title
Data Science Project - Covid-19 Data Analysis Project using Python | Python Training | Edureka

description
** Python Certification Training: https://www.edureka.co/data-science-python-certification-course ** This Edureka Live on Data Science Projects - 1 will help you understand how the processes in the data science life cycle can be used to derive insights from a given dataset. Following topics will be discussed in this session: Data Science Life Cycle Projects To Take As A Beginner COVID-19 Italy Data Analysis Python Tutorial Playlist: https://goo.gl/WsBpKe Blog Series: http://bit.ly/2sqmP4s #PythonEdureka #Edureka #datascienceproject #pythonprojects #pythonprogramming #pythontutorial #PythonTraining To subscribe to our channel and hit the bell icon to never miss an update from us in the future: https://goo.gl/6ohpTV Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka ----------------------------------------------------------------------------------------------------------------------------------- How it Works? 1. This is a 5 Week Instructor-led Online Course,40 hours of assignment and 20 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training, you will be working on a real-time project for which we will provide you a Grade and a Verifiable Certificate! --------------------------------- About the course Python has been one of the premier, flexible, and powerful open-source language that is easy to learn, easy to use, and has powerful libraries for data manipulation and analysis. For over a decade, Python has been used in scientific computing and highly quantitative domains such as finance, oil and gas, physics, and signal processing. Edureka's Python Certification Training not only focuses on the fundamentals of Python, Statistics and Machine Learning but also helps one gain expertise in applied Data Science at scale using Python. The training is a step by step guide to Python and Data Science with extensive hands-on. The course is packed with several activity problems and assignments and scenarios that help you gain practical experience in addressing predictive modeling problems that would either require Machine Learning using Python. Starting from basics of Statistics such as mean, median and mode to exploring features such as Data Analysis, Regression, Classification, Clustering, Naive Bayes, Cross-Validation, Label Encoding, Random Forests, Decision Trees and Support Vector Machines with a supporting example and exercise help you get into the weeds. Furthermore, you will be taught of Reinforcement Learning which in turn is an important aspect of Artificial Intelligence. You will be able to train your machine based on real-life scenarios using Machine Learning Algorithms. Edureka’s Python course will also cover both basic and advanced concepts of Python like writing Python scripts, sequence and file operations in Python. You will use libraries like pandas, numpy, matplotlib, scikit, and master concepts like Python machine learning, scripts, and sequence. Why learn Python? It's continued to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging programs is a breeze in Python with its built-in debugger. It runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for commercial products, because of its OSI-approved open source license. It has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that it is the " Next Big Thing " and a must for Professionals in the Data Analytics domain. Who Should Go For This Course? Programmers, Developers, Technical Leads, Architects Developers aspiring to be a ‘Machine Learning Engineer' Analytics Managers who are leading a team of analysts Business Analysts who want to understand Machine Learning (ML) Techniques Information Architects who want to gain expertise in Predictive Analytics 'Python' professionals who want to design automatic predictive models For more information, please write back to us at sales@edureka.in or call us at IND: 9606058406 / US: 18338555775

detail
{'title': 'Data Science Project - Covid-19 Data Analysis Project using Python | Python Training | Edureka', 'heatmap': [{'end': 433.043, 'start': 391.357, 'weight': 0.889}, {'end': 549.937, 'start': 529.582, 'weight': 0.927}, {'end': 732.72, 'start': 707.327, 'weight': 0.916}, {'end': 975.657, 'start': 953.965, 'weight': 0.938}], 'summary': "Covers data science projects for beginners, visualization basics, and covid-19 data analysis using python, focusing on italy's covid-19 dataset, visualization techniques, impact of home quarantine, and the need to flatten the curve to prevent overwhelming healthcare systems.", 'chapters': [{'end': 79.821, 'segs': [{'end': 79.821, 'src': 'embed', 'start': 0.009, 'weight': 0, 'content': [{'end': 0.569, 'text': 'Hello everyone.', 'start': 0.009, 'duration': 0.56}, {'end': 12.397, 'text': 'This is Hello everyone.', 'start': 0.729, 'duration': 11.668}, {'end': 15.839, 'text': 'This is Vasim from Edureka, and I welcome you all to this live session,', 'start': 12.557, 'duration': 3.282}, {'end': 20.342, 'text': 'in which I am going to talk about data science projects that you should work on to get a job.', 'start': 15.839, 'duration': 4.503}, {'end': 23.644, 'text': 'Let me get a quick confirmation guys if you guys can hear me or not.', 'start': 21.022, 'duration': 2.622}, {'end': 26.285, 'text': 'So if I am audible to you guys, please type.', 'start': 24.004, 'duration': 2.281}, {'end': 27.126, 'text': 'Yes in the chat box.', 'start': 26.305, 'duration': 0.821}, {'end': 41.818, 'text': "Now that I'm getting a lot of confirmation.", 'start': 39.997, 'duration': 1.821}, {'end': 44.02, 'text': 'Let us take a look at the agenda for this session.', 'start': 42.138, 'duration': 1.882}, {'end': 44.9, 'text': 'So, first of all,', 'start': 44.36, 'duration': 0.54}, {'end': 51.865, 'text': "I'm going to start with the basic introduction to data science life cycle and then I will explain the project objective for this session moving further.", 'start': 44.9, 'duration': 6.965}, {'end': 53.946, 'text': 'We will work on visualization for analysis.', 'start': 51.885, 'duration': 2.061}, {'end': 60.791, 'text': 'And finally we will work on covid-19 Italy data to understand how we can work with data science project for beginners.', 'start': 54.386, 'duration': 6.405}, {'end': 62.692, 'text': 'I hope you guys are clear with the agenda.', 'start': 61.371, 'duration': 1.321}, {'end': 64.536, 