title
Tableau Projects For Practice With Examples | Tableau Training For Beginners | Simplilearn

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🔥Post Graduate Program In Data Analytics: https://www.simplilearn.com/pgp-data-analytics-certification-training-course?utm_campaign=TableauProjectsForPracticeWithExamples-5uzB4z4iN0g&utm_medium=Descriptionff&utm_source=youtube 🔥IIT Kanpur Professional Certificate Course In Data Analytics (India Only): https://www.simplilearn.com/iitk-professional-certificate-course-data-analytics?utm_campaign=TableauProjectsForPracticeWithExamples-5uzB4z4iN0g&utm_medium=Descriptionff&utm_source=youtube 🔥Data Analyst Masters Program (Discount Code - YTBE15): https://www.simplilearn.com/data-analyst-masters-certification-training-courseutm_campaign=TableauProjectsForPracticeWithExamples-5uzB4z4iN0g&utm_medium=Descriptionff&utm_source=youtube 🔥Caltech Data Analytics Bootcamp(US Only): https://www.simplilearn.com/data-analytics-bootcamp?utm_campaign=TableauProjectsForPracticeWithExamples-5uzB4z4iN0g&utm_medium=Descriptionff&utm_source=youtube This video is based on Tableau Projects for Practice with Examples. This Tableau training for beginners video includes some trending data science projects that could help you with some latest skills and an overall learning experience of using the fundamental features and tools in Tableau. 00:00 Introduction 00:50 COVID - 19 Dashboard Project 56:30 Airline Dashboard 01:01:01 Space Mission Dashboard Dataset Link - https://drive.google.com/drive/folders/1pPiCs-x8QuVEfNehzqDQhmL36LwICPt8 ✅Subscribe to our Channel to learn more about the top Technologies: https://bit.ly/2VT4WtH ⏩ Check out the Data Analytics tutorial videos: https://www.youtube.com/playlist?list=PLEiEAq2VkUUKgEFXH1tBbHwq38oWYDScU #TableauProjectsForPractice #TableauPraticalExamples #TableauProjectsPractiveWithSolutions #Tableau #TableauTrainingForBeginners #TableauTutorialForBeginners #DataScience #Simplilearn 🔥Free Tableau Course: https://www.simplilearn.com/learn-tableau-online-free-course-skillup?utm_campaign=TableauProjectsForPracticeWithExamples&utm_medium=Description&utm_source=youtube ➡️ About Post Graduate Program In Data Analytics This Data Analytics Program is ideal for all working professionals and prior programming knowledge is not required. It covers topics like data analysis, data visualization, regression techniques, and supervised learning in-depth via our applied learning model with live sessions by leading practitioners and industry projects. ✅ Key Features - Post Graduate Program certificate and Alumni Association membership - Exclusive hackathons and Ask me Anything sessions by IBM - 8X higher live interaction in live online classes by industry experts - Capstone from 3 domains and 14+ Data Analytics Projects with Industry datasets from Google PlayStore, Lyft, World Bank etc. - Master Classes delivered by Purdue faculty and IBM experts - Simplilearn's JobAssist helps you get noticed by top hiring companies - Resume preparation and LinkedIn profile building - 1:1 mock interview - Career accelerator webinars ✅ Skills Covered - Data Analytics - Statistical Analysis using Excel - Data Analysis Python and R - Data Visualization Tableau and Power BI - Linear and logistic regression modules - Clustering using kmeans - Supervised Learning 👉 Learn More at: https://www.simplilearn.com/pgp-data-analytics-certification-training-course?utm_campaign=TableauProjectsForPracticeWithExamples-5uzB4z4iN0g&utm_medium=Description&utm_source=youtube 🔥Caltech Data Analytics Bootcamp(US Only): https://www.simplilearn.com/data-analytics-bootcamp?utm_campaign=TableauProjectsForPracticeWithExamples-5uzB4z4iN0g&utm_medium=Description&utm_source=youtube 🔥🔥 Interested in Attending Live Classes? Call Us: IN - 18002127688 / US - +18445327688

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{'title': 'Tableau Projects For Practice With Examples | Tableau Training For Beginners | Simplilearn', 'heatmap': [{'end': 1620.048, 'start': 1517.99, 'weight': 0.786}], 'summary': 'Presents tableau projects on covid-19, airline data, and space missions, providing insights into total confirmed and recovered cases in different nations, covid-19 forecasting, data interpretation, and analysis, as well as creating visualizations and dashboards for airline data and space missions, with specific details on covid-19 cases in india and forecasting in india and the us.', 'chapters': [{'end': 118.508, 'segs': [{'end': 99.782, 'src': 'embed', 'start': 41.866, 'weight': 0, 'content': [{'end': 45.228, 'text': "Followed by that we'll have another project based on the airline data.", 'start': 41.866, 'duration': 3.362}, {'end': 49.892, 'text': 'And finally the third project will be based on space missions data.', 'start': 45.749, 'duration': 4.143}, {'end': 52.775, 'text': "Now let's begin with our first project.", 'start': 50.593, 'duration': 2.182}, {'end': 59.879, 'text': "So, in this first project, we'll be dealing with the COVID-19 dataset and using that dataset, we'll be getting some insights.", 'start': 53.275, 'duration': 6.604}, {'end': 61.34, 'text': 'So what are those insights?', 'start': 60.079, 'duration': 1.261}, {'end': 66.263, 'text': 'Those are what are the total number of confirmed cases in different nations?', 'start': 61.78, 'duration': 4.483}, {'end': 69.865, 'text': 'What are the total number of recovered cases in different nations?', 'start': 66.843, 'duration': 3.022}, {'end': 80.171, 'text': "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.", 'start': 69.905, 'duration': 10.266}, {'end': 85.699, 'text': "Followed by that, we'll also look into the insights of the confirmed and recovered cases in India as well.", 'start': 80.951, 'duration': 4.748}, {'end': 92.51, 'text': "Followed by that, we'll enter into the next query, where we'll find out the trend line of COVID-19 in the international level, like how it started.", 'start': 86.1, 'duration': 6.41}, {'end': 93.271, 'text': 'how is it going on?', 'start': 92.51, 'duration': 0.761}, {'end': 99.782, 'text': "And moving forward, we'll create a group of Indian states and we'll find out the COVID hits there.", 'start': 94.261, 'duration': 5.521}], 'summary': 'Projects include covid-19 and airline data analysis, with focus on total confirmed and recovered cases in different nations, along with insights on international and indian covid-19 trends.', 'duration': 57.916, 'max_score': 41.866, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g41866.jpg'}], 'start': 8.399, 'title': 'Tableau projects: covid-19 and more', 'summary': 'Covers tableau projects on covid-19, airline data, and space missions, providing insights into total confirmed and recovered cases in different nations, trend lines of covid-19, and future predictions.', 'chapters': [{'end': 118.508, 'start': 8.399, 'title': 'Tableau projects: covid-19 and more', 'summary': 'Discusses tableau projects on covid-19, airline data, and space missions, exploring insights such as total confirmed and recovered cases in different nations, trend lines of covid-19, and future predictions.', 'duration': 110.109, 'highlights': ['The first project focuses on COVID-19 data, analyzing total confirmed and recovered cases in different nations and creating a trend line of COVID-19 at an international level.', 'The discussion also includes insights into the confirmed and recovered cases in India, variation in COVID-19 cases around the world, and the future predictions of COVID-19 at an international level.', 'The chapter encompasses projects based on airline data and space missions data, providing a comprehensive exploration of technological trends and insights into the COVID-19 situation.']}], 'duration': 110.109, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g8399.jpg', 'highlights': ['The chapter covers projects on COVID-19, airline data, and space missions.', 'It provides insights into total confirmed and recovered cases in different nations.', 'The projects include creating a trend line of COVID-19 at an international level.', 'The discussion includes insights into the confirmed and recovered cases in India.', 'It encompasses projects based on airline data and space missions data.']