title
Full Power BI Guided Project | Microsoft Power BI for Beginners

description
In this video we will be walking through a full project in Power BI! Download Microsoft Power BI: https://powerbi.microsoft.com/en-us/downloads/ Download Project Dataset: https://github.com/AlexTheAnalyst/Power-BI/blob/main/Power%20BI%20-%20Final%20Project.xlsx Favorite Power BI Courses: Power BI for Business Intelligence - https://bit.ly/3Nfi59i Power BI A-Z - https://bit.ly/3MkpYKw ____________________________________________ SUBSCRIBE! Do you want to become a Data Analyst? That's what this channel is all about! My goal is to help you learn everything you need in order to start your career or even switch your career into Data Analytics. Be sure to subscribe to not miss out on any content! ____________________________________________ RESOURCES: Coursera Courses: 📖Google Data Analyst Certification: https://coursera.pxf.io/5bBd62 📖Data Analysis with Python - https://coursera.pxf.io/BXY3Wy 📖IBM Data Analysis Specialization - https://coursera.pxf.io/AoYOdR 📖Tableau Data Visualization - https://coursera.pxf.io/MXYqaN Udemy Courses: 📖Python for Data Analysis and Visualization- https://bit.ly/3hhX4LX 📖Statistics for Data Science - https://bit.ly/37jqDbq 📖SQL for Data Analysts (SSMS) - https://bit.ly/3fkqEij 📖Tableau A-Z - http://bit.ly/385lYvN *Please note I may earn a small commission for any purchase through these links - Thanks for supporting the channel!* ____________________________________________ SUPPORT MY CHANNEL - PATREON/MERCH 🙌Patreon Page - https://www.patreon.com/AlexTheAnalyst 💻Alex The Analyst Shop - https://teespring.com/stores/alex-the-analyst-shop ____________________________________________ Websites: 💻Website: AlexTheAnalyst.com 💾GitHub: https://github.com/AlexTheAnalyst 📱Instagram: @Alex_The_Analyst ____________________________________________ *All opinions or statements in this video are my own and do not reflect the opinion of the company I work for or have ever worked for*

detail
{'title': 'Full Power BI Guided Project | Microsoft Power BI for Beginners', 'heatmap': [{'end': 898.611, 'start': 869.263, 'weight': 1}], 'summary': 'The power bi tutorial series showcases a final project using real survey data from 600-700 data professionals, covering data collection, cleaning, manipulation, visualization, and dashboard building, providing insights on cost of living, work-life balance analysis, and project tips for data organization and visualization.', 'chapters': [{'end': 257.392, 'segs': [{'end': 32.701, 'src': 'embed', 'start': 0.109, 'weight': 3, 'content': [{'end': 0.889, 'text': "What's going on everybody.", 'start': 0.109, 'duration': 0.78}, {'end': 3.01, 'text': 'Welcome back to the Power BI tutorial series.', 'start': 0.949, 'duration': 2.061}, {'end': 5.531, 'text': "Today, we're going to be working on our final project.", 'start': 3.25, 'duration': 2.281}, {'end': 14.693, 'text': 'Now this is our final project of the Power BI tutorial series.', 'start': 11.793, 'duration': 2.9}, {'end': 17.994, 'text': 'So, if you have not watched all of those videos leading up to this,', 'start': 14.733, 'duration': 3.261}, {'end': 23.176, 'text': "I recommend going and watching those videos so you can make sure that you know all the things that we're going to be looking at in today's project.", 'start': 17.994, 'duration': 5.182}, {'end': 25.557, 'text': 'I am really excited to work on this project with you,', 'start': 23.516, 'duration': 2.041}, {'end': 32.701, 'text': 'because I think it is a really good one and it uses real data that we collected about a month ago, where I took a survey of data professionals,', 'start': 25.557, 'duration': 7.144}], 'summary': 'Final power bi tutorial project using real data collected from data professionals.', 'duration': 32.592, 'max_score': 0.109, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/pixlHHe_lNQ/pics/pixlHHe_lNQ109.jpg'}, {'end': 89.407, 'src': 'embed', 'start': 60.89, 'weight': 0, 'content': [{'end': 67.034, 'text': 'Now, in the past several projects, we have been using this fake apocalypse dataset.', 'start': 60.89, 'duration': 6.144}, {'end': 68.255, 'text': 'You know, it was fun.', 'start': 67.054, 'duration': 1.201}, {'end': 69.475, 'text': 'It was, you know, whatever.', 'start': 68.315, 'duration': 1.16}, {'end': 71.216, 'text': 'This dataset is real.', 'start': 70.096, 'duration': 1.12}, {'end': 72.177, 'text': 'This is a real dataset.', 'start': 71.256, 'duration': 0.921}, {'end': 74.539, 'text': 'It was a survey that I took from data professionals.', 'start': 72.197, 'duration': 2.342}, {'end': 75.299, 'text': 'I posted on LinkedIn.', 'start': 74.579, 'duration': 0.72}, {'end': 80.902, 'text': 'in and twitter and