'text': 'So meanwhile,', 'start': 63.536, 'duration': 1}, {'end': 75.72, 'text': "don't forget to subscribe to Edureka for more exciting tutorials and press the bell icon to get the latest updates on Edureka and enroll to Edureka Python for data science certification program.", 'start': 64.536, 'duration': 11.184}, {'end': 77.781, 'text': 'The link is given in the description box below.', 'start': 75.88, 'duration': 1.901}, {'end': 79.821, 'text': 'Now, let us begin our session.', 'start': 78.721, 'duration': 1.1}], 'summary': 'Vasim from edureka discusses data science projects for beginners, including covid-19 italy data analysis.', 'duration': 79.812, 'max_score': 0.009, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mKSWAlvXSmw/pics/mKSWAlvXSmw9.jpg'}], 'start': 0.009, 'title': 'Data science projects for job', 'summary': 'Discusses data science projects for beginners, covering the data science life cycle, visualization for analysis, and working with covid-19 italy data.', 'chapters': [{'end': 79.821, 'start': 0.009, 'title': 'Data science projects for job', 'summary': 'Discusses data science projects for beginners, covering the data science life cycle, visualization for analysis, and working with covid-19 italy data.', 'duration': 79.812, 'highlights': ['The session covers the basic introduction to data science life cycle and project objectives, followed by visualization for analysis and working on Covid-19 Italy data.', 'Vasim from Edureka welcomes the audience to a live session about data science projects for job, emphasizing the importance of the projects for getting a job in the field.', 'Vasim encourages the audience to subscribe to Edureka for more tutorials and to enroll in the Python for data science certification program.']}], 'duration': 79.812, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mKSWAlvXSmw/pics/mKSWAlvXSmw9.jpg', 'highlights': ['The session covers the basic introduction to data science life cycle and project objectives, followed by visualization for analysis and working on Covid-19 Italy data.', 'Vasim from Edureka welcomes the audience to a live session about data science projects for job, emphasizing the importance of the projects for getting a job in the field.', 'Vasim encourages the audience to subscribe to Edureka for more tutorials and to enroll in the Python for data science certification program.']}, {'end': 408.328, 'segs': [{'end': 128.91, 'src': 'embed', 'start': 101.808, 'weight': 0, 'content': [{'end': 107.93, 'text': 'and when the data is loaded in the program, you have to clean the data manipulated according to your requirements,', 'start': 101.808, 'duration': 6.122}, {'end': 116.513, 'text': 'and then you have to draw conclusions or understand the data throughout by visualization to understand the relation between the different plot points of your data.', 'start': 107.93, 'duration': 8.583}, {'end': 121.265, 'text': 'So these are the processes that are included in your data science life cycle.', 'start': 117.162, 'duration': 4.103}, {'end': 128.91, 'text': 'after you have enough conclusive relationship between the variables, you are able to understand what kind of model you can approach this data for.', 'start': 121.265, 'duration': 7.645}], 'summary': 'In the data science life cycle, cleaning and visualizing are vital before modeling.', 'duration': 27.102, 'max_score': 101.808, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mKSWAlvXSmw/pics/mKSWAlvXSmw101808.jpg'}, {'end': 211.6, 'src': 'embed', 'start': 140.258, 'weight': 1, 'content': [{'end': 144.661, 'text': 'So the first project in this session will be drawing conclusions by data visualization.', 'start': 140.258, 'duration': 4.403}, {'end': 145.713, 'text': 'For that.', 'start': 145.353, 'duration': 0.36}, {'end': 147.595, 'text': 'Let me just tell you as a beginner.', 'start': 145.974, 'duration': 1.621}, {'end': 150.837, 'text': 'What kind of projects should you take for practice?', 'start': 147.955, 'duration': 2.882}, {'end': 157.783, 'text': "So, first of all, you have to keep in mind that the projects that you're taking are going to cover all the aspects of the data science life cycle,", 'start': 151.658, 'duration': 6.125}, {'end': 165.049, 'text': "that is, collecting the data, getting the correct data from the source that you're downloading it from or you're extracting it from.", 'start': 157.783, 'duration': 7.266}, {'end': 167.431, 'text': 'then you have to make sure that you understand the data.', 'start': 165.049, 'duration': 2.382}, {'end': 172.288, 'text': "You're able to clean the data of the redundancies or any missing values, for that matter.", 'start': 167.824, 'duration': 4.464}, {'end': 179.655, 'text': "Then you should be able to relate it to such a level that you can visualize it on a graph so that you'll be able to understand it better.", 'start': 172.749, 'duration': 6.906}, {'end': 185.041, 'text': 'So when you have reached that point, you have actually mastered quite a few skills in data science.', 'start': 180.196, 'duration': 4.845}, {'end': 191.407, 'text': "So after you're mastered, until that point where you can actually visualize the relationship between the variables,", 'start': 185.781, 'duration': 5.626}, {'end': 196.596, 'text': 'You can move on to making the model and there comes the picture, which is machine learning,', 'start': 191.874, 'duration': 4.722}, {'end': 200.237, 'text': 'and you can move on to advanced concepts like AI and everything.', 'start': 196.596, 'duration': 3.641}, {'end': 203.578, 'text': 'but before that, you have to keep in mind that you should master the basics first.', 'start': 200.237, 'duration': 3.341}, {'end': 211.6, 'text': 'So my suggestion would be you should start with the projects which will help you understand the first few processes in the data science lifecycle.', 'start': 204.378, 'duration': 7.222}], 'summary': 'Start with projects covering data collection, cleaning, visualization to master data science basics.', 'duration': 71.342, 'max_score': 140.258, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mKSWAlvXSmw/pics/mKSWAlvXSmw140258.jpg'}, {'end': 279.213, 'src': 'embed', 'start': 251.853, 'weight': 5, 'content': [{'end': 255.676, 'text': 'I am sure everybody is aware of the pandemic that we are facing right now.', 'start': 251.853, 'duration': 3.823}, {'end': 257.517, 'text': "I mean, it's been all over the world.", 'start': 