once you open Tableau Public and import your data set, it's basically just gonna show you all of the data fields that exist.", 'start': 540.482, 'duration': 8.708}, {'end': 553.494, 'text': 'And you may not know what those are.', 'start': 550.972, 'duration': 2.522}, {'end': 558.119, 'text': 'So passenger ID survived, passenger class name for example.', 'start': 553.674, 'duration': 4.445}, {'end': 564.865, 'text': 'So Kaggle actually has a data dictionary here on the data set page.', 'start': 559.82, 'duration': 5.045}, {'end': 572.654, 'text': "So survival is a categorical variable, one standing for yes, two meaning no, that they didn't survive.", 'start': 566.311, 'duration': 6.343}, {'end': 576.716, 'text': 'Passenger class is the ticket class, so first, second, third class.', 'start': 573.255, 'duration': 3.461}, {'end': 583.34, 'text': 'Sex is the gender, male or female, age and years, number of siblings, parents,', 'start': 577.377, 'duration': 5.963}, {'end': 591.004, 'text': 'children above the Titanic for the following variables and then ticket ticket number, fare, cabin number.', 'start': 583.34, 'duration': 7.664}], 'summary': 'Using tableau public to analyze titanic data with categorical variables and data dictionary.', 'duration': 59.663, 'max_score': 531.341, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/TPMlZxRRaBQ/pics/TPMlZxRRaBQ531341.jpg'}, {'end': 668.946, 'src': 'heatmap', 'start': 609.996, 'weight': 4, 'content': [{'end': 617.46, 'text': 'We want to look at the correlation between these variables, these other variables, and whether or not the passenger survived.', 'start': 609.996, 'duration': 7.464}, {'end': 621.083, 'text': "So now we're going to go back to Tableau.", 'start': 619.622, 'duration': 1.461}, {'end': 626.037, 'text': "Passenger ID, that's gonna be probably not very useful.", 'start': 623.015, 'duration': 3.022}, {'end': 627.698, 'text': "Survived, that's gonna be very important.", 'start': 626.117, 'duration': 1.581}, {'end': 629.338, 'text': 'Passenger class.', 'start': 628.458, 'duration': 0.88}, {'end': 632.34, 'text': 'Passenger name is not gonna be very important.', 'start': 630.519, 'duration': 1.821}, {'end': 638.564, 'text': 'The ticket number is unlikely to be significant.', 'start': 635.622, 'duration': 2.942}, {'end': 641.145, 'text': "Fare, that's how much they paid.", 'start': 639.824, 'duration': 1.321}, {'end': 643.146, 'text': 'Cabin number and embarked.', 'start': 641.305, 'duration': 1.841}, {'end': 646.908, 'text': 'So you can see we have all of these columns here and you can always reference the data dictionary.', 'start': 643.406, 'duration': 3.502}, {'end': 650.17, 'text': "So we're gonna go ahead and click on sheet one at the bottom.", 'start': 646.928, 'duration': 3.242}, {'end': 662.002, 'text': 'And you can look how Tableau automatically pulls in these different variables.', 'start': 655.038, 'duration': 6.964}, {'end': 668.946, 'text': 'So they, it makes a determination based on the type of data being pulled in, whether it should be a dimension or a measure.', 'start': 662.262, 'duration': 6.684}], 'summary': 'Analyzing correlation between variables and passenger survival using tableau.', 'duration': 28.568, 'max_score': 609.996, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/TPMlZxRRaBQ/pics/TPMlZxRRaBQ609996.jpg'}], 'start': 494.159, 'title': 'Analyzing titanic passenger data', 'summary': "Covers importing a csv file into tableau, connecting to the file, importing it and understanding the data fields, including passenger id, survived, passenger class, and name. it also discusses variables in the titanic passenger data, emphasizing the importance of 'survival' and demonstrating the use of tableau for data analysis.", 'chapters': [{'end': 564.865, 'start': 494.159, 'title': 'Importing and analyzing data in tableau', 'summary': 'Covers how to import a csv file into tableau, detailing the process of connecting to the file, importing it, and understanding the data fields, including passenger id, survived, passenger class, and name.', 'duration': 70.706, 'highlights': ['The chapter details the process of connecting to a CSV file, importing it, and understanding the data fields, such as passenger ID, survived, passenger class, and name.', 'It explains how to use Tableau Public to import the data set and view all the data fields.', 'The process involves using the text file input to navigate to the desktop and pull in the CSV file.']