all these other places, and we had about 600 700 people who responded to the questions.', 'start': 75.479, 'duration': 5.423}, {'end': 89.407, 'text': 'so before we actually get into it and start cleaning the data and doing all this stuff in power bi, i just wanted to show you the data all right.', 'start': 80.902, 'duration': 8.505}], 'summary': 'A real dataset from 600-700 data professionals used for past projects.', 'duration': 28.517, 'max_score': 60.89, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/pixlHHe_lNQ/pics/pixlHHe_lNQ60890.jpg'}, {'end': 237.426, 'src': 'embed', 'start': 212.217, 'weight': 2, 'content': [{'end': 218.62, 'text': 'What industry do you work in? Favorite programming language? Then there were a lot of different options.', 'start': 212.217, 'duration': 6.403}, {'end': 221.941, 'text': 'So this is like one question where they picked multiple options.', 'start': 218.64, 'duration': 3.301}, {'end': 227.542, 'text': 'So is how happy are you in your current position with the following? You have your salary, work life balance.', 'start': 222.101, 'duration': 5.441}, {'end': 237.426, 'text': 'Then we have coworkers, management, upward mobility, learning new things, and they could rank it from zero to 10.', 'start': 229.163, 'duration': 8.263}], 'summary': 'Surveyed employees rated job satisfaction on multiple factors, including salary and work-life balance.', 'duration': 25.209, 'max_score': 212.217, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/pixlHHe_lNQ/pics/pixlHHe_lNQ212217.jpg'}], 'start': 0.109, 'title': 'Power bi final project and real data survey analysis', 'summary': 'Focuses on the final project of the power bi tutorial series, utilizing real data collected from a survey of data professionals conducted a month prior, transforming the data using power query, creating visualizations and dashboards, and applying a unique theme and color scheme. it also introduces a real survey dataset with 600-700 responses from data professionals, showcasing the raw data and discussing the approach for data cleaning and transformation using power bi.', 'chapters': [{'end': 60.81, 'start': 0.109, 'title': 'Power bi final project', 'summary': 'Focuses on the final project of the power bi tutorial series, utilizing real data collected from a survey of data professionals conducted a month prior, transforming the data using power query, creating visualizations and dashboards, and applying a unique theme and color scheme.', 'duration': 60.701, 'highlights': ['The chapter focuses on the final project of the Power BI tutorial series The final project of the Power BI tutorial series is the main focus, indicating the culmination of the series.', 'Utilizing real data collected from a survey of data professionals conducted a month prior Real data collected from a survey of data professionals about a month ago is being utilized for the project, adding authenticity and relevance.', 'Transforming the data using Power Query and creating visualizations and dashboards The process involves transforming the collected raw data using Power Query and creating visualizations and dashboards, demonstrating practical application of Power BI skills.', 'Applying a unique theme and color scheme to the project The project involves applying a unique theme and color scheme to enhance the visual appeal, promoting creativity and customization.']}, {'end': 257.392, 'start': 60.89, 'title': 'Real data survey analysis', 'summary': 'Introduces a real survey dataset with 600-700 responses from data professionals, showcasing the raw data and discussing the approach for data cleaning and transformation using power bi.', 'duration': 196.502, 'highlights': ['The survey dataset was collected from 600-700 data professionals through LinkedIn, Twitter, and other platforms, providing real and raw data for analysis.', 'The chapter emphasizes using Power BI for data transformation, avoiding extensive data cleaning in Excel, and focuses on showcasing the raw dataset and discussing the approach for data cleaning and transformation.', "The dataset includes questions on job titles, yearly salary, industry, favorite programming language, satisfaction levels, and job preferences, providing diverse insights into the data professionals' backgrounds and preferences."]