256.036, 'duration': 1.481}, {'end': 262.06, 'text': "People are suffering from it and it's a very tough time for all humanity.", 'start': 257.898, 'duration': 4.162}, {'end': 267.045, 'text': 'But in the wake of it, we can actually do something productive in spite of being at home.', 'start': 262.782, 'duration': 4.263}, {'end': 267.845, 'text': 'We can learn stuff.', 'start': 267.105, 'duration': 0.74}, {'end': 271.208, 'text': 'So I was able to find this data on Kaggle.', 'start': 268.626, 'duration': 2.582}, {'end': 279.213, 'text': "So this is a Italy data for the past month and we are going to read, understand the data and we're going to use the visualization libraries,", 'start': 271.909, 'duration': 7.304}], 'summary': 'The pandemic has impacted the world, but we can learn and be productive at home. utilizing italy data from kaggle for analysis and visualization.', 'duration': 27.36, 'max_score': 251.853, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mKSWAlvXSmw/pics/mKSWAlvXSmw251853.jpg'}, {'end': 314.99, 'src': 'embed', 'start': 288.838, 'weight': 6, 'content': [{'end': 295.082, 'text': "and I'm choosing Jupiter notebook because it is very easy to work with Jupiter notebook when you're working in data science and, most specifically,", 'start': 288.838, 'duration': 6.244}, {'end': 297.196, 'text': "If you're working on visualization.", 'start': 295.575, 'duration': 1.621}, {'end': 299.218, 'text': 'Jupiter notebook is the best deal you have right now.', 'start': 297.196, 'duration': 2.022}, {'end': 305.603, 'text': 'I mean you can also work on other IDs, like by charm and everything, but this is quite good when it comes to, you know,', 'start': 299.358, 'duration': 6.245}, {'end': 308.525, 'text': 'just putting something over here and executing it at your fingertips.', 'start': 305.603, 'duration': 2.922}, {'end': 309.345, 'text': "That's pretty cool.", 'start': 308.685, 'duration': 0.66}, {'end': 314.99, 'text': "So I'm going to use Jupiter notebook in this session and I'm hoping everybody is familiar with Jupiter notebook.", 'start': 309.906, 'duration': 5.084}], 'summary': 'Jupyter notebook is the best tool for data visualization in data science, offering easy execution and familiarity.', 'duration': 26.152, 'max_score': 288.838, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mKSWAlvXSmw/pics/mKSWAlvXSmw288838.jpg'}, {'end': 408.328, 'src': 'embed', 'start': 350.554, 'weight': 7, 'content': [{'end': 355.691, 'text': "I'm just going to import all of them and For visualization in this session.", 'start': 350.554, 'duration': 5.137}, {'end': 356.912, 'text': "I'm going to use seaborn guys.", 'start': 355.731, 'duration': 1.181}, {'end': 364.138, 'text': "So I'll put seaborn as SNS and to be on the safer side.", 'start': 357.292, 'duration': 6.846}, {'end': 371.184, 'text': "I'm going to import matplotlib.pyplot as PLT.", 'start': 364.678, 'duration': 6.506}, {'end': 375.788, 'text': "So I'm going to run this and we have I think we don't have any errors.", 'start': 372.365, 'duration': 3.423}, {'end': 377.75, 'text': "So it's going to take a while.", 'start': 376.849, 'duration': 0.901}, {'end': 381.433, 'text': "Meanwhile, I'll just write the code to import the data.", 'start': 378.61, 'duration': 2.823}, {'end': 384.212, 'text': 'or read that CSV data that we have here.', 'start': 382.111, 'duration': 2.101}, {'end': 388.715, 'text': "So I'm going to use PD dot read CSV.", 'start': 384.232, 'duration': 4.483}, {'end': 396.1, 'text': "Right, and then I'm going to mention the file location.", 'start': 391.357, 'duration': 4.743}, {'end': 401.163, 'text': 'should work fine, or we just add our over here to avoid any arrows right?', 'start': 396.1, 'duration': 5.063}, {'end': 402.764, 'text': 'We have successfully imported the data.', 'start': 401.203, 'duration': 1.561}, {'end': 404.865, 'text': 'Now, we are going to look at the data for the first time.', 'start': 402.824, 'duration': 2.041}, {'end': 406.927, 'text': "We'll see what the data looks like.", 'start': 405.366, 'duration': 1.561}, {'end': 408.328, 'text': 'Okay, we all right.', 'start': 407.487, 'duration': 0.841}], 'summary': 'Imported data using seaborn and matplotlib for visualization.', 'duration': 57.774, 'max_score': 350.554, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mKSWAlvXSmw/pics/mKSWAlvXSmw350554.jpg'}], 'start': 80.542, 'title': 'Data science basics and visualization', 'summary': 'Covers the basics of the data science life cycle, including data collection, cleaning, visualization, model selection, and deployment, emphasizing the importance of drawing conclusions through data visualization. it also focuses on mastering data science basics through visualization, project-based learning, and practical application of skills, using covid-19 italy data as an example. additionally, it involves analyzing italy data using visualization libraries like seaborn and jupiter notebook, emphasizing ease of use and dependencies required for the analysis.', 'chapters': [{'end': 172.288, 'start': 80.542, 'title': 'Data science life cycle basics', 'summary': 'Covers the basics of the data science life cycle, including data collection, cleaning, visualization, model selection, building, and deployment, emphasizing the importance of drawing conclusions through data visualization and selecting comprehensive projects for practice.', 'duration': 91.746, 'highlights': ['The data science life cycle involves processes like data collection, cleaning, visualization, model selection, building, and deployment, with an emphasis on drawing conclusions through data visualization.', 'Beginners should start with projects that cover all aspects of the data science life cycle, including data collection, understanding, cleaning, and ensuring the completeness of the data.', 'Understanding the data and cleaning it of redundancies or missing values is crucial in approaching any data science project.']}, {'end': 271.208, 'start': 172.749, 'title': 'Mastering basics of data science', 'summary': 'Emphasizes mastering the basics of data science through visualization, project-based learning, and practical application of skills, using covid-19 italy data as an example.', 'duration': 98.459, 'highlights': ['Visualization and understanding the relationship between variables are key skills in mastering data science, leading to the ability to move on to machine learning and advanced concepts like AI.', 'Starting with projects using real-world data, such as COVID-19 Italy data from Kaggle, is recommended to understand the data science lifecycle.', 'Emphasizing the importance of being productive and learning during the pandemic by utilizing available resources like data on Kaggle to engage in data science projects.']