}, {'end': 764.891, 'start': 566.311, 'title': 'Analyzing titanic passenger data', 'summary': "Discusses the variables in the titanic passenger data, emphasizing the importance of 'survival' and the correlation between different variables and passenger survival, while demonstrating the use of tableau for data analysis.", 'duration': 198.58, 'highlights': ["The importance of 'survival' as a variable in analyzing Titanic passenger data. ", "Emphasizing the correlation between different variables and passenger survival, with a focus on 'age' and its potential correlation with survival. ", 'Demonstration of using Tableau for data analysis and visualization of the Titanic passenger data. ']}], 'duration': 270.732, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/TPMlZxRRaBQ/pics/TPMlZxRRaBQ494159.jpg', 'highlights': ['The chapter details the process of connecting to a CSV file, importing it, and understanding the data fields, such as passenger ID, survived, passenger class, and name.', 'It explains how to use Tableau Public to import the data set and view all the data fields.', 'The process involves using the text file input to navigate to the desktop and pull in the CSV file.', "The importance of 'survival' as a variable in analyzing Titanic passenger data.", "Emphasizing the correlation between different variables and passenger survival, with a focus on 'age' and its potential correlation with survival.", 'Demonstration of using Tableau for data analysis and visualization of the Titanic passenger data.']}, {'end': 1264.839, 'segs': [{'end': 855.156, 'src': 'embed', 'start': 824.025, 'weight': 1, 'content': [{'end': 829.089, 'text': "But I really don't have any labels so I need to add the labels here so this makes sense.", 'start': 824.025, 'duration': 5.064}, {'end': 831.25, 'text': 'In the marks bar.', 'start': 830.489, 'duration': 0.761}, {'end': 839.504, 'text': 'This basically allows you to change the coloring, the labels, the size of your chart, and you have three.', 'start': 832.799, 'duration': 6.705}, {'end': 841.245, 'text': 'in this example, you have three sections.', 'start': 839.504, 'duration': 1.741}, {'end': 855.156, 'text': 'You have all, this section, which is the summation of all the records, and then this bottom one represents basically the percent of total.', 'start': 841.285, 'duration': 13.871}], 'summary': 'Adding labels and customizing chart features in the marks bar, with options for color, size, and section representation.', 'duration': 31.131, 'max_score': 824.025, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/TPMlZxRRaBQ/pics/TPMlZxRRaBQ824025.jpg'}, {'end': 941.535, 'src': 'embed', 'start': 913.254, 'weight': 4, 'content': [{'end': 916.977, 'text': "we're gonna use the survived variable here, and it's a measure.", 'start': 913.254, 'duration': 3.723}, {'end': 926.684, 'text': 'Tableau treated that as a measure when it pulled it in to the data set, but we really wanna treat that as a categorical variable,', 'start': 918.698, 'duration': 7.986}, {'end': 928.545, 'text': 'so we wanna convert it from a measure to a dimension.', 'start': 926.684, 'duration': 1.861}, {'end': 936.091, 'text': 'And the way you do that is you hover over the variable, click down here, and then convert to dimension.', 'start': 929.346, 'duration': 6.745}, {'end': 941.535, 'text': "So now that's a dimension, it moves up to, from measures up to the dimension section.", 'start': 936.951, 'duration': 4.584}], 'summary': "Convert 'survived' from measure to dimension in tableau.", 'duration': 28.281, 'max_score': 913.254, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/TPMlZxRRaBQ/pics/TPMlZxRRaBQ913254.jpg'}, {'end': 1019.945, 'src': 'embed', 'start': 993.358, 'weight': 0, 'content': [{'end': 1004.642, 'text': 'So you can see what the distribution looks like here in terms of the total number of records by age bin, and then you can compare each ratio,', 'start': 993.358, 'duration': 11.284}, {'end': 1013.506, 'text': 'the percentage, each age bucket, to see if that age grouping had a disproportionate survival rate relative to all the passengers.', 'start': 1004.642, 'duration': 8.864}, {'end': 1019.945, 'text': "So this is great, we're gonna call this, we're gonna rename this tab.", 'start': 1016.704, 'duration': 3.241}], 'summary': 'Analyzing age distribution and survival rates for passengers.', 'duration': 26.587, 