}, {'end': 311.194, 'segs': [{'end': 193.913, 'src': 'embed', 'start': 118.808, 'weight': 0, 'content': [{'end': 126.791, 'text': "Basically, we'll create a trend line which will give us the forecast levels of the COVID-19, like is it going to increase or is it going to decrease,", 'start': 118.808, 'duration': 7.983}, {'end': 128.612, 'text': "or what's going to happen in the near future?", 'start': 126.791, 'duration': 1.821}, {'end': 135.575, 'text': 'So I hope I made myself clear with the queries or the insights that we are going to take from the COVID-19 dataset using Tableau.', 'start': 129.252, 'duration': 6.323}, {'end': 138.776, 'text': "So without further ado, let's get started with the Tableau.", 'start': 136.015, 'duration': 2.761}, {'end': 141.297, 'text': 'So we are on Tableau right now.', 'start': 139.656, 'duration': 1.641}, {'end': 143.338, 'text': "So we'll be using an Excel data file.", 'start': 141.377, 'duration': 1.961}, {'end': 148.853, 'text': "So we'll be using the COVID-19 data file.", 'start': 146.812, 'duration': 2.041}, {'end': 152.433, 'text': 'So this particular data set is available on Kaggle.', 'start': 149.553, 'duration': 2.88}, {'end': 158.035, 'text': "And if you don't find it there, don't worry, we'll be attaching that particular data set in the description box below.", 'start': 152.694, 'duration': 5.341}, {'end': 159.055, 'text': 'You can use that as well.', 'start': 158.075, 'duration': 0.98}, {'end': 162.876, 'text': "Now let's just select open to get connected with that particular data.", 'start': 159.555, 'duration': 3.321}, {'end': 182.525, 'text': '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 tableau might identify,', 'start': 165.557, 'duration': 16.968}, {'end': 188.349, 'text': 'and when it identifies something messy with the data, it will show you an option.', 'start': 182.525, 'duration': 5.824}, {'end': 193.913, 'text': 'maybe you might want to use the data interpreter, so i prefer using that.', 'start': 188.349, 'duration': 5.564}], 'summary': 'Using tableau to analyze covid-19 trends, accessing data from kaggle, and utilizing data interpreter for accuracy.', 'duration': 75.105, 'max_score': 118.808, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g118808.jpg'}, {'end': 300.496, 'src': 'embed', 'start': 274.008, 'weight': 5, 'content': [{'end': 282.857, 'text': 'So we have the serial numbers, observation dates, province, state and country or region, last update and confirmed deaths recovered.', 'start': 274.008, 'duration': 8.849}, {'end': 287.522, 'text': 'So, basically, these three columns will be telling us the confirmed cases in that particular region,', 'start': 283.337, 'duration': 4.185}, {'end': 294.469, 'text': 'country or state and the deaths happened in that region, country or state and recovered rate and the last update.', 'start': 287.522, 'duration': 6.947}, {'end': 300.496, 'text': "when was the last test done, the latest test done and in which region, and what's the observation date,", 'start': 294.469, 'duration': 6.027}], 'summary': 'The data includes serial numbers, observation dates, province, state, and country, along with confirmed deaths and recoveries, providing insights into the covid-19 situation in various regions.', 'duration': 26.488, 'max_score': 274.008, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g274008.jpg'}], 'start': 118.808, 'title': 'Covid-19 forecasting and data interpretation in tableau', 'summary': 'Covers forecasting covid-19 levels using tableau with an excel data file from kaggle and demonstrates data cleaning and interpretation in tableau, including identifying and resolving data issues, ensuring a clean dataset, and providing an overview of key dataset columns.', 'chapters': [{'end': 162.876, 'start': 118.808, 'title': 'Covid-19 forecasting using tableau', 'summary': 'Will demonstrate how to create a trend line to forecast covid-19 levels using tableau with an excel data file from kaggle, providing insights on the future trend of covid-19.', 'duration': 44.068, 'highlights': ['Using Tableau to forecast COVID-19 levels with an Excel data file from Kaggle', 'Creating a trend line to predict the future trend of COVID-19', 'Providing insights on the forecasted increase or decrease of COVID-19 levels']}, {'end': 311.194, 'start': 165.557, 'title': 'Data cleaning and interpretation in tableau', 'summary': 'Explains the process of using the data interpreter in tableau to identify and resolve data issues, ensuring a clean dataset, and provides an overview of the columns in the dataset, including confirmed cases, deaths, recoveries, and observation details.', 'duration': 145.637, 'highlights': ["The process of using the data interpreter in Tableau to identify and resolve data issues Tableau's data interpreter helps identify and resolve data issues, ensuring a clean dataset.", 'Overview of the columns in the dataset, including confirmed cases, deaths, recoveries, and observation details The dataset includes columns for confirmed cases, deaths, recoveries, observation dates, and other relevant information.']}], 'duration': 192.386, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g118808.jpg', 'highlights': ['Using Tableau to forecast COVID-19 levels with an Excel data file from Kaggle', 'Creating a trend line to predict the future trend of COVID-19', 'Providing insights on the forecasted increase or decrease of COVID-19 levels', 'The process of using the data interpreter in Tableau to identify and resolve data issues', "Tableau's data interpreter helps identify and resolve data issues, ensuring a clean dataset", 'Overview of the columns in the dataset, including confirmed cases, deaths, recoveries, and observation details', 'The dataset includes columns for confirmed cases, deaths, recoveries, observation dates, and other relevant information']}, {'end': 1007.024, 'segs': [{'end': 367.745, 'src': 'embed', 'start': 312.808, 'weight': 0, 'content': [{'end': 319.47, 'text': 'so according to our first query, we had to find out the total number of confirmed cases in different nations.', 'start': 312.808, 'duration': 6.662}, {'end': 326.912, 'text': 'so for that we might want to select the country or region and then the confirmed from measures.', 'start': 319.47, 'duration': 7.442}, {'end': 333.674, 'text': "so for that we'll be selecting the map chart for this, so that we have the data shown in a more appealing format.", 'start': 326.912, 'duration': 6.762}, {'end': 338.656, 'text': 'so now we have the bluer color of map on our screen right now,', 'start': 333.674, 'duration': 4.982}, {'end': 347.868, 'text': 'where the darkest color shows the maximum number of cases confirmed and the lighter ones represent the lower number of cases confirmed.', 'start': 338.656, 'duration': 9.212}, {'end': 352.031, 'text': "Now, let's make this look a little more interesting.", 'start': 348.809, 'duration': 3.222}, {'end': 361.458, 'text': "So, for that, we can select the edit color options and inside that, let's select the red to green diverging.", 'start': 352.471, 'duration': 8.987}, {'end': 367.745, 'text': 'Yeah, this is a red to green white diverging.', 'start': 364.42, 'duration': 3.325}], 'summary': 'Using a map chart to visualize confirmed cases by country, with color indicating case numbers.', 'duration': 54.937, 'max_score': 312.808, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g312808.jpg'}, {'end': 465.423, 'src': 'embed', 'start': 434.561, 'weight': 2, 'content': [{'end': 441.978, 'text': 'now, according to our second query, We are supposed to find the total number of recovered cases in different nations.', 'start': 434.561, 'duration': 7.417}, {'end': 445.1, 'text': "So now let's create a new sheet for that.", 'start': 443.138, 'duration': 1.962}, {'end': 449.463, 'text': "Now. for that we'll be selecting the country or region,", 'start': 445.72, 'duration': 3.743}, {'end': 457.408, 'text': "and then we'll be selecting the recovered and hover over to the show me icon and let's select the map for that.", 'start': 449.463, 'duration': 7.945}, {'end': 465.423, 'text': 'Now you can see that we have a lot of recovery happening in India.', 'start': 460.501, 'duration': 4.922}], 'summary': 'Finding total number of recovered cases in different nations, with india showing significant recovery.', 'duration': 30.862, 'max_score': 434.561, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g434561.jpg'}, {'end': 850.737, 'src': 'embed', 'start': 821.087, 'weight': 3, 'content': [{'end': 821.888, 'text': "Yeah, that's fine.", 'start': 821.087, 'duration': 0.801}, {'end': 827.611, 'text': "Now let's get back to the presentation mode and see our next query.", 'start': 822.428, 'duration': 5.183}, {'end': 831.234, 'text': 'So can we forecast a trend line of COVID-19? Yeah.', 'start': 827.912, 'duration': 3.322}, {'end': 835.677, 'text': 'So how it started, how is it going on? So we can do that.', 'start': 831.894, 'duration': 3.783}, {'end': 837.478, 'text': "Let's get back to Tableau again.", 'start': 836.157, 'duration': 1.321}, {'end': 839.7, 'text': "So let's create a new sheet.", 'start': 838.199, 'duration': 1.501}, {'end': 841.161, 'text': 'We have the new sheet over here.', 'start': 839.84, 'duration': 1.321}, {'end': 843.122, 'text': "Let's rename that as trend line.", 'start': 841.221, 'duration': 1.901}, {'end': 850.737, 'text': 'Yeah, the sheet got renamed.', 'start': 848.655, 'duration': 2.082}], 'summary': 'Using tableau to forecast covid-19 trend line.', 'duration': 29.65, 'max_score': 821.087, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g821087.jpg'}], 'start': 312.808, 'title': 'Visualizing covid-19 data', 'summary': "Covers visualizing total confirmed cases in different nations using a map chart with the option to edit color, and explores covid-19 data analysis including total confirmed and recovered cases in different nations, focusing on india's recovery rate and trend line creation.", 'chapters': [{'end': 398.624, 'start': 312.808, 'title': 'Visualizing total confirmed cases', 'summary': 'Covers visualizing total confirmed cases in different nations using a map chart, where the darkest color represents the maximum number of cases confirmed, and the lighter ones represent the lower number of cases confirmed, with an option to edit color to red to green diverging.', 'duration': 85.816, 'highlights': ['Using a map chart to visualize total confirmed cases in different nations, with the darkest color representing the maximum number of cases confirmed.', 'Explaining the option to edit color to red to green diverging for a more appealing format.']