}, {'end': 408.328, 'start': 271.909, 'title': 'Italy data visualization', 'summary': 'Involves analyzing italy data using visualization libraries like seaborn and jupiter notebook, emphasizing the ease of use and dependencies required for the analysis.', 'duration': 136.419, 'highlights': ['Jupiter notebook is the best tool for working on visualization in data science, providing ease of execution and fingertip accessibility.', 'Importing pandas and necessary libraries, and using seaborn for visualization are key steps in the data analysis process.', 'Emphasizing the ease of using Jupiter notebook for data analysis, with references to tutorials and cheat sheets for beginners.', 'Demonstrating the process of importing and reading CSV data using pandas for analysis.']}], 'duration': 327.786, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mKSWAlvXSmw/pics/mKSWAlvXSmw80542.jpg', 'highlights': ['The data science life cycle involves processes like data collection, cleaning, visualization, model selection, building, and deployment, with an emphasis on drawing conclusions through data visualization.', 'Visualization and understanding the relationship between variables are key skills in mastering data science, leading to the ability to move on to machine learning and advanced concepts like AI.', 'Beginners should start with projects that cover all aspects of the data science life cycle, including data collection, understanding, cleaning, and ensuring the completeness of the data.', 'Understanding the data and cleaning it of redundancies or missing values is crucial in approaching any data science project.', 'Starting with projects using real-world data, such as COVID-19 Italy data from Kaggle, is recommended to understand the data science lifecycle.', 'Emphasizing the importance of being productive and learning during the pandemic by utilizing available resources like data on Kaggle to engage in data science projects.', 'Jupiter notebook is the best tool for working on visualization in data science, providing ease of execution and fingertip accessibility.', 'Importing pandas and necessary libraries, and using seaborn for visualization are key steps in the data analysis process.', 'Emphasizing the ease of using Jupiter notebook for data analysis, with references to tutorials and cheat sheets for beginners.', 'Demonstrating the process of importing and reading CSV data using pandas for analysis.']}, {'end': 946.456, 'segs': [{'end': 441.144, 'src': 'embed', 'start': 408.708, 'weight': 0, 'content': [{'end': 410.469, 'text': "We'll just take a look at the first five rows first.", 'start': 408.708, 'duration': 1.761}, {'end': 412.035, 'text': 'All right.', 'start': 411.755, 'duration': 0.28}, {'end': 416.257, 'text': 'So we have all these rows and columns.', 'start': 413.796, 'duration': 2.461}, {'end': 419.338, 'text': 'All right, so we have date.', 'start': 417.517, 'duration': 1.821}, {'end': 423.719, 'text': "Okay, we'll just get the list of all the columns.", 'start': 419.758, 'duration': 3.961}, {'end': 433.043, 'text': 'So we have one unnamed we update state hospitalized with symptoms.', 'start': 428.821, 'duration': 4.222}, {'end': 434.203, 'text': 'We have intensive care.', 'start': 433.143, 'duration': 1.06}, {'end': 439.122, 'text': 'people in the intensive care the total hospitalized people home quarantine people.', 'start': 434.619, 'duration': 4.503}, {'end': 441.144, 'text': 'We have total confirmed cases.', 'start': 439.142, 'duration': 2.002}], 'summary': 'Analyzing first 5 rows of data: date, state hospitalized, intensive care, home quarantine, total confirmed cases.', 'duration': 32.436, 'max_score': 408.708, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mKSWAlvXSmw/pics/mKSWAlvXSmw408708.jpg'}, {'end': 491.701, 'src': 'embed', 'start': 460.358, 'weight': 2, 'content': [{'end': 465.169, 'text': 'just keep in mind, This is exploring the data, you know, trying to find out what exactly it looks like.', 'start': 460.358, 'duration': 4.811}, {'end': 466.61, 'text': 'So we have date all those dates.', 'start': 465.189, 'duration': 1.421}, {'end': 468.552, 'text': "It's in the date format.", 'start': 467.431, 'duration': 1.121}, {'end': 472.256, 'text': 'Then we have state the people with hospitalized with symptoms.', 'start': 468.812, 'duration': 3.444}, {'end': 476.82, 'text': 'So the 34th entry has more than 27, 000 people with symptoms,', 'start': 472.296, 'duration': 4.524}, {'end': 483.936, 'text': 'intensive care and everything we have on the first day when it is recorded people with symptoms 126.', 'start': 476.82, 'duration': 7.116}, {'end': 491.701, 'text': "So we'll try to figure out the relationship between all these variables so we can say all these instances in this data frame that we have over here.", 'start': 483.936, 'duration': 7.765}], 'summary': 'Exploring data to find relationships, e.g., 27,000 people hospitalized with symptoms', 'duration': 31.343, 'max_score': 460.358, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mKSWAlvXSmw/pics/mKSWAlvXSmw460358.jpg'}, {'end': 554.839, 'src': 'heatmap', 'start': 529.582, 'weight': 0.927, 'content': [{'end': 538.071, 'text': "So you just write data dot is null All right, I'm going to get the sum of all the values that are null over here.", 'start': 529.582, 'duration': 8.489}, {'end': 545.155, 'text': 'So we have noted and note n which is we have 27 values which are null from out of 34 values.', 'start': 538.191, 'duration': 6.964}, {'end': 549.937, 'text': 'So if I dropped all these columns my data will not be left with any values.', 'start': 546.015, 'duration': 3.922}, {'end': 554.839, 'text': "I mean, I don't need seven rows in my data because that's not going to be enough to make conclusions.", 'start': 550.037, 'duration': 4.802}], 'summary': '27 out of 34 values are null, dropping them would leave insufficient data for analysis.', 'duration': 25.257, 'max_score': 529.582, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mKSWAlvXSmw/pics/mKSWAlvXSmw529582.jpg'}, {'end': 741.257, 'src': 'heatmap', 'start': 