'max_score': 993.358, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/TPMlZxRRaBQ/pics/TPMlZxRRaBQ993358.jpg'}, {'end': 1219.302, 'src': 'embed', 'start': 1193.248, 'weight': 6, 'content': [{'end': 1198.93, 'text': "if you click on, show me, over here in the top right corner, I'm gonna actually just create a pie chart.", 'start': 1193.248, 'duration': 5.682}, {'end': 1206.732, 'text': 'I feel like that makes a lot of sense for this type of information.', 'start': 1198.93, 'duration': 7.802}, {'end': 1207.913, 'text': "you know it's gonna be one or the other.", 'start': 1206.732, 'duration': 1.181}, {'end': 1211.194, 'text': "they survived or they didn't survive, and I can drag that out to make it a little bit bigger.", 'start': 1207.913, 'duration': 3.281}, {'end': 1219.302, 'text': 'And when you click on the pie chart option here, it automatically adds these labels.', 'start': 1213.097, 'duration': 6.205}], 'summary': 'Demonstrating the creation of a pie chart for binary survival data.', 'duration': 26.054, 'max_score': 1193.248, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/TPMlZxRRaBQ/pics/TPMlZxRRaBQ1193248.jpg'}], 'start': 765.432, 'title': 'Visualization tool usage and titanic data analysis', 'summary': 'Demonstrates using a visualization tool to filter out null values, calculate percentages, and add labels to a bar chart for data analysis. it also covers the process of analyzing titanic passenger data in tableau, including converting variables, creating visualizations, and comparing survival rates based on different variables such as age, passenger class, and sibling spouses.', 'chapters': [{'end': 882.791, 'start': 765.432, 'title': 'Visualization tool usage for data analysis', 'summary': 'Demonstrates using a visualization tool to filter out null values, calculate percentages, and add labels to a bar chart for data analysis.', 'duration': 117.359, 'highlights': ['By filtering out null values and applying percentages, the distribution of data is visualized effectively.', 'Adding labels to the bar chart provides context and improves data interpretation.', 'Utilizing the visualization tool to calculate percentages allows for a clear understanding of the data distribution.']}, {'end': 1264.839, 'start': 884.901, 'title': 'Titanic data analysis', 'summary': 'Covers the process of analyzing titanic passenger data in tableau, including converting variables, creating visualizations, and comparing survival rates based on different variables such as age, passenger class, and sibling spouses.', 'duration': 379.938, 'highlights': ["The chapter demonstrates the process of analyzing Titanic passenger data in Tableau, including converting variables, creating visualizations, and comparing survival rates. The demonstration includes converting the 'survived' variable from a measure to a dimension, creating visualizations based on age and passenger class, and utilizing a pie chart to compare the number of survivors and non-survivors.", "The process of converting variables, such as 'survived' from a measure to a dimension, is explained. The process includes demonstrating how to convert the 'survived' variable from a measure to a dimension in Tableau, allowing for categorical analysis of survival rates.", 'Creating visualizations based on different variables, such as age and passenger class, is highlighted. The chapter showcases the creation of visualizations based on age and passenger class, enabling the comparison of survival rates across different categories within the dataset.', 'Utilizing a pie chart to compare the number of survivors and non-survivors is demonstrated. A demonstration of using a pie chart to visually compare the number of survivors and non-survivors within the Titanic passenger dataset is provided, offering a clear representation of survival proportions.']}], 'duration': 499.407, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/TPMlZxRRaBQ/pics/TPMlZxRRaBQ765432.jpg', 'highlights': ['By filtering out null values and applying percentages, the distribution of data is visualized effectively.', 'Adding labels to the bar chart provides context and improves data interpretation.', 'Utilizing the visualization tool to calculate percentages allows for a clear understanding of the data distribution.', 'The chapter demonstrates the process of analyzing Titanic passenger data in Tableau, including converting variables, creating visualizations, and comparing survival rates.', "The process of converting variables, such as 'survived' from a measure to a dimension, is explained.", 'Creating visualizations based on different variables, such as age and passenger class, is highlighted.', 'Utilizing a pie chart to compare the number of survivors and non-survivors is demonstrated.']