}], 'duration': 257.283, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/pixlHHe_lNQ/pics/pixlHHe_lNQ109.jpg', 'highlights': ['Utilizing real data collected from a survey of data professionals conducted a month prior Real data collected from a survey of data professionals about a month ago is being utilized for the project, adding authenticity and relevance.', 'The survey dataset was collected from 600-700 data professionals through LinkedIn, Twitter, and other platforms, providing real and raw data for analysis.', "The dataset includes questions on job titles, yearly salary, industry, favorite programming language, satisfaction levels, and job preferences, providing diverse insights into the data professionals' backgrounds and preferences.", 'The chapter focuses on the final project of the Power BI tutorial series The final project of the Power BI tutorial series is the main focus, indicating the culmination of the series.']}, {'end': 646.085, 'segs': [{'end': 305.321, 'src': 'embed', 'start': 257.632, 'weight': 0, 'content': [{'end': 261.954, 'text': 'We have male, female, which country are you from? And then this is more like demographics.', 'start': 257.632, 'duration': 4.322}, {'end': 265.677, 'text': "So if you're male, how old you are, and this was in a range.", 'start': 262.155, 'duration': 3.522}, {'end': 268.499, 'text': 'So this is like a, uh, uh, a sliding bar.', 'start': 265.717, 'duration': 2.782}, {'end': 270.78, 'text': 'So you could slide it to the exact age you had.', 'start': 268.539, 'duration': 2.241}, {'end': 274.242, 'text': "There's some people who are apparently 92.", 'start': 271.301, 'duration': 2.941}, {'end': 279.105, 'text': "Um, which if that's true, I mean, good for you, man or woman actually really quickly.", 'start': 274.242, 'duration': 4.863}, {'end': 279.486, 'text': "I'm gonna see.", 'start': 279.125, 'duration': 0.361}, {'end': 283.627, 'text': "Just, just while we're here, I'm going to see if this is a male, a male or a female.", 'start': 280.185, 'duration': 3.442}, {'end': 285.749, 'text': "That's a female from India.", 'start': 284.288, 'duration': 1.461}, {'end': 286.209, 'text': 'Very cool.', 'start': 285.829, 'duration': 0.38}, {'end': 293.013, 'text': 'Um, so we have all this information and it is a lot of information when you have something like this.', 'start': 286.949, 'duration': 6.064}, {'end': 297.056, 'text': 'I mean, there is so much data cleaning that can be done.', 'start': 293.173, 'duration': 3.883}, {'end': 305.321, 'text': 'I mean, I already see like 20 plus different things that I would need to do to make this a lot better.', 'start': 297.396, 'duration': 7.925}], 'summary': 'Demographics data collected with male, female, and age range. data cleaning needed.', 'duration': 47.689, 'max_score': 257.632, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/pixlHHe_lNQ/pics/pixlHHe_lNQ257632.jpg'}, {'end': 352.038, 'src': 'embed', 'start': 327.409, 'weight': 2, 'content': [{'end': 334.352, 'text': "doing a lot more data cleaning and creating a much more advanced visualization with what we have and what we're looking at right here.", 'start': 327.409, 'duration': 6.943}, {'end': 343.215, 'text': "But for this video we're just gonna be doing a pretty simple visualization and dashboard that you can use to practice with or put it on your portfolio,", 'start': 334.432, 'duration': 8.783}, {'end': 343.635, 'text': 'if you know.', 'start': 343.215, 'duration': 0.42}, {'end': 344.495, 'text': "that's where you're at right now.", 'start': 343.635, 'duration': 0.86}, {'end': 347.896, 'text': "So let's get out of here and let's put this into Power BI.", 'start': 344.855, 'duration': 3.041}, {'end': 352.038, 'text': "So let's exit out and let's come right over here to import data from Excel.", 'start': 348.076, 'duration': 3.962}], 'summary': 'Enhancing data visualization and creating a simple dashboard in power bi.', 'duration': 24.629, 'max_score': 327.409, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/pixlHHe_lNQ/pics/pixlHHe_lNQ327409.jpg'}, {'end': 399.527, 'src': 'embed', 'start': 372.384, 'weight': 3, 'content': [{'end': 376.226, 'text': 'And now we have all of our data in here, and it should look extremely familiar.', 'start': 372.384, 'duration': 3.842}, {'end': 380.369, 'text': "Now, when I'm looking at this, when I start..", 'start': 377.707, 'duration': 2.662}, {'end': 386.658, 'text': 'looking at this information, I kind of need to know beforehand what I want to get out of this.', 'start': 381.354, 'duration': 5.304}, {'end': 394.203, 'text': "Do I need to clean every single column? Do I just need to clean a few of them? Do I need to get rid of columns? That's kind of where my head's at.", 'start': 387.238, 'duration': 6.965}, {'end': 399.527, 'text': 'And so right off the bat, I can already tell you that there are columns that we can just delete to get out of our way.', 'start': 394.263, 'duration': 5.264}], 'summary': 'Data cleaning process involves deciding which columns to clean or delete.', 'duration': 27.143, 'max_score': 372.384, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/pixlHHe_lNQ/pics/pixlHHe_lNQ372384.jpg'}], 'start': 