707.327, 'weight': 0.916, 'content': [{'end': 711.088, 'text': 'And I want to check people who have actually recovered.', 'start': 707.327, 'duration': 3.761}, {'end': 713.689, 'text': 'All right.', 'start': 713.429, 'duration': 0.26}, {'end': 715.655, 'text': 'So we have a relationship over here.', 'start': 714.195, 'duration': 1.46}, {'end': 723.497, 'text': 'So as you can see on the x-axis, we have the total number of cases and on the y-axis and we have the number of people who have recovered.', 'start': 715.675, 'duration': 7.822}, {'end': 732.72, 'text': 'So when I look at the data over here for the initial 20, 000 total cases, they were not a lot of people who had recovered less than 2, 000 people.', 'start': 724.238, 'duration': 8.482}, {'end': 741.257, 'text': "But then as the number grew stronger, I mean it grew a lot more than let's say hundred thousand people actually recovered more.", 'start': 733.928, 'duration': 7.329}], 'summary': 'Data shows increasing number of recoveries as cases grow.', 'duration': 33.93, 'max_score': 707.327, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mKSWAlvXSmw/pics/mKSWAlvXSmw707327.jpg'}, {'end': 796.986, 'src': 'embed', 'start': 754.606, 'weight': 1, 'content': [{'end': 762.048, 'text': 'So this is a good conclusion that we make, looking at this relationship over here between total cases and recovered,', 'start': 754.606, 'duration': 7.442}, {'end': 766.409, 'text': 'that people are actually recovering from the disease in Italy in the last 34 days.', 'start': 762.048, 'duration': 4.361}, {'end': 772.33, 'text': "So we'll make one point for the conclusion that is people are recovering now.", 'start': 767.129, 'duration': 5.201}, {'end': 778.151, 'text': "We'll take a look at the next graph or we'll take a look at different perspective of this graph plot.", 'start': 772.35, 'duration': 5.801}, {'end': 780.634, 'text': 'So we want to check the total cases.', 'start': 778.752, 'duration': 1.882}, {'end': 783.015, 'text': "Let's say how many people have actually died from it.", 'start': 780.854, 'duration': 2.161}, {'end': 788.64, 'text': 'Okay, so deaths are also going the same direction with the recovered people.', 'start': 783.035, 'duration': 5.605}, {'end': 795.245, 'text': 'like more than 10, 000 people have actually died from the disease in the last 34 days in Italy.', 'start': 788.64, 'duration': 6.605}, {'end': 796.986, 'text': 'And if you look at the number,', 'start': 795.805, 'duration': 1.181}], 'summary': 'In italy, over 10,000 people have died from the disease in the last 34 days, and recoveries are also increasing.', 'duration': 42.38, 'max_score': 754.606, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mKSWAlvXSmw/pics/mKSWAlvXSmw754606.jpg'}, {'end': 893.479, 'src': 'embed', 'start': 861.523, 'weight': 4, 'content': [{'end': 869.145, 'text': 'So, from when it started, it started from zero and then it has reached more than 70, 000 people the total number of cases,', 'start': 861.523, 'duration': 7.622}, {'end': 872.506, 'text': 'which is actually a very sad part to look at.', 'start': 869.145, 'duration': 3.361}, {'end': 881.048, 'text': 'out of all the hundred thousand cases, more than 70, 000 people have actually confirmed the case,', 'start': 872.506, 'duration': 8.542}, {'end': 893.479, 'text': "and let's say we want to check the people who were hospitalized with symptoms and the number between the total number of confirmed cases.", 'start': 881.048, 'duration': 12.431}], 'summary': 'Over 70,000 out of 100,000 confirmed cases, with a total outreach of more than 70,000 people, reflect a concerning situation.', 'duration': 31.956, 'max_score': 861.523, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mKSWAlvXSmw/pics/mKSWAlvXSmw861523.jpg'}], 'start': 408.708, 'title': 'Covid-19 data analysis', 'summary': 'Explores the initial covid-19 dataset, including columns such as date, state, hospitalized, intensive care, home quarantine, confirmed cases, recovered cases, deaths, and total cases, providing insights into the number of affected individuals and the format of the data. it also analyzes the relationship between variables, including the count of null values and the use of scatter plots to visualize the relationship between total cases and recoveries, deaths, and confirmed cases in italy over the last 34 days.', 'chapters': [{'end': 483.936, 'start': 408.708, 'title': 'Covid-19 data exploration', 'summary': 'Explores the initial covid-19 dataset, including columns such as date, state, hospitalized with symptoms, intensive care, home quarantine, confirmed cases, recovered cases, deaths, and total cases, providing insights into the number of affected individuals and the format of the data.', 'duration': 75.228, 'highlights': ['The dataset includes columns such as date, state, hospitalized with symptoms, intensive care, home quarantine, confirmed cases, recovered cases, deaths, and total cases.', 'The 34th entry records more than 27,000 people with symptoms, with 126 individuals in intensive care on the first day.']}, {'end': 946.456, 'start': 483.936, 'title': 'Analyzing relationship between variables', 'summary': 'Explores the relationship between variables in a dataset, revealing insights such as the count of null values, the use of scatter plots to visualize the relationship between total cases and recoveries, deaths, and confirmed cases in italy over the last 34 days.', 'duration': 462.52, 'highlights': ['The scatter plot visualization reveals a linear relationship between the total number of cases and the number of people who have recovered, indicating that more than 12,000 people have recovered when the total cases reached 100,000, suggesting a positive recovery trend in Italy over the last 34 days.', 'The analysis also uncovers a concerning trend as more than 10,000 people have died from the disease in the last 34 days in Italy, with the number of deaths reaching a level comparable to the number of recoveries.', 'The data indicates an exponential increase in the total number of confirmed cases, reaching more than 70,000 out of 100,000 cases, highlighting the severity of the situation in Italy over the last 34 days.']