}, {'end': 1716.223, 'segs': [{'end': 1368.872, 'src': 'heatmap', 'start': 1271.835, 'weight': 0, 'content': [{'end': 1277.378, 'text': "We can actually use this information to create a dashboard in Tableau, and I'm gonna get to that in a second.", 'start': 1271.835, 'duration': 5.543}, {'end': 1282.821, 'text': 'but what I wanna cover very quickly is how to create your own measure, okay?', 'start': 1277.378, 'duration': 5.443}, {'end': 1285.162, 'text': "So I'm gonna use age for this.", 'start': 1282.841, 'duration': 2.321}, {'end': 1288.624, 'text': "I'm going to, instead of using the bins, create a calculated field.", 'start': 1285.622, 'duration': 3.002}, {'end': 1294.647, 'text': "We'll call it custom age bins.", 'start': 1292.126, 'duration': 2.521}, {'end': 1311.414, 'text': "We're gonna say if age is less than or equal to 10, then 0 to 10 else.", 'start': 1297.629, 'duration': 13.785}, {'end': 1352.603, 'text': "if age greater than 10 and age less than or equal to, let's just say 20, then 11 to 20..", 'start': 1311.414, 'duration': 41.189}, {'end': 1357.106, 'text': "Else if, you get the idea, I'm not gonna do this for every age bucket.", 'start': 1352.603, 'duration': 4.503}, {'end': 1363.93, 'text': "We'll just lump everybody else in over 20.", 'start': 1358.947, 'duration': 4.983}, {'end': 1368.872, 'text': "We'll just put them in 20 plus, so they're 20 years plus.", 'start': 1363.93, 'duration': 4.942}], 'summary': 'Creating custom age bins in tableau for data visualization.', 'duration': 103.973, 'max_score': 1271.835, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/TPMlZxRRaBQ/pics/TPMlZxRRaBQ1271835.jpg'}, {'end': 1476.962, 'src': 'heatmap', 'start': 1443.157, 'weight': 0.742, 'content': [{'end': 1446.94, 'text': 'Okay, so what this does is creates a blank canvas for us to create a dashboard.', 'start': 1443.157, 'duration': 3.783}, {'end': 1451.844, 'text': 'And this thing always, for whatever reason, the size is always wrong.', 'start': 1446.96, 'duration': 4.884}, {'end': 1453.365, 'text': 'So I just change it.', 'start': 1452.204, 'duration': 1.161}, {'end': 1462.191, 'text': 'click on this little down arrow here and then the other one right below it and choose automatic, and it expands it to fit your screen.', 'start': 1453.365, 'duration': 8.826}, {'end': 1464.193, 'text': 'And then we just double click each of these sheets.', 'start': 1462.351, 'duration': 1.842}, {'end': 1467.155, 'text': 'Age, class, sibling, survive.', 'start': 1465.134, 'duration': 2.021}, {'end': 1476.962, 'text': 'Okay That was really fast, really easy to kind of pull this stuff together and add it to a dashboard.', 'start': 1468.016, 'duration': 8.946}], 'summary': 'The process creates a dashboard with automatic expansion to fit the screen, enabling quick and easy addition of data.', 'duration': 33.805, 'max_score': 1443.157, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/TPMlZxRRaBQ/pics/TPMlZxRRaBQ1443157.jpg'}, {'end': 1606.544, 'src': 'embed', 'start': 1551.291, 'weight': 2, 'content': [{'end': 1560.624, 'text': "So we just in a matter of minutes were able to create sheets and then a dashboard, and that's really fantastic.", 'start': 1551.291, 'duration': 9.333}, {'end': 1568.77, 'text': "All these other tools that you could use like Qlik or D3 or, I don't know, it takes a while.", 'start': 1561.365, 'duration': 7.405}, {'end': 1574.834, 'text': 'You gotta know how to code in those software programs in order to make the visualizations.', 'start': 1569.83, 'duration': 5.004}, {'end': 1578.573, 'text': "you know, it's just a pain.", 'start': 1577.332, 'duration': 1.241}, {'end': 1582.194, 'text': "So the thing I like about Tableau is it's really easy.", 'start': 1578.733, 'duration': 3.461}, {'end': 1589.417, 'text': 'I compare it to like an iPhone where someone, a child can basically pick up an iPhone and immediately start using it.', 'start': 1582.254, 'duration': 7.163}, {'end': 1590.297, 'text': "It's that intuitive.", 'start': 1589.457, 'duration': 0.84}, {'end': 1593.559, 'text': 'You know, Tableau is that way for visualization.', 'start': 