257.632, 'title': 'Data collection, cleaning, and visualization', 'summary': 'Covers demographic data collection focusing on challenges, improvements, and data cleaning and visualization in power bi, highlighting simplification, standardization, and organization for better analysis.', 'chapters': [{'end': 305.321, 'start': 257.632, 'title': 'Demographic data collection', 'summary': 'Discusses the collection of demographic data, including gender, age range, and country of origin, with a focus on the challenges of data cleaning and potential improvements, such as using sliding bars for age input and identifying gender and nationality.', 'duration': 47.689, 'highlights': ['The process involves collecting demographic data such as gender, age range, and country of origin, with a focus on data cleaning and potential improvements (e.g., using sliding bars for age input and identifying gender and nationality).', 'Challenges related to data cleaning are mentioned, with the speaker identifying over 20 different tasks that could be done to improve the data quality.', 'The speaker observes the diversity in age range, noting that some individuals are as old as 92 years, showcasing the broad spectrum of participants involved in the data collection.']}, {'end': 646.085, 'start': 306.036, 'title': 'Data cleaning and visualization in power bi', 'summary': 'Discusses data cleaning and visualization in power bi, showcasing the process of simplifying and standardizing data for better visualization, including removing unnecessary columns, standardizing categories, and using custom delimiters to clean and organize data for effective visualization and analysis.', 'duration': 340.049, 'highlights': ['The process of simplifying and standardizing data for better visualization The chapter focuses on streamlining the data for improved visualization and analysis, aiming to reduce complexity and standardize categories to facilitate effective data representation and interpretation.', 'Removing unnecessary columns to declutter the dataset The presenter emphasizes the importance of removing irrelevant columns at the beginning of the process to avoid clutter and streamline the dataset, enhancing the efficiency of data analysis and visualization.', 'Using custom delimiters to clean and organize data The tutorial demonstrates the use of custom delimiters to separate and organize data, showcasing the practical application of this technique to simplify and structure the dataset for efficient analysis and visualization.']}], 'duration': 388.453, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/pixlHHe_lNQ/pics/pixlHHe_lNQ257632.jpg', 'highlights': ['Challenges related to data cleaning are mentioned, with the speaker identifying over 20 different tasks that could be done to improve the data quality.', 'The process involves collecting demographic data such as gender, age range, and country of origin, with a focus on data cleaning and potential improvements (e.g., using sliding bars for age input and identifying gender and nationality).', 'The process of simplifying and standardizing data for better visualization The chapter focuses on streamlining the data for improved visualization and analysis, aiming to reduce complexity and standardize categories to facilitate effective data representation and interpretation.', 'Removing unnecessary columns to declutter the dataset The presenter emphasizes the importance of removing irrelevant columns at the beginning of the process to avoid clutter and streamline the dataset, enhancing the efficiency of data analysis and visualization.', 'Using custom delimiters to clean and organize data The tutorial demonstrates the use of custom delimiters to separate and organize data, showcasing the practical application of this technique to simplify and structure the dataset for efficient analysis and visualization.', 'The speaker observes the diversity in age range, noting that some individuals are as old as 92 years, showcasing the broad spectrum of participants involved in the data collection.']