}], 'duration': 537.748, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mKSWAlvXSmw/pics/mKSWAlvXSmw408708.jpg', 'highlights': ['The dataset includes columns such as date, state, hospitalized with symptoms, intensive care, home quarantine, confirmed cases, recovered cases, deaths, and total cases.', 'The scatter plot visualization reveals a linear relationship between the total number of cases and the number of people who have recovered, indicating that more than 12,000 people have recovered when the total cases reached 100,000, suggesting a positive recovery trend in Italy over the last 34 days.', 'The 34th entry records more than 27,000 people with symptoms, with 126 individuals in intensive care on the first day.', 'The analysis also uncovers a concerning trend as more than 10,000 people have died from the disease in the last 34 days in Italy, with the number of deaths reaching a level comparable to the number of recoveries.', 'The data indicates an exponential increase in the total number of confirmed cases, reaching more than 70,000 out of 100,000 cases, highlighting the severity of the situation in Italy over the last 34 days.']}, {'end': 1211.114, 'segs': [{'end': 985.366, 'src': 'heatmap', 'start': 953.965, 'weight': 0.938, 'content': [{'end': 956.386, 'text': 'So for you, let me just add recovered.', 'start': 953.965, 'duration': 2.421}, {'end': 960.288, 'text': 'Right, we have a syntax error.', 'start': 956.406, 'duration': 3.882}, {'end': 962.189, 'text': "Let's see what this tells us now.", 'start': 960.889, 'duration': 1.3}, {'end': 963.81, 'text': 'So we have added the hue.', 'start': 962.209, 'duration': 1.601}, {'end': 970.474, 'text': 'All right, so we have a recovered sign from 0 then then we have 5, 000 10, 000 and 15, 000.', 'start': 963.83, 'duration': 6.644}, {'end': 975.657, 'text': "So all these plot points that I'm telling you are to understand the relationship between all these variables that we have.", 'start': 970.474, 'duration': 5.183}, {'end': 979.24, 'text': 'and also we can also have this pay plot.', 'start': 976.698, 'duration': 2.542}, {'end': 985.366, 'text': "Okay, so I'm going to show you this what happens if I do that if I get the pay plot.", 'start': 980.101, 'duration': 5.265}], 'summary': 'Data analysis shows relationship between variables with recovered sign at 0, 5,000, 10,000, and 15,000.', 'duration': 31.401, 'max_score': 953.965, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mKSWAlvXSmw/pics/mKSWAlvXSmw953965.jpg'}, {'end': 1056.078, 'src': 'embed', 'start': 1012.553, 'weight': 3, 'content': [{'end': 1018.915, 'text': 'and let me just tell you, like scatter, plots are highly effective, but there is no universally optimal type of visualization.', 'start': 1012.553, 'duration': 6.362}, {'end': 1023.637, 'text': 'So instead the visual representation should be adapted for the specific of the data set.', 'start': 1019.535, 'duration': 4.102}, {'end': 1026.534, 'text': 'and to the question you are trying to answer with the plot.', 'start': 1024.21, 'duration': 2.324}, {'end': 1031.04, 'text': 'Like if I have a question, I should be able to answer that question looking at the visualization of the plot.', 'start': 1026.714, 'duration': 4.326}, {'end': 1034.505, 'text': "So what I'm going to do is with some data sets.", 'start': 1031.901, 'duration': 2.604}, {'end': 1040.634, 'text': 'You may want to understand changes in one variable as a function or a similarity continuous variable.', 'start': 1034.986, 'duration': 5.648}, {'end': 1045.19, 'text': 'In this situation a good choice to draw a line plot.', 'start': 1041.686, 'duration': 3.504}, {'end': 1056.078, 'text': 'So in Seabourn we can accomplish this by line plot function or we can just use L plot and in the type or the kind we can write line, right guys.', 'start': 1045.69, 'duration': 10.388}], 'summary': 'Scatter plots are effective, but visualizations should adapt to specific data and question. line plots are useful for understanding changes in continuous variables.', 'duration': 43.525, 'max_score': 1012.553, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mKSWAlvXSmw/pics/mKSWAlvXSmw1012553.jpg'}, {'end': 1211.114, 'src': 'embed', 'start': 1164.265, 'weight': 0, 'content': [{'end': 1167.626, 'text': "All right, there's a spelling mistake.", 'start': 1164.265, 'duration': 3.361}, {'end': 1168.286, 'text': "I'm sorry guys.", 'start': 1167.686, 'duration': 0.6}, {'end': 1177.108, 'text': 'Okay So the total number of cases is probably around hundred thousand and the home quarantine people are more than 40, 000 people.', 'start': 1169.086, 'duration': 8.022}, {'end': 1184.61, 'text': 'So all these people, if you guys stay at home, we can actually flatten this curve and make a dent in the total number of cases.', 'start': 1177.548, 'duration': 7.062}, {'end': 1189.851, 'text': 'so we can draw one more conclusion from over here is, that is, if more people are in quarantine,', 'start': 1184.61, 'duration': 5.241}, {'end': 1194.306, 'text': 'The total number of cases going to be very low instead of total cases.', 'start': 1190.404, 'duration': 3.902}, {'end': 1196.667, 'text': "Let's see recover.", 'start': 1194.386, 'duration': 2.281}, {'end': 1199.588, 'text': 'All right.', 'start': 1196.687, 'duration': 2.901}, {'end': 1209.533, 'text': 'so it is actually started from 0 and the recovered people reached 2, 000 pretty easily and in the home quarantine people live when they were 10, 000,', 'start': 1199.588, 'duration': 9.945}, {'end': 1209.833, 'text': 'more than 4, 000..', 'start': 1209.533, 'duration': 0.3}, {'end': 1211.114, 'text': 'We will have to recover.', 'start': 1209.833, 'duration': 1.281}], 'summary': 'Total cases around 100,000, 40,000 in home quarantine. staying home can flatten the curve and reduce total cases.', 'duration': 46.849, 'max_score': 1164.265, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mKSWAlvXSmw/pics/mKSWAlvXSmw1164265.jpg'}], 'start': 947.401, 'title': 'Visualizing data and analyzing home quarantine', 'summary': 'Covers the process of visualizing data with seaborn, emphasizing plot types and their adaptability, and discusses the impact of home quarantine on flattening the curve, reducing total cases, and increasing recovery rates.', 'chapters': [{'end': 1076.532, 'start': 947.401, 'title': 'Visualizing data with seaborn', 'summary': 'Explains the process of visualizing data using seaborn, emphasizing the use of various plot types and their adaptability to specific datasets, while highlighting the importance of understanding relationships between variables. it also mentions the effectiveness of scatter plots and the use of line plots to visualize changes in one variable as a function of another.', 'duration': 129.131, 'highlights': ['The chapter emphasizes the adaptability of visual representations for specific datasets and the importance of understanding relationships between variables in the visualization process.', 'It mentions the effectiveness of scatter plots and advises on the absence of a universally optimal type of visualization, advocating for adaptability to the specific characteristics of the dataset and the questions being addressed.', 'The process of visualizing changes in one variable as a function of another is highlighted, with a recommendation for using line plots in such situations.']