1591.178, 'duration': 2.381}, {'end': 1595.059, 'text': "It's really that simple.", 'start': 1593.679, 'duration': 1.38}, {'end': 1598.641, 'text': 'You just literally drag and drop until you get what you want.', 'start': 1595.099, 'duration': 3.542}, {'end': 1602.542, 'text': "So I really actually don't like these colors, especially the red.", 'start': 1599.721, 'duration': 2.821}, {'end': 1606.544, 'text': "Maybe we'll just add the blue back.", 'start': 1602.562, 'duration': 3.982}], 'summary': 'Tableau allows for quick and intuitive data visualization, unlike qlik or d3, making it easy for non-coders.', 'duration': 55.253, 'max_score': 1551.291, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/TPMlZxRRaBQ/pics/TPMlZxRRaBQ1551291.jpg'}, {'end': 1683.935, 'src': 'embed', 'start': 1655.419, 'weight': 1, 'content': [{'end': 1666.802, 'text': 'And siblings and spouses, those that had I guess fewer siblings and spouses, they survived at a higher rate, which is obviously pretty sad.', 'start': 1655.419, 'duration': 11.383}, {'end': 1671.103, 'text': 'But this really kind of brings to life the data.', 'start': 1667.482, 'duration': 3.621}, {'end': 1674.024, 'text': 'We all know what happened with the Titanic.', 'start': 1671.764, 'duration': 2.26}, {'end': 1683.935, 'text': "And if we were to just look at this data here in the data source, you know, just looking at this, you know, there's only 891 rows.", 'start': 1674.885, 'duration': 9.05}], 'summary': 'Fewer siblings and spouses led to higher survival rate on the titanic.', 'duration': 28.516, 'max_score': 1655.419, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/TPMlZxRRaBQ/pics/TPMlZxRRaBQ1655419.jpg'}], 'start': 1264.899, 'title': 'Creating custom age bins and dashboards in tableau', 'summary': 'Covers creating custom age bins in tableau for passengers aged 0-10, 11-20, and 20+, and demonstrates dashboard creation, including insights from titanic dataset like survival rates based on age, class, and siblings/spouses.', 'chapters': [{'end': 1403.882, 'start': 1264.899, 'title': 'Creating custom age bins in tableau', 'summary': "Covers the process of creating custom age bins in tableau by using the 'if' condition to group passengers into specific age ranges, with a focus on passengers aged 0-10, 11-20, and 20+.", 'duration': 138.983, 'highlights': ['The chapter explains how to create a calculated field in Tableau to group passengers into custom age bins, focusing on age ranges 0-10, 11-20, and 20+.', "The speaker discusses the use of 'if' conditions to categorize passengers based on their age, with a specific focus on creating a catch-all category for passengers not falling into the predefined age ranges.", "The process involves creating a calculated field called 'custom age bins' and using 'if' statements to define age ranges, such as 0-10, 11-20, and 20+, to categorize passengers in Tableau."]}, {'end': 1716.223, 'start': 1405.438, 'title': 'Creating dashboards with tableau', 'summary': "Demonstrates how to create a dashboard in tableau, including steps such as using the bin function, arranging sheets, modifying visuals, and comparing tableau's ease of use with other software. it also highlights key insights from a titanic dataset, such as survival rates based on age, class, and siblings/spouses.", 'duration': 310.785, 'highlights': ['By using Tableau, the process of creating sheets and a dashboard is fast and easy, compared to other tools like Qlik or D3, which require coding for visualizations.', 'Insights from the Titanic dataset show higher survival rates for passengers aged 20-30, those in the first class, and individuals with fewer siblings/spouses.', 'The demonstration emphasizes the ease and intuitiveness of Tableau, likening it to an iPhone in terms of user-friendliness and simplicity for visualization creation.', "Tableau's efficiency in handling large datasets is highlighted, showcasing its advantage over Excel and other software in terms of data analysis and visualization creation."]