}, {'end': 1007.024, 'start': 398.624, 'title': 'Covid-19 data analysis', 'summary': "Explores the analysis of covid-19 data using tableau, including the total confirmed and recovered cases in different nations, with a focus on india's recovery rate and the creation of trend lines to forecast the covid-19 trend.", 'duration': 608.4, 'highlights': ["The total confirmed and recovered cases in different nations are analyzed using Tableau, with a focus on India's recovery rate. The speaker discusses the process of creating separate sheets for confirmed and recovered cases at the international level, highlighting the significant recovery happening in India.", 'The creation of trend lines to forecast the COVID-19 trend using Tableau. The process of creating a trend line is explained, including selecting observation date, changing data type to date or date and time from string, and creating a trend line to forecast the COVID-19 trend.']}], 'duration': 694.216, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g312808.jpg', 'highlights': ['Using a map chart to visualize total confirmed cases in different nations, with the darkest color representing the maximum number of cases confirmed.', 'Explaining the option to edit color to red to green diverging for a more appealing format.', "The total confirmed and recovered cases in different nations are analyzed using Tableau, with a focus on India's recovery rate.", 'The creation of trend lines to forecast the COVID-19 trend using Tableau.']}, {'end': 1431.915, 'segs': [{'end': 1049.949, 'src': 'embed', 'start': 1008.305, 'weight': 0, 'content': [{'end': 1014.629, 'text': 'So in January, we find one OK, this is in billions, maybe.', 'start': 1008.305, 'duration': 6.324}, {'end': 1016.411, 'text': 'Yeah, maybe even trillions.', 'start': 1014.97, 'duration': 1.441}, {'end': 1026.098, 'text': 'Who knows? But but based on the data we have in the last year, we have a decrement of the confirmed cases in January.', 'start': 1016.771, 'duration': 9.327}, {'end': 1032.642, 'text': "So it's basically indicating that Corona is basically or slowly decreasing.", 'start': 1026.157, 'duration': 6.485}, {'end': 1033.643, 'text': "That's a good sign.", 'start': 1032.842, 'duration': 0.801}, {'end': 1040.568, 'text': "Now, now let's try to find out the trend line for India.", 'start': 1036.285, 'duration': 4.283}, {'end': 1049.949, 'text': "let's duplicate this.", 'start': 1042.805, 'duration': 7.144}], 'summary': 'Confirmed cases in january show a decreasing trend, indicating a positive sign for the decreasing impact of corona.', 'duration': 41.644, 'max_score': 1008.305, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g1008305.jpg'}, {'end': 1230.608, 'src': 'embed', 'start': 1164.988, 'weight': 4, 'content': [{'end': 1172.495, 'text': "now let's select a couple of states we know which are in India Arunachal Pradesh, Assam.", 'start': 1164.988, 'duration': 7.507}, {'end': 1180.319, 'text': "Don't forget to hold the control key for this or else the options might vanish.", 'start': 1175.757, 'duration': 4.562}, {'end': 1195.286, 'text': 'We have Bihar.', 'start': 1194.406, 'duration': 0.88}, {'end': 1203.01, 'text': 'We have Chandigarh.', 'start': 1201.909, 'duration': 1.101}, {'end': 1209.154, 'text': 'We have Chhattisgarh.', 'start': 1207.813, 'duration': 1.341}, {'end': 1218.56, 'text': 'We have Dadar and Nagar Haveli, Dayodaman.', 'start': 1215.078, 'duration': 3.482}, {'end': 1221.522, 'text': 'We have Delhi.', 'start': 1220.601, 'duration': 0.921}, {'end': 1230.608, 'text': 'Yeah, we are going to just select a couple of states just to show how a group can be done.', 'start': 1223.083, 'duration': 7.525}], 'summary': 'Selecting states from india like arunachal pradesh, assam, bihar, chandigarh, chhattisgarh, dadar and nagar haveli, dadra and nagar haveli, and delhi to demonstrate group selection.', 'duration': 65.62, 'max_score': 1164.988, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g1164988.jpg'}, {'end': 1393.769, 'src': 'embed', 'start': 1347.486, 'weight': 3, 'content': [{'end': 1348.467, 'text': 'We have West Bengal.', 'start': 1347.486, 'duration': 0.981}, {'end': 1373.606, 'text': "and let's rename the group as Indian States Group Let's select apply and OK.", 'start': 1357.191, 'duration': 16.415}, {'end': 1384.411, 'text': 'So after selecting the apply option and clicking OK, so we can have a new pill in the dimension section that happens to be Indian States Group.', 'start': 1374.287, 'duration': 10.124}, {'end': 1391.054, 'text': "So what we're going to do is drag that pill into detail option so that we can have the results on our screen.", 'start': 1385.091, 'duration': 5.963}, {'end': 1393.769, 'text': 'So there you go.', 'start': 1392.768, 'duration': 1.001}], 'summary': 'Renamed west bengal to indian states group, added as dimension, and displayed results.', 'duration': 46.283, 'max_score': 1347.486, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g1347486.jpg'}], 'start': 1008.305, 'title': 'Covid-19 cases and indian states in tableau', 'summary': "Highlights a decrease in confirmed covid-19 cases in january, with a notable drop in cases in india from over 30 crores to nearly 20 crores. additionally, it demonstrates creating a grouped sheet for indian states in tableau, resulting in a new pill in the dimension section labeled 'indian states group' and displaying the selected states on the screen.", 'chapters': [{'end': 1124.529, 'start': 1008.305, 'title': 'Decrease in covid-19 cases', 'summary': 'Highlights a decrease in confirmed covid-19 cases in january, indicating a slow decrease in the virus, with a notable drop in cases in india from over 30 crores to nearly 20 crores.', 'duration': 116.224, 'highlights': ['The confirmed cases of Covid-19 showed a decrement in January, indicating a slow decrease in the virus.', 'There is a gradual drop of Covid-19 cases in India, with a decrease from over 30 crores to nearly 20 crores.', 'The trend line for India shows a gradual drop of Covid-19 cases, supporting the indication of a decrease in the virus.']}, {'end': 1431.915, 'start': 1126.61, 'title': 'Creating grouped sheet for indian states', 'summary': "Demonstrates how to create a grouped sheet for indian states in tableau, selecting and grouping various indian states, including andaman and nicobar, andhra pradesh, arunachal pradesh, assam, bihar, chandigarh, chhattisgarh, dadar and nagar haveli, daman, delhi, gujarat, haryana, jammu and kashmir, jharkhand, karnataka, kerala, ladakh, lakshadweep, madhya pradesh, maharashtra, nagaland, punjab, rajasthan, tamil nadu, telangana, uttar pradesh, and west bengal, resulting in a new pill in the dimension section labeled 'indian states group' and displaying the selected states on the screen.", 'duration': 305.305, 'highlights': ["The chapter demonstrates how to create a grouped sheet for Indian states in Tableau, selecting and grouping various Indian states, resulting in a new pill in the dimension section labeled 'Indian States Group' and displaying the selected states on the screen.", 'The process involves selecting and grouping various Indian states, including Andaman and Nicobar, Andhra Pradesh, Arunachal Pradesh, Assam, Bihar, Chandigarh, Chhattisgarh, Dadar and Nagar Haveli, Daman, Delhi, Gujarat, Haryana, Jammu and Kashmir, Jharkhand, Karnataka, Kerala, Ladakh, Lakshadweep, Madhya Pradesh, Maharashtra, Nagaland, Punjab, Rajasthan, Tamil Nadu, Telangana, Uttar Pradesh, and West Bengal.', "The new pill in the dimension section is labeled 'Indian States Group' and displays the selected states on the screen."]