}, {'end': 1211.114, 'start': 1076.652, 'title': 'Analyzing home quarantine and total cases', 'summary': 'Discusses the relationship between home quarantine and total cases, highlighting the impact of home quarantine on flattening the curve and reducing total number of cases, along with the observation that more people in quarantine result in lower total cases and higher recovery rates.', 'duration': 134.462, 'highlights': ['The total number of cases is around 100,000 and the home quarantine population exceeds 40,000, indicating the potential impact of home quarantine on reducing the total number of cases.', 'More people in quarantine lead to a lower total number of cases, as observed from the relationship between home quarantine and total cases.', 'The recovered people reached 2,000 when the home quarantine population was more than 10,000, highlighting the correlation between home quarantine and higher recovery rates.']}], 'duration': 263.713, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mKSWAlvXSmw/pics/mKSWAlvXSmw947401.jpg', 'highlights': ['The recovered people reached 2,000 when the home quarantine population was more than 10,000, highlighting the correlation between home quarantine and higher recovery rates.', 'More people in quarantine lead to a lower total number of cases, as observed from the relationship between home quarantine and total cases.', 'The total number of cases is around 100,000 and the home quarantine population exceeds 40,000, indicating the potential impact of home quarantine on reducing the total number of cases.', 'The chapter emphasizes the adaptability of visual representations for specific datasets and the importance of understanding relationships between variables in the visualization process.', 'It mentions the effectiveness of scatter plots and advises on the absence of a universally optimal type of visualization, advocating for adaptability to the specific characteristics of the dataset and the questions being addressed.', 'The process of visualizing changes in one variable as a function of another is highlighted, with a recommendation for using line plots in such situations.']}, {'end': 1726.027, 'segs': [{'end': 1240.881, 'src': 'embed', 'start': 1211.474, 'weight': 1, 'content': [{'end': 1212.795, 'text': 'So this is the bright side guys.', 'start': 1211.474, 'duration': 1.321}, {'end': 1220.148, 'text': 'And similarly we can also check for other relationship between, you know, intensive care, like people with intensive care,', 'start': 1213.584, 'duration': 6.564}, {'end': 1224.511, 'text': 'and all these plot points that you have inside this data set after this.', 'start': 1220.148, 'duration': 4.363}, {'end': 1230.554, 'text': "Let's take a look at how we can actually plot a few graphs using the categorical scatter plots.", 'start': 1224.911, 'duration': 5.643}, {'end': 1235.097, 'text': 'So the default representation of the data in cat plot uses a scatter plot.', 'start': 1231.295, 'duration': 3.802}, {'end': 1240.881, 'text': 'So we are going to use the cat plot guys.', 'start': 1235.638, 'duration': 5.243}], 'summary': 'Analyzing data using categorical scatter plots for intensive care relationships.', 'duration': 29.407, 'max_score': 1211.474, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mKSWAlvXSmw/pics/mKSWAlvXSmw1211474.jpg'}, {'end': 1432.309, 'src': 'embed', 'start': 1399.04, 'weight': 5, 'content': [{'end': 1403.141, 'text': 'the new confirmed cases and the people who had recovered.', 'start': 1399.04, 'duration': 4.101}, {'end': 1405.722, 'text': 'number of deaths the total cases.', 'start': 1403.141, 'duration': 2.581}, {'end': 1410.052, 'text': 'all these values we had in the data set that we had and on the last day,', 'start': 1405.722, 'duration': 4.33}, {'end': 1416.135, 'text': 'the 34th entry shows the people who are with hospitalized with symptoms are much more than 27, 000..', 'start': 1410.052, 'duration': 6.083}, {'end': 1418.777, 'text': 'So we can look at the number over here.', 'start': 1416.135, 'duration': 2.642}, {'end': 1424.84, 'text': "But let's say this data is new to somebody and who does not have any idea about this data.", 'start': 1419.397, 'duration': 5.443}, {'end': 1432.309, 'text': 'So how is he going to interpret what is happening over here and like how has the disease spread over all these days.', 'start': 1425.26, 'duration': 7.049}], 'summary': '34th entry shows over 27,000 hospitalized with symptoms, revealing significant impact.', 'duration': 33.269, 'max_score': 1399.04, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mKSWAlvXSmw/pics/mKSWAlvXSmw1399040.jpg'}, {'end': 1481.982, 'src': 'embed', 'start': 1440.175, 'weight': 0, 'content': [{'end': 1448.762, 'text': 'So we did that and we were able to conclude that the number of people who had recovered is also increasing at a very rapid rate.', 'start': 1440.175, 'duration': 8.587}, {'end': 1454.527, 'text': 'So that is the best bet that we have against this virus looking at the data.', 'start': 1449.203, 'duration': 5.324}, {'end': 1461.55, 'text': 'And of course number of deaths are rising the number of cases are actually very much and they are rising again.', 'start': 1455.345, 'duration': 6.205}, {'end': 1464.333, 'text': 'So that is what we have to control.', 'start': 1462.111, 'duration': 2.222}, {'end': 1472.099, 'text': 'So the people all around the globe, the people who are trying to tell you to stay home, stay in the quarantine, are actually trying to bend the curve.', 'start': 1464.693, 'duration': 7.406}, {'end': 1473.12, 'text': 'total number of cases.', 'start': 1472.099, 'duration': 1.021}, {'end': 1475.622, 'text': 'So that is going to happen if you stay at home.', 'start': 