}, {'end': 1062.791, 'segs': [{'end': 722.116, 'src': 'embed', 'start': 692.834, 'weight': 4, 'content': [{'end': 694.275, 'text': "Let's see if we can use it.", 'start': 692.834, 'duration': 1.441}, {'end': 699.617, 'text': "Here's what I wanna do with it, and this is not perfect, but for this video, I wanna try it.", 'start': 695.175, 'duration': 4.442}, {'end': 707.541, 'text': "What I wanna do is break up these numbers, 106, 125, and then take the average of those numbers, then we'll use some docs in there.", 'start': 700.118, 'duration': 7.423}, {'end': 716.15, 'text': "we'll take 106, 125, create that into two separate columns, then we'll create a third column that will give us the average of those two numbers.", 'start': 708.223, 'duration': 7.927}, {'end': 722.116, 'text': "so we'll do 106 plus 125, divided by two, and then we'll have the average of that.", 'start': 716.15, 'duration': 5.966}], 'summary': 'Break up 106,125, find their average, and use the result in a video.', 'duration': 29.282, 'max_score': 692.834, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/pixlHHe_lNQ/pics/pixlHHe_lNQ692834.jpg'}, {'end': 762.617, 'src': 'embed', 'start': 738.269, 'weight': 3, 'content': [{'end': 744.113, 'text': "it's a numeric value instead of being this, which is text which we really we could use,", 'start': 738.269, 'duration': 5.844}, {'end': 746.714, 'text': "and and i'll show you how to do that because we're going to keep this column,", 'start': 744.113, 'duration': 2.601}, {'end': 756.109, 'text': "i'll create a copy of this and i'll show you the difference between this and using the average, but for But for this data cleaning portion.", 'start': 746.714, 'duration': 9.395}, {'end': 757.212, 'text': "let's just try it.", 'start': 756.109, 'duration': 1.103}, {'end': 759.64, 'text': "Let's see what we can do and see if we can make it work.", 'start': 757.353, 'duration': 2.287}, {'end': 762.617, 'text': "So first let's create a duplicate.", 'start': 760.475, 'duration': 2.142}], 'summary': 'Demonstrating numeric data conversion and duplicate creation for data cleaning.', 'duration': 24.348, 'max_score': 738.269, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/pixlHHe_lNQ/pics/pixlHHe_lNQ738269.jpg'}, {'end': 812.421, 'src': 'embed', 'start': 784.773, 'weight': 1, 'content': [{'end': 789.337, 'text': "Then we're going to click on split column and we'll do it by digit to non-digit.", 'start': 784.773, 'duration': 4.564}, {'end': 800.116, 'text': "And if you look at it right here, it's broken it out kind of, um, in the fact that now in this one, we just have numeric values.", 'start': 791.392, 'duration': 8.724}, {'end': 805.718, 'text': 'And in this one, we have K dash numeric or just dash numeric.', 'start': 800.796, 'duration': 4.922}, {'end': 808.459, 'text': 'And now this can be easily cleaned.', 'start': 806.699, 'duration': 1.76}, {'end': 812.421, 'text': "Whereas this one we can just completely get rid of cause it's only K.", 'start': 809, 'duration': 3.421}], 'summary': 'Data split by digit to non-digit, enabling easy cleaning and removal of unnecessary values.', 'duration': 27.648, 'max_score': 784.773, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/pixlHHe_lNQ/pics/pixlHHe_lNQ784773.jpg'}, {'end': 898.611, 'src': 'heatmap', 'start': 869.263, 'weight': 1, 'content': [{'end': 870.704, 'text': "That's just what we're gonna put it as.", 'start': 869.263, 'duration': 1.441}, {'end': 871.624, 'text': "And there's only two people.", 'start': 870.724, 'duration': 0.9}, {'end': 874.426, 'text': "So, uh, I'm actually gonna replace this.", 'start': 871.704, 'duration': 2.722}, {'end': 876.308, 'text': "I'm gonna do replace values.", 'start': 874.446, 'duration': 1.862}, {'end': 880.971, 'text': "I'm gonna say plus 225 and we'll click.", 'start': 876.328, 'duration': 4.643}, {'end': 883.113, 'text': 'Okay Awesome.', 'start': 881.071, 'duration': 2.042}, {'end': 884.254, 'text': 'We can unfilter these.', 'start': 883.313, 'duration': 0.941}, {'end': 888.703, 'text': "So we're going to go right up here to add column.", 'start': 886.561, 'duration': 2.142}, {'end': 894.167, 'text': "I'm going to say custom column, and we're going to go right over here.", 'start': 889.443, 'duration': 4.724}, {'end': 898.611, 'text': "Actually, let's make it a average salary.", 'start': 894.247, 'duration': 4.364}], 'summary': 'Replacing values with +225, adding custom column for average salary.', 'duration': 29.348, 'max_score': 869.263, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/pixlHHe_lNQ/pics/pixlHHe_lNQ869263.jpg'}, {'end': 1006.579, 'src': 'embed', 'start': 949.409, 'weight': 0, 'content': [{'end': 950.509, 'text': "Let's try this all again.", 'start': 949.409, 'duration': 1.1}, {'end': 951.93, 'text': 'See if I can make it work.', 'start': 950.529, 'duration': 1.401}, {'end': 960.173, 'text': 'Insert this one plus this one.', 'start': 953.51, 'duration': 6.663}, {'end': 963.094, 'text': "And we'll do divided by two.", 'start': 960.193, 'duration': 2.901}, {'end': 964.535, 'text': "And let's try this one.", 'start': 963.835, 'duration': 0.7}, {'end': 966.452, 'text': 'And there we go.', 'start': 965.57, 'duration': 0.882}, {'end': 967.995, 'text': "So now let's get rid of this column.", 'start': 966.472, 'duration': 1.523}, {'end': 972.825, 'text': 'Columns And we can actually remove these ones as well.', 'start': 969.559, 'duration': 