}], 'duration': 423.61, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g1008305.jpg', 'highlights': ['The confirmed cases of Covid-19 showed a decrement in January, indicating a slow decrease in the virus.', 'There is a gradual drop of Covid-19 cases in India, with a decrease from over 30 crores to nearly 20 crores.', 'The trend line for India shows a gradual drop of Covid-19 cases, supporting the indication of a decrease in the virus.', "The chapter demonstrates how to create a grouped sheet for Indian states in Tableau, selecting and grouping various Indian states, resulting in a new pill in the dimension section labeled 'Indian States Group' and displaying the selected states on the screen.", 'The process involves selecting and grouping various Indian states, including Andaman and Nicobar, Andhra Pradesh, Arunachal Pradesh, Assam, Bihar, Chandigarh, Chhattisgarh, Dadar and Nagar Haveli, Daman, Delhi, Gujarat, Haryana, Jammu and Kashmir, Jharkhand, Karnataka, Kerala, Ladakh, Lakshadweep, Madhya Pradesh, Maharashtra, Nagaland, Punjab, Rajasthan, Tamil Nadu, Telangana, Uttar Pradesh, and West Bengal.', "The new pill in the dimension section is labeled 'Indian States Group' and displays the selected states on the screen."]}, {'end': 1967.808, 'segs': [{'end': 1495.297, 'src': 'embed', 'start': 1469.043, 'weight': 1, 'content': [{'end': 1473.105, 'text': "Now, let's quickly get back to our presentation and check out our next query.", 'start': 1469.043, 'duration': 4.062}, {'end': 1476.846, 'text': 'So find the highest death rates at international level.', 'start': 1473.585, 'duration': 3.261}, {'end': 1486.77, 'text': '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.', 'start': 1477.186, 'duration': 9.584}, {'end': 1491.073, 'text': "So which is the safest country? Now, let's get back to Tableau.", 'start': 1486.89, 'duration': 4.183}, {'end': 1493.875, 'text': "Now, we're not going to mess with this particular sheet.", 'start': 1491.613, 'duration': 2.262}, {'end': 1495.297, 'text': "Let's create a new sheet.", 'start': 1494.016, 'duration': 1.281}], 'summary': 'Analyzing international death rates to determine safest country.', 'duration': 26.254, 'max_score': 1469.043, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g1469043.jpg'}, {'end': 1620.048, 'src': 'heatmap', 'start': 1517.99, 'weight': 0.786, 'content': [{'end': 1529.955, 'text': "let's drag in country and let's drag in confirm cases.", 'start': 1517.99, 'duration': 11.965}, {'end': 1532.076, 'text': 'so we have a map over here.', 'start': 1529.955, 'duration': 2.121}, {'end': 1539.339, 'text': 'so tableau basically kind of selected the map as default.', 'start': 1532.076, 'duration': 7.263}, {'end': 1546.606, 'text': 'we can drag the text and Now we can actually change this to a text shot.', 'start': 1539.339, 'duration': 7.267}, {'end': 1561.331, 'text': "now let's drag the measure names into rows.", 'start': 1557.228, 'duration': 4.103}, {'end': 1563.012, 'text': 'so we have a little bit more.', 'start': 1561.331, 'duration': 1.681}, {'end': 1565.674, 'text': 'you know, sorted kind of data.', 'start': 1563.012, 'duration': 2.662}, {'end': 1570.037, 'text': 'so you can see we have the confirm cases over here and that traits here.', 'start': 1565.674, 'duration': 4.363}, {'end': 1581.806, 'text': 'now if we kind of sort it in the descending order, yep.', 'start': 1570.037, 'duration': 11.769}, {'end': 1585.289, 'text': 'so the order is being changed now.', 'start': 1581.806, 'duration': 3.483}, {'end': 1586.049, 'text': 'so we have.', 'start': 1585.289, 'duration': 0.76}, {'end': 1591.506, 'text': 'So we have our charts processed by Tableau for a better visual.', 'start': 1587.403, 'duration': 4.103}, {'end': 1596.511, 'text': 'So our chart got rearranged or ordered in the descending order.', 'start': 1591.867, 'duration': 4.644}, {'end': 1603.216, 'text': 'So with that, we have the highest deaths and confirmed cases in the US.', 'start': 1597.091, 'duration': 6.125}, {'end': 1613.925, 'text': 'So we can even do that using a parameter where you can create the top 10 or top five nations with highest confirmed and death values.', 'start': 1603.436, 'duration': 10.489}, {'end': 1620.048, 'text': 'So for that you can drag both.', 'start': 1615.126, 'duration': 4.922}], 'summary': 'Using tableau, we visualized and sorted confirmed cases and deaths, finding the highest values in the us.', 'duration': 102.058, 'max_score': 1517.99, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g1517990.jpg'}, {'end': 1620.048, 'src': 'embed', 'start': 1587.403, 'weight': 0, 'content': [{'end': 1591.506, 'text': 'So we have our charts processed by Tableau for a better visual.', 'start': 1587.403, 'duration': 4.103}, {'end': 1596.511, 'text': 'So our chart got rearranged or ordered in the descending order.', 'start': 1591.867, 'duration': 4.644}, {'end': 1603.216, 'text': 'So with that, we have the highest deaths and confirmed cases in the US.', 'start': 1597.091, 'duration': 6.125}, {'end': 1613.925, 'text': 'So we can even do that using a parameter where you can create the top 10 or top five nations with highest confirmed and death values.', 'start': 1603.436, 'duration': 10.489}, {'end': 1620.048, 'text': 'So for that you can drag both.', 'start': 1615.126, 'duration': 4.922}], 'summary': 'Tableau processed charts show us has highest deaths & confirmed cases.', 'duration': 32.645, 'max_score': 1587.403, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g1587403.jpg'}, {'end': 1768.65, 'src': 'embed', 'start': 1744.141, 'weight': 2, 'content': [{'end': 1754.87, 'text': 'So, after changing some arrangements or by making an ascending arrangement and changing the layout or the orientation and everything,', 'start': 1744.141, 'duration': 10.729}, {'end': 1763.217, 'text': 'we have our final result, which states that we have the least number of deaths and confirmations of COVID-19 in the country of Afghanistan.', 'start': 1754.87, 'duration': 8.347}, {'end': 1768.65, 'text': 'So, yeah, so we have the pretty well sorted arranged data over here on the screen.', 'start': 1764.249, 'duration': 4.401}], 'summary': 'Afghanistan has the least covid-19 deaths and confirmations.', 'duration': 24.509, 'max_score': 1744.141, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g1744141.jpg'}, {'end': 1865.595, 'src': 'embed', 'start': 1842.557, 'weight': 3, 'content': [{'end': 1851.043, 'text': "Now let's sort it in the descending order so that we can find out maximum variation which is happening in France.", 'start': 1842.557, 'duration': 8.486}, {'end': 1854.626, 'text': 'so of course there are less number of confirmed cases,', 'start': 1851.043, 'duration': 3.583}, {'end': 1865.595, 'text': 'but there is a lot of variation which states that they have something wrong with the climatic conditions or the weather conditions there.', 'start': 1854.626, 'duration': 10.969}], 'summary': 'France has low confirmed cases but significant variation, suggesting climate or weather issues.', 'duration': 23.038, 'max_score': 1842.557, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g1842557.jpg'}, {'end': 1926.43, 'src': 'embed', 'start': 1895.85, 'weight': 4, 'content': [{'end': 1901.652, 'text': "yeah, that's how we can find the variation of presence of cover 19 in a particular country.", 'start': 1895.85, 'duration': 5.802}, {'end': 1905.782, 'text': "So with that let's move into the next query.", 'start': 1902.461, 'duration': 3.321}, {'end': 1913.305, 'text': 'So the next query is, can we forecast the sheet of future and reference of COVID-19 presence? Yes, we can do that.', 'start': 1905.882, 'duration': 7.423}, {'end': 1915.046, 'text': "Let's get back to TableView.", 'start': 1913.365, 'duration': 1.681}, {'end': 1926.43, 'text': "For that, let's create a new sheet and rename it as forecast of COVID-19 presence.", 'start': 1916.166, 'duration': 10.264}], 'summary': "Forecast covid-19 presence and variation in a country's coverage can be determined using data analysis.", 'duration': 30.58, 'max_score': 1895.85, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g1895850.jpg'}], 'start': 1436.997, 'title': 'Covid-19 data analysis', 'summary': 'Discusses using tableau to visualize and analyze covid-19 data, identifying the highest and least death rates at the international level, sorting the data to find the highest deaths and confirmed cases in the us, and forecasting future covid-19 presence.', 'chapters': [{'end': 1684.18, 'start': 1436.997, 'title': 'Tableau data analysis', 'summary': 'Discusses using tableau to visualize and analyze covid-19 data, finding the highest and least death rates at the international level, and sorting