}], 'duration': 451.324, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/TPMlZxRRaBQ/pics/TPMlZxRRaBQ1264899.jpg', 'highlights': ["The process involves creating a calculated field called 'custom age bins' and using 'if' statements to define age ranges, such as 0-10, 11-20, and 20+, to categorize passengers in Tableau.", 'Insights from the Titanic dataset show higher survival rates for passengers aged 20-30, those in the first class, and individuals with fewer siblings/spouses.', 'By using Tableau, the process of creating sheets and a dashboard is fast and easy, compared to other tools like Qlik or D3, which require coding for visualizations.', "The speaker discusses the use of 'if' conditions to categorize passengers based on their age, with a specific focus on creating a catch-all category for passengers not falling into the predefined age ranges.", 'The demonstration emphasizes the ease and intuitiveness of Tableau, likening it to an iPhone in terms of user-friendliness and simplicity for visualization creation.', "Tableau's efficiency in handling large datasets is highlighted, showcasing its advantage over Excel and other software in terms of data analysis and visualization creation."]}], 'highlights': ["Tableau serves as an ideal tool for reporting and sharing results, offering great reporting tools and the ability to share workbooks for others to view, regardless of the organization's type.", 'Tableau Desktop enables visualization of large datasets with drag and drop interface, allowing easy creation of charts and dashboards for organizational use.', 'The exploration phase in Tableau allows for looking at different variables, data distribution, detecting outliers, and identifying relationships between variables, aiding in determining the quality and usability of data.', 'Tableau Public is a free version that can be downloaded from their website, providing the same functionalities as the paid version for personal use.', 'Tableau desktop offers more options and can connect to cloud environments like AWS, Azure, or Google Cloud.', 'Installing Tableau Public is generally quick, depending on internet speed.', 'The tutorial focuses on using the Titanic dataset from Kaggle for analysis and emphasizes the need for a Kaggle account to access it.', 'The chapter details the process of connecting to a CSV file, importing it, and understanding the data fields, such as passenger ID, survived, passenger class, and name.', 'It explains how to use Tableau Public to import the data set and view all the data fields.', 'The process involves using the text file input to navigate to the desktop and pull in the CSV file.', "The importance of 'survival' as a variable in analyzing Titanic passenger data.", "Emphasizing the correlation between different variables and passenger survival, with a focus on 'age' and its potential correlation with survival.", 'Demonstration of using Tableau for data analysis and visualization of the Titanic passenger data.', 'By filtering out null values and applying percentages, the distribution of data is visualized effectively.', 'Adding labels to the bar chart provides context and improves data interpretation.', 'Utilizing the visualization tool to calculate percentages allows for a clear understanding of the data distribution.', 'The chapter demonstrates the process of analyzing Titanic passenger data in Tableau, including converting variables, creating visualizations, and comparing survival rates.', "The process of converting variables, such as 'survived' from a measure to a dimension, is explained.", 'Creating visualizations based on different variables, such as age and passenger class, is highlighted.', 'Utilizing a pie chart to compare the number of survivors and non-survivors is demonstrated.', "The process involves creating a calculated field called 'custom age bins' and using 'if' statements to define age ranges, such as 0-10, 11-20, and 20+, to categorize passengers in Tableau.", 'Insights from the Titanic dataset show higher survival rates for passengers aged 20-30, those in the first class, and individuals with fewer siblings/spouses.', 'By using Tableau, the process of creating sheets and a dashboard is fast and easy, compared to other tools like Qlik or D3, which require coding for visualizations.', "The speaker discusses the use of 'if' conditions to categorize passengers based on their age, with a specific focus on creating a catch-all category for passengers not falling into the predefined age ranges.", 'The demonstration emphasizes the ease and intuitiveness of Tableau, likening it to an iPhone in terms of user-friendliness and simplicity for visualization creation.', "Tableau's efficiency in handling large datasets is highlighted, showcasing its advantage over Excel and other software in terms of data analysis and visualization creation."]}