3.266}, {'end': 975.591, 'text': 'Because now we have this..', 'start': 974.228, 'duration': 1.363}, {'end': 986.247, 'text': 'average salary column which, when we look at this or when we use this, uh, we can.', 'start': 978.642, 'duration': 7.605}, {'end': 988.708, 'text': 'let me see if i can just move this way way, way over.', 'start': 986.247, 'duration': 2.461}, {'end': 991.85, 'text': "all right, i might cut, because it's taking forever.", 'start': 988.708, 'duration': 3.142}, {'end': 994.572, 'text': "so if you take the average of these two numbers, you'll get 53.", 'start': 991.85, 'duration': 2.722}, {'end': 997.633, 'text': "if you take the average of 0 and 40, you'll get 20..", 'start': 994.572, 'duration': 3.061}, {'end': 1002.376, 'text': 'so now we have this average salary and again, When we get to the actual visualization part,', 'start': 997.633, 'duration': 4.743}, {'end': 1006.579, 'text': "I'll show you why this isn't as useful as having this average salary.", 'start': 1002.376, 'duration': 4.203}], 'summary': 'Data manipulation and visualization. average salary of 53 derived from 0 and 40.', 'duration': 57.17, 'max_score': 949.409, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/pixlHHe_lNQ/pics/pixlHHe_lNQ949409.jpg'}], 'start': 646.605, 'title': 'Data cleaning and manipulation techniques', 'summary': 'Covers data cleaning techniques such as splitting, deleting unwanted columns, and calculating averages. it also addresses data manipulation techniques including duplicating columns, removing unwanted values, and replacing values, resulting in a more usable dataset for visualization.', 'chapters': [{'end': 738.269, 'start': 646.605, 'title': 'Data cleaning and analysis techniques', 'summary': 'Discusses data cleaning techniques including splitting columns, deleting unwanted columns, and calculating averages to make the data usable, with the example of breaking up yearly salary data into two separate columns and calculating the average.', 'duration': 91.664, 'highlights': ['The chapter discusses data cleaning techniques including splitting columns, deleting unwanted columns, and calculating averages to make the data usable, with the example of breaking up yearly salary data into two separate columns and calculating the average.', "Usage of delimiter 'colon' to split columns, and the use of mathematical operations to calculate the average of two numbers is explained.", 'Consideration of practicality and imperfection in the data cleaning technique is mentioned, emphasizing the usability and practicality of the calculated average for the given salary range.']}, {'end': 1062.791, 'start': 738.269, 'title': 'Data cleaning and column manipulation', 'summary': 'Covers data cleaning and manipulation techniques, including duplicating columns, splitting columns, removing unwanted values, replacing values, calculating average salary, and addressing data usability issues, resulting in a more usable dataset for visualization.', 'duration': 324.522, 'highlights': ["The process involves duplicating columns, splitting them by digit to non-digit, and removing unwanted values such as 'K' and special characters, resulting in a cleaner dataset for analysis.", "The average salary is calculated by replacing values such as 'plus' with the intended numeric values and then performing the calculation, ensuring accurate representation of salary data.", "The chapter emphasizes the limitations of the data cleaning approach, stating that it is not perfect and may not be the preferred method in other scenarios, but it improves the dataset's usability for the current analysis.", 'Further data manipulation techniques are discussed, including breaking out values for industry and country, acknowledging challenges in normalizing country names for effective analysis.', 'The implementation of data cleaning and manipulation techniques results in a more usable dataset, addressing specific challenges and preparing the data for visualization and analysis.']}], 'duration': 416.186, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/pixlHHe_lNQ/pics/pixlHHe_lNQ646605.jpg', 'highlights': ['The chapter discusses data cleaning techniques including splitting columns, deleting unwanted columns, and calculating averages to make the data usable, with the example of breaking up yearly salary data into two separate columns and calculating the average.', "The process involves duplicating columns, splitting them by digit to non-digit, and removing unwanted values such as 'K' and special characters, resulting in a cleaner dataset for analysis.", "The average salary is calculated by replacing values such as 'plus' with the intended numeric values and then performing the calculation, ensuring accurate representation of salary data.", 'The implementation of data cleaning and manipulation techniques results in a more usable dataset, addressing specific challenges and preparing the data for visualization and analysis.', "Usage of delimiter 'colon' to split columns, and the use of mathematical operations to calculate the average of two numbers is explained."]