the data to identify the highest deaths and confirmed cases in the us.', 'duration': 247.183, 'highlights': ['Using Tableau to visualize and analyze COVID-19 data, including finding the highest and least death rates at the international level', 'Identifying the highest deaths and confirmed cases in the US by sorting the data in descending order', 'Renaming and creating new sheets in Tableau to analyze COVID-19 data']}, {'end': 1967.808, 'start': 1684.18, 'title': 'Covid-19 variations analysis', 'summary': 'Discusses the process of sorting and arranging covid-19 data to identify countries with the least number of cases and deaths, creating a visualization to show the variation in covid-19 cases around the world, and exploring the possibility of forecasting future covid-19 presence.', 'duration': 283.628, 'highlights': ['The least number of deaths and confirmed cases of COVID-19 are found in the country of Afghanistan after sorting and rearranging the data. Afghanistan has the least number of deaths and confirmed cases of COVID-19, indicating successful containment efforts.', 'France shows the maximum variation in COVID-19 cases, despite having fewer confirmed cases than the US, indicating potential issues with climatic or weather conditions. France exhibits the highest variation in confirmed COVID-19 cases, suggesting potential environmental factors contributing to the variation.', "Exploring the possibility of forecasting future COVID-19 presence using Tableau by creating a new sheet and renaming it as 'forecast of COVID-19 presence'. The process of creating a new sheet and renaming it for forecasting future COVID-19 presence is discussed."]}], 'duration': 530.811, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g1436997.jpg', 'highlights': ['Identifying the highest deaths and confirmed cases in the US by sorting the data in descending order', 'Using Tableau to visualize and analyze COVID-19 data, including finding the highest and least death rates at the international level', 'The least number of deaths and confirmed cases of COVID-19 are found in the country of Afghanistan after sorting and rearranging the data', 'France shows the maximum variation in COVID-19 cases, despite having fewer confirmed cases than the US, indicating potential issues with climatic or weather conditions', "Exploring the possibility of forecasting future COVID-19 presence using Tableau by creating a new sheet and renaming it as 'forecast of COVID-19 presence'"]}, {'end': 2399.608, 'segs': [{'end': 2014.126, 'src': 'embed', 'start': 1969.33, 'weight': 0, 'content': [{'end': 1973.653, 'text': "Now let's select this to day.", 'start': 1969.33, 'duration': 4.323}, {'end': 1979.318, 'text': 'We can change that to year.', 'start': 1975.795, 'duration': 3.523}, {'end': 1985.562, 'text': "Now let's select forecast option.", 'start': 1983.301, 'duration': 2.261}, {'end': 1988.685, 'text': "Yeah, so this is how it's going to be.", 'start': 1985.823, 'duration': 2.862}, {'end': 1994.221, 'text': 'So in the year of 2020, we had the confirmed cases around this number, which is 7637053464.', 'start': 1990.06, 'duration': 4.161}, {'end': 1995.522, 'text': 'So which is nearly 76, 370 lakh.', 'start': 1994.221, 'duration': 1.301}, {'end': 1999.683, 'text': 'And in the 2021, the number got a little decreased.', 'start': 1995.582, 'duration': 4.101}, {'end': 2014.126, 'text': 'which is 17, 130 lakh cases.', 'start': 2010.762, 'duration': 3.364}], 'summary': 'In 2020, there were 76.37 billion confirmed cases, decreasing to 17.13 billion in 2021.', 'duration': 44.796, 'max_score': 1969.33, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g1969330.jpg'}, {'end': 2066.54, 'src': 'embed', 'start': 2042.226, 'weight': 1, 'content': [{'end': 2048.009, 'text': 'so yeah, if we get back to the presentation mode, so all the queries on the covet 19 data are finished.', 'start': 2042.226, 'duration': 5.783}, {'end': 2049.469, 'text': "now let's create a dashboard.", 'start': 2048.009, 'duration': 1.46}, {'end': 2055.793, 'text': 'Yeah, we have the dashboard right now, so we can change the layout of dashboard.', 'start': 2051.971, 'duration': 3.822}, {'end': 2063.737, 'text': 'Let me increase the width to 1320 and decrease the height to 70 or 760.', 'start': 2055.833, 'duration': 7.904}, {'end': 2066.54, 'text': 'So we have the entire screen right now.', 'start': 2063.737, 'duration': 2.803}], 'summary': 'Queries on covid-19 data finished, creating dashboard with adjusted layout for screen.', 'duration': 24.314, 'max_score': 2042.226, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g2042226.jpg'}, {'end': 2282.144, 'src': 'embed', 'start': 2242.616, 'weight': 2, 'content': [{'end': 2243.296, 'text': 'Yeah, this is good.', 'start': 2242.616, 'duration': 0.68}, {'end': 2245.957, 'text': 'So this is how we can have the dashboard.', 'start': 2244.036, 'duration': 1.921}, {'end': 2249.539, 'text': "And now let's create another dashboard for Indian results.", 'start': 2246.378, 'duration': 3.161}, {'end': 2256.823, 'text': "So again, let's change the dimensions of the screen.", 'start': 2250.34, 'duration': 6.483}, {'end': 2260.419, 'text': "It's pretty good.", 'start': 2259.879, 'duration': 0.54}, {'end': 2268.841, 'text': "Now let's take the confirmed cases in India and drop it over here.", 'start': 2260.999, 'duration': 7.842}, {'end': 2272.602, 'text': 'And recovery cases in India and drop it over there.', 'start': 2269.341, 'duration': 3.261}, {'end': 2276.243, 'text': 'And trend lines in India over here.', 'start': 2272.622, 'duration': 3.621}, {'end': 2282.144, 'text': 'And Indian states.', 'start': 2276.263, 'duration': 5.881}], 'summary': 'Creating dashboards for indian covid-19 data with confirmed and recovery cases, trend lines, and state information.', 'duration': 39.528, 'max_score': 2242.616, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g2242616.jpg'}, {'end': 2404.048, 'src': 'embed', 'start': 2376.714, 'weight': 3, 'content': [{'end': 2382.139, 'text': 'What are the total number of flights which are taking off in a day from the San Francisco airport?', 'start': 2376.714, 'duration': 5.425}, {'end': 2389.265, 'text': 'and followed by that, we have the next query, which reads out find the busiest day of San Francisco airport.', 'start': 2382.139, 'duration': 7.126}, {'end': 2399.608, 'text': "we'll be finding out the top five busiest air days in the san francisco airport and followed by that we'll also find what are the total number of flights per day in a month.", 'start': 2390.006, 'duration': 9.602}, {'end': 2404.048, 'text': "then we'll find out what are the top 10 busiest flight routes.", 'start': 2399.608, 'duration': 4.44}], 'summary': 'San francisco airport handles numerous daily flights, busiest days, and top flight routes.', 'duration': 27.334, 'max_score': 2376.714, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g2376714.jpg'}], 'start': 1969.33, 'title': 'Covid-19 analysis and forecasting', 'summary': 'Discusses covid-19 forecasting in india, with confirmed cases reaching 7637 million in 2020, 1713 million in 2021, and a further decrease in 2022. it also covers the analysis of airline data, including the total number of flights and busiest days at san francisco airport.', 'chapters': [{'end': 2066.54, 'start': 1969.33, 'title': 'Covid-19 forecast in india', 'summary': 'Discusses the forecasted covid-19 cases in india, with confirmed cases reaching 7637 million in 2020, 1713 million in 2021, and a further decrease in 2022, indicating a positive trend. the presentation mode and dashboard layout adjustments are also discussed.', 'duration': 97.21, 'highlights': ['Confirmed COVID-19 cases in India were 7637 million in 2020 and 1713 million in 2021, with a forecasted decrease in 2022, signifying a positive trend. In 2020, India had confirmed cases around 7637053464 (nearly 7637 million), and in 2021, the number decreased to 1713 million. The forecast for the end of 2022 indicates a further drop, suggesting a positive trend in COVID-19 cases.', 'Adjustments to the presentation mode and dashboard layout were discussed, including changing the width to 1320 and the height to 760 for the entire screen. The presenter discussed finishing all queries on the COVID-19 data in presentation mode and proceeded to create a dashboard. They made specific adjustments, such as changing the width to 1320 and decreasing the height to 760 for the entire screen.']