1473.82, 'duration': 1.802}, {'end': 1481.982, 'text': 'and number of people who are recovering is also increasing, and if the number of people in the hospitals increase,', 'start': 1476.34, 'duration': 5.642}], 'summary': 'Rapid increase in recoveries is the best hope against rising virus cases and deaths.', 'duration': 41.807, 'max_score': 1440.175, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mKSWAlvXSmw/pics/mKSWAlvXSmw1440175.jpg'}, {'end': 1566.48, 'src': 'embed', 'start': 1536.97, 'weight': 3, 'content': [{'end': 1542.976, 'text': 'when the cases reach 40, 000 cases, the total cases and number of people hospitalized were actually flattening.', 'start': 1536.97, 'duration': 6.006}, {'end': 1545.399, 'text': 'So this is what we have to flatten guys.', 'start': 1543.737, 'duration': 1.662}, {'end': 1553.848, 'text': "So we don't want more number of people to be hospitalized and we don't want total cases to actually reach the height that would be devastating.", 'start': 1545.519, 'duration': 8.329}, {'end': 1556.251, 'text': 'So We have to take the measure.', 'start': 1554.429, 'duration': 1.822}, {'end': 1558.473, 'text': 'So this is one conclusion that we can make.', 'start': 1556.271, 'duration': 2.202}, {'end': 1566.48, 'text': 'so we have to keep in mind that total hospitalized people, the quarantine people, the people with more number of cases, will not be reported.', 'start': 1558.473, 'duration': 8.007}], 'summary': 'As cases reach 40,000, total cases and hospitalizations are flattening, prompting the need for measures to prevent further hospitalizations and cases.', 'duration': 29.51, 'max_score': 1536.97, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mKSWAlvXSmw/pics/mKSWAlvXSmw1536970.jpg'}], 'start': 1211.474, 'title': 'Covid-19 data analysis', 'summary': 'Discusses the use of categorical scatter plots to visualize relationships in covid-19 data, highlighting the increase in cases, deaths, and recoveries. it also emphasizes the need to flatten the curve and stay at home to prevent overwhelming healthcare systems, with the 34th entry showing over 27,000 hospitalized with symptoms.', 'chapters': [{'end': 1439.895, 'start': 1211.474, 'title': 'Categorical scatter plots and data analysis', 'summary': 'Discusses the use of categorical scatter plots to visualize relationships in data, highlighting the increase in covid-19 cases, deaths, and recoveries, with the 34th entry showing over 27,000 hospitalized with symptoms.', 'duration': 228.421, 'highlights': ['Visualizing relationships with categorical scatter plots', 'Increase in COVID-19 cases, deaths, and recoveries', 'Over 27,000 hospitalized with symptoms in the 34th entry']}, {'end': 1726.027, 'start': 1440.175, 'title': 'Covid-19 recovery and prevention insights', 'summary': 'Highlights the increasing rate of covid-19 recoveries, the need to flatten the curve of total cases and hospitalizations, and the importance of staying at home to prevent overwhelming healthcare systems, with emphasis on the rising number of deaths.', 'duration': 285.852, 'highlights': ['The increasing rate of Covid-19 recoveries is a key observation, providing hope and indicating progress in the fight against the virus.', 'The need to flatten the curve of total cases and hospitalizations is emphasized to prevent overwhelming healthcare systems, with a specific focus on preventing the increase of hospitalized individuals and total cases.', 'The importance of staying at home is stressed to prevent overwhelming healthcare systems and the rising number of deaths, indicating the urgency of public adherence to safety measures.']}], 'duration': 514.553, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/mKSWAlvXSmw/pics/mKSWAlvXSmw1211474.jpg', 'highlights': ['The increasing rate of Covid-19 recoveries is a key observation, providing hope and indicating progress in the fight against the virus.', 'Visualizing relationships with categorical scatter plots', 'Increase in COVID-19 cases, deaths, and recoveries', 'The need to flatten the curve of total cases and hospitalizations is emphasized to prevent overwhelming healthcare systems, with a specific focus on preventing the increase of hospitalized individuals and total cases.', 'The importance of staying at home is stressed to prevent overwhelming healthcare systems and the rising number of deaths, indicating the urgency of public adherence to safety measures.', 'Over 27,000 hospitalized with symptoms in the 34th entry']}], 'highlights': ['The session covers the basic introduction to data science life cycle and project objectives, followed by visualization for analysis and working on Covid-19 Italy data.', 'The data science life cycle involves processes like data collection, cleaning, visualization, model selection, building, and deployment, with an emphasis on drawing conclusions through data visualization.', 'The dataset includes columns such as date, state, hospitalized with symptoms, intensive care, home quarantine, confirmed cases, recovered cases, deaths, and total cases.', 'The scatter plot visualization reveals a linear relationship between the total number of cases and the number of people who have recovered, indicating that more than 12,000 people have recovered when the total cases reached 100,000, suggesting a positive recovery trend in Italy over the last 34 days.', 'The recovered people reached 2,000 when the home quarantine population was more than 10,000, highlighting the correlation between home quarantine and higher recovery rates.', 'The increasing rate of Covid-19 recoveries is a key observation, providing hope and indicating progress in the fight against the virus.', 'The need to flatten the curve of total cases and hospitalizations is emphasized to prevent overwhelming healthcare systems, with a specific focus on preventing the increase of hospitalized individuals and total cases.', 'More people in quarantine lead to a lower total number of cases, as observed from the relationship between home quarantine and total cases.', 'The total number of cases is around 100,000 and the home quarantine population exceeds 40,000, indicating the potential impact of home quarantine on reducing the total number of cases.', 'The analysis also uncovers a concerning trend as more than 10,000 people have died from the disease in the last 34 days in Italy, with the number of deaths reaching a level comparable to the number of recoveries.']}