}, {'end': 1742.935, 'segs': [{'end': 1149.401, 'src': 'embed', 'start': 1090.44, 'weight': 0, 'content': [{'end': 1096.122, 'text': "And I think, you know, there is, let me tell you, there's so much more that we could do with this.", 'start': 1090.44, 'duration': 5.682}, {'end': 1099.204, 'text': 'I mean, just so many other things.', 'start': 1096.343, 'duration': 2.861}, {'end': 1104.246, 'text': 'But this is like what the bare minimum of what we need for this project.', 'start': 1099.904, 'duration': 4.342}, {'end': 1107.728, 'text': "So let's go ahead and close and apply this.", 'start': 1104.726, 'duration': 3.002}, {'end': 1112.832, 'text': 'And if we need to come back at any point and actually fix anything or change anything, we can.', 'start': 1108.288, 'duration': 4.544}, {'end': 1114.393, 'text': "So it's not like that's permanent.", 'start': 1113.132, 'duration': 1.261}, {'end': 1116.575, 'text': 'So as you can see, we have everything over here.', 'start': 1114.893, 'duration': 1.682}, {'end': 1120.898, 'text': 'We have all of our data as it is transformed in here as well.', 'start': 1117.115, 'duration': 3.783}, {'end': 1125.562, 'text': 'And now we can start building out our visualization.', 'start': 1121.959, 'duration': 3.603}, {'end': 1130.286, 'text': "Let's go back to our report and let's start building something out.", 'start': 1125.582, 'duration': 4.704}, {'end': 1133.268, 'text': "So let's add a title to our dashboard.", 'start': 1130.306, 'duration': 2.962}, {'end': 1136.711, 'text': 'Make this right at the top.', 'start': 1135.069, 'duration': 1.642}, {'end': 1145.078, 'text': 'Call this the data professional survey breakdown.', 'start': 1138.353, 'duration': 6.725}, {'end': 1149.401, 'text': "And let's make that quite a bit larger.", 'start': 1147.1, 'duration': 2.301}], 'summary': 'Bare minimum data for project, building visualization, survey breakdown.', 'duration': 58.961, 'max_score': 1090.44, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/pixlHHe_lNQ/pics/pixlHHe_lNQ1090440.jpg'}, {'end': 1264.32, 'src': 'embed', 'start': 1217.523, 'weight': 4, 'content': [{'end': 1219.144, 'text': 'Survey takers.', 'start': 1217.523, 'duration': 1.621}, {'end': 1223.888, 'text': 'And you can say whatever you want here, but in, in general, that is what it is.', 'start': 1220.025, 'duration': 3.863}, {'end': 1228.752, 'text': "We're, we're counting how many people, um you know, took this survey,", 'start': 1224.088, 'duration': 4.664}, {'end': 1233.676, 'text': "and that's just a kind of a total maybe actually I say total amount or of survey takers,", 'start': 1228.752, 'duration': 4.924}, {'end': 1237.259, 'text': 'but you can say count of survey takers how many people took the survey.', 'start': 1233.676, 'duration': 3.583}, {'end': 1238.88, 'text': "So let's click out of there.", 'start': 1237.699, 'duration': 1.181}, {'end': 1240.221, 'text': "Let's click on card.", 'start': 1239.2, 'duration': 1.021}, {'end': 1242.743, 'text': "Let's make it about the same size.", 'start': 1240.241, 'duration': 2.502}, {'end': 1243.924, 'text': "We're gonna drag it up here.", 'start': 1242.823, 'duration': 1.101}, {'end': 1247.708, 'text': 'Right And make them about the same.', 'start': 1246.687, 'duration': 1.021}, {'end': 1249.629, 'text': "We will in a little bit, we'll make them the same size.", 'start': 1247.748, 'duration': 1.881}, {'end': 1252.852, 'text': "Um, but for this one, we're gonna look at age.", 'start': 1250.41, 'duration': 2.442}, {'end': 1254.593, 'text': "So we're gonna look at current age.", 'start': 1252.872, 'duration': 1.721}, {'end': 1259.216, 'text': "So I'm gonna click on that and we'll say we want the average age.", 'start': 1254.613, 'duration': 4.603}, {'end': 1263.039, 'text': 'So our average age taker is almost 30 years old.', 'start': 1259.877, 'duration': 3.162}, {'end': 1264.32, 'text': "So let's go right over here.", 'start': 1263.059, 'duration': 1.261}], 'summary': 'Survey shows average age of takers is nearly 30 years.', 'duration': 46.797, 'max_score': 1217.523, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/pixlHHe_lNQ/pics/pixlHHe_lNQ1217523.jpg'}, {'end': 1333.578, 'src': 'embed', 'start': 1307.924, 'weight': 8, 'content': [{'end': 1312.869, 'text': "So let's go ahead and click on the cluster bar chart and create as small or as large as we'd like.", 'start': 