}, {'end': 2399.608, 'start': 2067.58, 'title': 'Covid-19 and airline data analysis', 'summary': 'Discusses creating dashboards for covid-19 international and indian data and then transitions to analyzing airline data, including finding the total number of flights, the busiest days at san francisco airport, and the total number of flights per day in a month.', 'duration': 332.028, 'highlights': ['Creating dashboards for COVID-19 international and Indian data, including confirmed cases, recovery cases, trend lines, and Indian states.', 'Analyzing airline data to find the total number of flights taking off from San Francisco airport in a day, the busiest days, and the total number of flights per day in a month.']}], 'duration': 430.278, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g1969330.jpg', 'highlights': ['Confirmed COVID-19 cases in India were 7637 million in 2020 and 1713 million in 2021, with a forecasted decrease in 2022, signifying a positive trend.', 'Adjustments to the presentation mode and dashboard layout were discussed, including changing the width to 1320 and the height to 760 for the entire screen.', 'Creating dashboards for COVID-19 international and Indian data, including confirmed cases, recovery cases, trend lines, and Indian states.', 'Analyzing airline data to find the total number of flights taking off from San Francisco airport in a day, the busiest days, and the total number of flights per day in a month.']}, {'end': 3174.672, 'segs': [{'end': 2426.837, 'src': 'embed', 'start': 2399.608, 'weight': 2, 'content': [{'end': 2404.048, 'text': "then we'll find out what are the top 10 busiest flight routes.", 'start': 2399.608, 'duration': 4.44}, {'end': 2410.33, 'text': "then we'll find out what are the top 10 longest flight routes from san francisco airport.", 'start': 2404.048, 'duration': 6.282}, {'end': 2418.231, 'text': 'then we have to represent the flights flying outside the san francisco towards different parts of the world using a map chart.', 'start': 2410.33, 'duration': 7.901}, {'end': 2421.853, 'text': "So these are the queries that we'll be executing in our second project.", 'start': 2419.091, 'duration': 2.762}, {'end': 2424.335, 'text': "Without further ado, let's get back to the Tableau.", 'start': 2421.993, 'duration': 2.342}, {'end': 2426.837, 'text': 'So now we are back on the Tableau dashboard.', 'start': 2424.675, 'duration': 2.162}], 'summary': 'Analyzing top 10 busiest and longest flight routes from san francisco airport using tableau.', 'duration': 27.229, 'max_score': 2399.608, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g2399608.jpg'}, {'end': 3002.314, 'src': 'embed', 'start': 2907.922, 'weight': 0, 'content': [{'end': 2910.564, 'text': 'So, we can actually make a set of these.', 'start': 2907.922, 'duration': 2.642}, {'end': 2913.965, 'text': 'The set of these, which happens to be in the March.', 'start': 2911.704, 'duration': 2.261}, {'end': 2918.287, 'text': 'So, March happens to be the busiest month for San Francisco airport.', 'start': 2914.225, 'duration': 4.062}, {'end': 2920.668, 'text': 'So, with that, we have finished the second query.', 'start': 2918.647, 'duration': 2.021}, {'end': 2922.989, 'text': "Now, let's create a new sheet for our third query.", 'start': 2920.708, 'duration': 2.281}, {'end': 2924.47, 'text': "Let's get back to the presentation.", 'start': 2923.029, 'duration': 1.441}, {'end': 2930.632, 'text': 'the third query reads that what are the total number of flights per day in a month?', 'start': 2925.49, 'duration': 5.142}, {'end': 2935.573, 'text': "so for that, let's get back to tableau.", 'start': 2930.632, 'duration': 4.941}, {'end': 2947.256, 'text': "let's try to rename it total flights in a month.", 'start': 2935.573, 'duration': 11.683}, {'end': 2960.123, 'text': "done so for that, let's select date and drag it to columns and let's make it to month.", 'start': 2947.256, 'duration': 12.867}, {'end': 2964.968, 'text': "let's remove this, let's remove this.", 'start': 2960.123, 'duration': 4.845}, {'end': 2966.43, 'text': "let's remove this as well.", 'start': 2964.968, 'duration': 1.462}, {'end': 2971.976, 'text': "now let's check it to day and now number of flights.", 'start': 2966.43, 'duration': 5.546}, {'end': 2982.002, 'text': 'So automatically we have a line chart and we have the flights taking off from March 1st to March 31st,', 'start': 2973.757, 'duration': 8.245}, {'end': 2985.824, 'text': 'which happens to be the busiest month for San Francisco Airport.', 'start': 2982.002, 'duration': 3.822}, {'end': 2991.708, 'text': "Now let's just tick the show mark label so that we have the number of flights taking off every day.", 'start': 2986.325, 'duration': 5.383}, {'end': 3001.193, 'text': 'So, as we got the result in the previous sheet, 3, 295 flights on the date of sixth march.', 'start': 2992.408, 'duration': 8.785}, {'end': 3002.314, 'text': 'or is it third march?', 'start': 3001.193, 'duration': 1.121}], 'summary': 'March is the busiest month for san francisco airport with 3,295 flights on march 6th.', 'duration': 94.392, 'max_score': 2907.922, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g2907922.jpg'}], 'start': 2399.608, 'title': 'Air and airport data analysis', 'summary': "Covers executing queries in tableau to find top 10 busiest flight routes, analyzing san francisco airport's flight data in 2020, and identifying the busiest day with 3,295 flights on 6th march.", 'chapters': [{'end': 2873.315, 'start': 2399.608, 'title': 'Air travel data analysis', 'summary': 'Focuses on executing queries in tableau to find the top 10 busiest flight routes, splitting the root column into origin and destination, and creating visualizations to determine the total number of flights per day and the busiest day at san francisco airport.', 'duration': 473.707, 'highlights': ['Executing query to find the busiest day at San Francisco airport Determining the busiest day by analyzing the top 10 days with the highest number of flights taking off', 'Creating visualizations to determine the total number of flights per day Using Tableau to calculate the total number of flights per day taking off from San Francisco airport', 'Splitting the root column into origin and destination Splitting the root column to obtain separate fields for origin and destination of flights', 'Executing query to find the top 10 busiest flight routes Identifying the top 10 busiest flight routes based on the number of flights']}, {'end': 3174.672, 'start': 2873.475, 'title': 'Airport data analysis', 'summary': "Covers the analysis of san francisco airport's flight data in the year 2020, identifying the busiest day, month, and top 10 busiest flight routes, with the busiest day recording 3,295 flights on 6th march.", 'duration': 301.197, 'highlights': ['The busiest day in the year 2020 for San Francisco Airport was 6th March with 3,295 flights taking off. Identifying the busiest day with quantifiable data.', 'March was identified as the busiest month for San Francisco Airport. Highlighting the busiest month with quantifiable data.', 'The analysis revealed the top 10 busiest flight routes from San Francisco Airport. Identifying the top 10 busiest flight routes for the airport.']}], 'duration': 775.064, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g2399608.jpg', 'highlights': ['Identifying the busiest day in 2020 for San Francisco Airport as 6th March with 3,295 flights taking off.', 'Determining the busiest month for San Francisco Airport as March with quantifiable data.', 'Identifying the top 10 busiest flight routes based on the number of flights.', 'Creating visualizations to determine the total number of flights per day using Tableau.']}, {'end': 3653.171, 'segs': [{'end': 3209.266, 'src': 'embed', 'start': 3176.952, 'weight': 1, 'content': [{'end': 3185.154, 'text': "So, to find out the longest routes, we'll create a new sheet and rename it as busiest.", 'start': 3176.952, 'duration': 8.202}, {'end': 3188.335, 'text': 'no, not busiest longest longest routes.', 'start': 3185.154, 'duration': 3.181}, {'end': 3197.174, 'text': 'Yeah The sheet is renamed and you can see that we have geometry coordinates 0, 0, 0, 1, 1, 0 and 1, 1.', 'start': 3189.535, 'duration': 7.639}, {'end': 3209.266, 'text': '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.', 'start': 3197.175, 'duration': 12.091}], 'summary': 'Creating a new sheet to find longest routes with origin and destination coordinates.', 'duration': 32.314, 'max_score': 3176.952, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g3176952.jpg'}, {'end': 3292.885, 'src': 'embed', 'start': 3256.538, 'weight': 0, 'content': [{'end': 3260.14, 'text': "now let's create another for destination.", 'start': 3256.538, 'duration': 3.602}, {'end': 3275.694, 'text': 'we are creating a calculated field, destination and inside destination we are going to use the same make point and geo metric coordinates zero,', 'start': 3260.14, 'duration': 15.554}, {'end': 3277.115, 'text': 'zero comma.', 'start': 3275.694, 'duration': 1.421}, {'end': 3284.739, 'text': 'Geometric coordinates zero one And select apply.', 'start': 3277.115, 'duration': 7.624}, {'end': 3289.122, 'text': 'okay, Now the origin and destination are created now.', 'start': 3284.739, 'duration': 4.383}, {'end': 3292.885, 'text': 'We need to create another calculated field for distance.', 'start': 3289.182, 'duration': 3.703}], 'summary': 'Creating calculated fields for destination and distance.', 'duration': 36.347, 'max_score': 3256.538, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g3256538.jpg'}, {'end': 3402.093, 'src': 'embed', 'start': 3339.811, 'weight': 2, 'content': [{'end': 3349.079, 'text': "oh, there's no problem, we can actually change the orientation and now let's rearrange it in the form of descending order.", 'start': 3339.811, 'duration': 9.268}, {'end': 3356.67, 'text': 'Now we have the distance sorted in the descending order, but there is a small change.', 'start': 3350.407, 'duration': 6.263}, {'end': 3360.971, 'text': 'We have to change the sum to average.', 'start': 3357.15, 'duration': 3.821}, {'end': 3365.713, 'text': 'So once you change that, you want to arrange it again.', 'start': 3362.752, 'duration': 2.961}, {'end': 3371.795, 'text': 'Now we have the BLR Bangalore as the farthest airport from SFO.', 'start': 3365.913, 'duration': 5.882}, {'end': 3380.241, 'text': 'Now we might want to drag the busy into filters again.', 'start': 3372.756, 'duration': 7.485}, {'end': 3384.164, 'text': 'now we have the top 10 apply.', 'start': 3380.241, 'duration': 3.923}, {'end': 3388.746, 'text': 'okay, so we have the top 10 longest routes from sfo.', 'start': 3384.164, 'duration': 4.582}, {'end': 3392.008, 'text': 'so with that we have, uh, finished our fifth query.', 'start': 3388.746, 'duration': 3.262}, {'end': 3399.452, 'text': "let's get back to presentation mode and the sixth query represent the flights flying outside sfo towards different parts of the world.", 'start': 3392.008, 'duration': 7.444}, {'end': 3400.612, 'text': 'yeah, that can be done.', 'start': 3399.452, 'duration': 1.16}, {'end': 3402.093, 'text': "let's get back to tableau again.", 'start': 3400.612, 'duration': 1.481}], 'summary': 'Sorted distance in descending order, found blr as farthest airport from sfo, identified top 10 longest routes.', 'duration': 62.282, 'max_score': 3339.811, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g3339811.jpg'}, {'end': 3526.857, 'src': 'embed', 'start': 3488.423, 'weight': 4, 'content': [{'end': 3495.006, 'text': 'okay, now we have the newly created flight line over here.', 'start': 3488.423, 'duration': 6.583}, {'end': 3500.048, 'text': "now we'll drag that flight line to detail.", 'start': 3495.006, 'duration': 5.042}, {'end': 3509.672, 'text': 'now, once we drag that flight line to the detail, we have the lines or flights taking off from sfo to different parts of the world.', 'start': 3500.048, 'duration': 9.624}, {'end': 3526.857, 'text': 'now we can make it look a bit more appealing or more informative by dragging the routes or, yeah, into detail.', 'start': 3509.672, 'duration': 17.185}], 'summary': 'New flight line created, showcasing flights from sfo to various parts of the world.', 'duration': 38.434, 'max_score': 3488.423, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g3488423.jpg'}, {'end': 3653.171, 'src': 'embed', 'start': 3622.808, 'weight': 3, 'content': [{'end': 3626.79, 'text': 'we have the flights taking off in the month of march.', 'start': 3622.808, 'duration': 3.982}, {'end': 3630.931, 'text': 'the busiest month was the march and the busiest day was 6th of march.', 'start': 3626.79, 'duration': 4.141}, {'end': 3633.552, 'text': "i don't know what was so special on that day.", 'start': 3630.931, 'duration': 2.621}, {'end': 3636.214, 'text': 'if you know it, please let me know in the comment section below.', 'start': 3633.552, 'duration': 2.662}, {'end': 3639.155, 'text': 'and yeah, so totally.', 'start': 3636.214, 'duration': 2.941}, {'end': 3640.495, 'text': 'we created a dashboard.', 'start': 3639.155, 'duration': 1.34}, {'end': 3653.171, 'text': "now let's rename the dashboard as SFO Flight Data Dashboard and we are done.", 'start': 3640.495, 'duration': 12.676}], 'summary': 'March was the busiest month for flights, with the 6th being the busiest day. a dashboard named sfo flight data dashboard was created.', 'duration': 30.363, 'max_score': 3622.808, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g3622808.jpg'}], 'start': 3176.952, 'title': 'Calculating longest routes and sfo flight data dashboard', 'summary': 'Involves creating calculated fields for origin and destination using geometry coordinates to calculate the distance in kilometers and plotting the busiest routes against the distance measures. additionally, it includes creating a tableau dashboard to analyze sfo flight data, finding the farthest airport from sfo, identifying the top 10 longest routes, and visualizing flights taking off from sfo on a map.', 'chapters': [{'end': 3339.811, 'start': 3176.952, 'title': 'Calculating longest routes', 'summary': 'Involves creating calculated fields for origin and destination using geometry coordinates to calculate the distance in kilometers and plotting the busiest routes against the distance measures in the measure section.', 'duration': 162.859, 'highlights': ['Creating calculated fields for origin and destination using geometry coordinates to calculate the distance Involves using makepoint and distance functions to calculate origin and destination coordinates. The distance is represented in kilometers.', 'Plotting the busiest routes against the distance measures in the measure section The chapter involves plotting the busiest routes against the distance measures in the measure section to visualize the longest routes.']}, {'end': 3653.171, 'start': 3339.811, 'title': 'Sfo flight data dashboard', 'summary': 'Involves creating a dashboard in tableau to analyze sfo flight data, including finding the farthest airport from sfo, identifying the top 10 longest routes, and visualizing flights taking off from sfo on a map.', 'duration': 313.36, 'highlights': ['The farthest airport from SFO is BLR Bangalore.', 'Identified the top 10 longest routes from SFO.', 'Created a map visualization of flights taking off from SFO, including details such as routes and distances.', 'Generated a dashboard displaying busiest routes, longest routes, and flights taking off in the month of March.']}], 'duration': 476.219, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g3176952.jpg', 'highlights': ['Creating calculated fields for origin and destination using geometry coordinates to calculate the distance in kilometers', 'Plotting the busiest routes against the distance measures to visualize the longest routes', 'Identified the top 10 longest routes from SFO', 'Generated a dashboard displaying busiest routes, longest routes, and flights taking off in the month of March', 'Created a map visualization of flights taking off from SFO, including details such as routes and distances', 'The farthest airport from SFO is BLR Bangalore']}, {'end': 4364.639, 'segs': [{'end': 3703.48, 'src': 'embed', 'start': 3675.156, 'weight': 0, 'content': [{'end': 3677.577, 'text': "So we're going to find out what are the average temperature?", 'start': 3675.156, 'duration': 2.421}, {'end': 3679.599, 'text': 'details of the launch sites.', 'start': 3677.577, 'duration': 2.022}, {'end': 3681.1, 'text': 'what are the average wind speed?', 'start': 3679.599, 'duration': 1.501}, {'end': 3682.441, 'text': 'details of the launch sites.', 'start': 3681.1, 'duration': 1.341}, {'end': 3683.622, 'text': 'what are the average humidity?', 'start': 3682.441, 'duration': 1.181}, {'end': 3684.882, 'text': 'details of the launch sites.', 'start': 3683.622, 'duration': 1.26}, {'end': 3689.886, 'text': 'So we need all these to, you know, before launching a satellite or a rocket into space.', 'start': 3685.283, 'duration': 4.603}, {'end': 3692.208, 'text': 'Everything needs to be in ideal condition.', 'start': 3690.146, 'duration': 2.062}, {'end': 3698.114, 'text': 'So, followed by that, we have what are the different varieties of launch vehicles used by different companies.', 'start': 3692.828, 'duration': 5.286}, {'end': 3700.136, 'text': 'So, there are a lot many companies.', 'start': 3698.154, 'duration': 1.982}, {'end': 3701.578, 'text': 'We are from government sector.', 'start': 3700.317, 'duration': 1.261}, {'end': 3703.48, 'text': 'We are from private sector.', 'start': 3701.598, 'duration': 1.882}], 'summary': 'Researching average temperature, wind speed, and humidity at launch sites to ensure ideal conditions before satellite or rocket launch.', 'duration': 28.324, 'max_score': 3675.156, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g3675156.jpg'}, {'end': 3783.046, 'src': 'embed', 'start': 3754.286, 'weight': 1, 'content': [{'end': 3755.988, 'text': "Now, we're going to extract the dataset.", 'start': 3754.286, 'duration': 1.702}, {'end': 3759.532, 'text': 'So, the dataset we need is the Space Machines dataset.', 'start': 3756.228, 'duration': 3.304}, {'end': 3765.621, 'text': 'You can get this in the Kaggle or you can even have the access to this dataset from the description box below.', 'start': 3759.553, 'duration': 6.068}, {'end': 3767.243, 'text': 'Select Open to open the data.', 'start': 3765.661, 'duration': 1.582}, {'end': 3770.957, 'text': 'So, yeah, the data got successfully loaded.', 'start': 3768.835, 'duration': 2.122}, {'end': 3781.025, 'text': "Again, use the interpreter and it's a good habit of using the interpreter to clean your data and make everything understandable or look understandable.", 'start': 3771.257, 'duration': 9.768}, {'end': 3783.046, 'text': 'Show all the answers, everything is fine.', 'start': 3781.385, 'duration': 1.661}], 'summary': 'Extracted space machines dataset successfully and loaded data using interpreter.', 'duration': 28.76, 'max_score': 3754.286, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g3754286.jpg'}, {'end': 3963.128, 'src': 'embed', 'start': 3929.444, 'weight': 3, 'content': [{'end': 3939.92, 'text': 'yeah, so the wind speeds at uh kennedy space center are here 20 miles and 23 at vandenberg And Marshall at 9..', 'start': 3929.444, 'duration': 10.476}, {'end': 3944.322, 'text': 'Yeah, so this is the wind speeds at different launch sites.', 'start': 3939.92, 'duration': 4.402}, {'end': 3948.123, 'text': "Now let's get back to the presentation mode.", 'start': 3944.982, 'duration': 3.141}, {'end': 3951.784, 'text': 'And now we have to find the humidity details of launch sites.', 'start': 3948.663, 'duration': 3.121}, {'end': 3954.325, 'text': "So let's get back to Tableau.", 'start': 3953.005, 'duration': 1.32}, {'end': 3955.586, 'text': 'We are back on Tableau.', 'start': 3954.345, 'duration': 1.241}, {'end': 3963.128, 'text': "Let's rename it Humidity Launch Site.", 'start': 3955.646, 'duration': 7.482}], 'summary': 'Wind speeds: kennedy 20mph, vandenberg 23mph, marshall 9mph. searching humidity details.', 'duration': 33.684, 'max_score': 3929.444, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g3929444.jpg'}, {'end': 4302.875, 'src': 'embed', 'start': 4240.853, 'weight': 2, 'content': [{'end': 4249.656, 'text': "Now let's create a new dashboard as we always do change the resolution according to the monitor we have.", 'start': 4240.853, 'duration': 8.803}, {'end': 4253.177, 'text': "So I'm going to use 1030p and height as 760.", 'start': 4249.996, 'duration': 3.181}, {'end': 4261.8, 'text': "Now let's drag the sheets.", 'start': 4253.177, 'duration': 8.623}, {'end': 4286.623, 'text': 'So we have the launch temperatures, launch wind speeds, and launch site humidity at one place.', 'start': 4279.938, 'duration': 6.685}, {'end': 4296.29, 'text': 'Now the launch vehicles used, mission status, and the track records.', 'start': 4287.764, 'duration': 8.526}, {'end': 4302.875, 'text': "So we'll kind of drag it here.", 'start': 4299.352, 'duration': 3.523}], 'summary': 'Create a new dashboard with 1030p x 760 resolution, combining launch data and track records.', 'duration': 62.022, 'max_score': 4240.853, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g4240853.jpg'}], 'start': 3653.391, 'title': 'Space missions analysis', 'summary': 'Covers the analysis of space missions dataset to gather insights on average temperature, wind speed, humidity, launch vehicles, mission status, and track records of launch sites, ensuring ideal conditions before launching satellites or rockets. it also demonstrates the creation of a tableau dashboard to analyze launch site statistics.', 'chapters': [{'end': 3795.015, 'start': 3653.391, 'title': 'Space missions insights', 'summary': 'Covers the third project which entails analyzing the space missions dataset to gather insights on average temperature, wind speed, humidity, launch vehicles, mission status, and track records of launch sites, aiming to ensure ideal conditions before launching satellites or rockets into space.', 'duration': 141.624, 'highlights': ['The project involves analyzing the Space Missions dataset to gather insights on average temperature, wind speed, humidity, launch vehicles, mission status, and track records of launch sites. The chapter discusses the analysis of the Space Missions dataset to obtain insights on average temperature, wind speed, humidity, launch vehicles, mission status, and track records of launch sites.', 'The chapter emphasizes the importance of ensuring ideal conditions before launching satellites or rockets into space. It emphasizes the significance of ensuring ideal conditions before launching satellites or rockets into space to ensure successful missions.', 'The dataset is obtained from Kaggle and is successfully loaded for further analysis. The dataset is obtained from Kaggle and successfully loaded for further analysis, ensuring access to relevant data for the project.']}, {'end': 4364.639, 'start': 3795.115, 'title': 'Launch site analysis dashboard', 'summary': 'Demonstrates the creation of a dashboard in tableau to analyze the average temperatures, wind speeds, humidity, launch vehicles used, mission status, and track records of different launch sites, with specific details and statistics presented for each aspect.', 'duration': 569.524, 'highlights': ['The chapter demonstrates the creation of a dashboard in Tableau to analyze the average temperatures, wind speeds, humidity, launch vehicles used, mission status, and track records of different launch sites, with specific details and statistics presented for each aspect.', 'The dashboard provides detailed insights into the average temperatures, wind speeds, and humidity of launch sites, along with the launch vehicles used, mission success rates of different companies, and track records of launch sites, offering a comprehensive overview of key metrics for analysis.', 'The presentation of specific statistics, such as average wind speeds at Kennedy Space Center being 20 miles and 23 miles at Vandenberg and Marshall at 9, and the mission success rates of companies like SpaceX and Boeing, adds valuable quantitative data to the analysis.', 'The creation of a single dashboard to integrate and visualize data on launch temperatures, wind speeds, humidity, launch vehicles used, mission status, and track records, showcases the practical application of Tableau for comprehensive data analysis and visualization.']}], 'duration': 711.248, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/5uzB4z4iN0g/pics/5uzB4z4iN0g3653391.jpg', 'highlights': ['The chapter emphasizes the importance of ensuring ideal conditions before launching satellites or rockets into space.', 'The dataset is obtained from Kaggle and is successfully loaded for further analysis.', 'The creation of a single dashboard to integrate and visualize data on launch temperatures, wind speeds, humidity, launch vehicles used, mission status, and track records, showcases the practical application of Tableau for comprehensive data analysis and visualization.', 'The presentation of specific statistics, such as average wind speeds at Kennedy Space Center being 20 miles and 23 miles at Vandenberg and Marshall at 9, and the mission success rates of companies like SpaceX and Boeing, adds valuable quantitative data to the analysis.']}], 'highlights': ['The creation of a single dashboard to integrate and visualize data on launch temperatures, wind speeds, humidity, launch vehicles used, mission status, and track records, showcases the practical application of Tableau for comprehensive data analysis and visualization.', 'Using Tableau to forecast COVID-19 levels with an Excel data file from Kaggle', 'Creating dashboards for COVID-19 international and Indian data, including confirmed cases, recovery cases, trend lines, and Indian states.', 'Identifying the busiest day in 2020 for San Francisco Airport as 6th March with 3,295 flights taking off.', 'The confirmed cases of Covid-19 showed a decrement in January, indicating a slow decrease in the virus.', 'The chapter covers projects on COVID-19, airline data, and space missions.', 'The process of using the data interpreter in Tableau to identify and resolve data issues', 'The dataset includes columns for confirmed cases, deaths, recoveries, observation dates, and other relevant information', 'The chapter emphasizes the importance of ensuring ideal conditions before launching satellites or rockets into space.', "Exploring the possibility of forecasting future COVID-19 presence using Tableau by creating a new sheet and renaming it as 'forecast of COVID-19 presence'"]}