1307.924, 'duration': 4.945}, {'end': 1316.552, 'text': "And for this one, we're gonna be looking at the job titles.", 'start': 1313.79, 'duration': 2.762}, {'end': 1324.029, 'text': 'Now, remember we kind of change the job titles or, you know, uh, transform those if you want to say that.', 'start': 1316.673, 'duration': 7.356}, {'end': 1328.513, 'text': "So we're gonna look at job titles and then we're going to look at their average salary.", 'start': 1324.589, 'duration': 3.924}, {'end': 1331.636, 'text': 'And if you remember, we transformed that one as well.', 'start': 1328.533, 'duration': 3.103}, {'end': 1333.578, 'text': 'We have average average salary.', 'start': 1331.836, 'duration': 1.742}], 'summary': 'Analyze job titles and their average salary from transformed data.', 'duration': 25.654, 'max_score': 1307.924, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/pixlHHe_lNQ/pics/pixlHHe_lNQ1307924.jpg'}, {'end': 1407.156, 'src': 'embed', 'start': 1376.001, 'weight': 6, 'content': [{'end': 1377.762, 'text': 'So we can click average right here.', 'start': 1376.001, 'duration': 1.761}, {'end': 1382.845, 'text': 'And what we want to do is actually break this down by the job title.', 'start': 1378.623, 'duration': 4.222}, {'end': 1387.468, 'text': 'And so now we can see data scientists are making the most by far.', 'start': 1383.145, 'duration': 4.323}, {'end': 1391.931, 'text': "They're making average of 93,000, at least from the survey takers that took it.", 'start': 1387.708, 'duration': 4.223}, {'end': 1396.033, 'text': 'Then we have our data engineers making 65,000.', 'start': 1392.631, 'duration': 3.402}, {'end': 1398.635, 'text': 'Data architects are making 63.', 'start': 1396.033, 'duration': 2.602}, {'end': 1400.196, 'text': "And then we're the data analyst.", 'start': 1398.635, 'duration': 1.561}, {'end': 1402.893, 'text': 'Data analysts are right here making 55.', 'start': 1400.712, 'duration': 2.181}, {'end': 1407.156, 'text': 'So again, we had 630 people take this survey.', 'start': 1402.893, 'duration': 4.263}], 'summary': 'Data scientists make the most, averaging $93,000, from a survey of 630 people.', 'duration': 31.155, 'max_score': 1376.001, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/pixlHHe_lNQ/pics/pixlHHe_lNQ1376001.jpg'}, {'end': 1575.418, 'src': 'embed', 'start': 1545.72, 'weight': 7, 'content': [{'end': 1548.981, 'text': "Let's do a clustered column chart.", 'start': 1545.72, 'duration': 3.261}, {'end': 1550.702, 'text': 'Click on this right here.', 'start': 1549.641, 'duration': 1.061}, {'end': 1555.104, 'text': 'And it looks like, here we go.', 'start': 1551.562, 'duration': 3.542}, {'end': 1556.945, 'text': "That is kind of what we're looking for.", 'start': 1555.684, 'duration': 1.261}, {'end': 1563.768, 'text': "And instead of count of unique ID, we'll say count of, let's do count of voters.", 'start': 1556.965, 'duration': 6.803}, {'end': 1575.418, 'text': "And for favorite programming language, we'll say, Favorite, oops, favorite programming language and get rid of that as well.", 'start': 1565.869, 'duration': 9.549}], 'summary': 'Creating a clustered column chart with count of voters for favorite programming languages.', 'duration': 29.698, 'max_score': 1545.72, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/pixlHHe_lNQ/pics/pixlHHe_lNQ1545720.jpg'}], 'start': 1063.352, 'title': 'Data visualization and dashboard building', 'summary': 'Covers the quick data transformation process, building visualizations, and customization of a dashboard for a data professional survey breakdown. it also includes creating visualizations for survey data to provide high-level insights for easy interpretation, such as displaying the count of survey takers, average age visual, average salaries by job title, and favorite programming languages.', 'chapters': [{'end': 1175.932, 'start': 1063.352, 'title': 'Data visualization and dashboard building', 'summary': 'Covers the quick data transformation process, the start of building visualizations, and the customization of a dashboard for a data professional survey breakdown.', 'duration': 112.58, 'highlights': ['The process of data transformation and split-up of options for a project is briefed, with the mention of the bare minimum needed for the project and the flexibility to revisit and make changes if required.', 'Guidance is provided on adding a title, adjusting the size, making it bold, centering it, and changing the background for a dashboard.', 'Emphasis is placed on starting the visualization building process with the transformed data.', 'The narrator expresses the potential for further enhancements beyond the minimum requirements for the project.']}, {'end': 1742.935, 'start': 1175.952, 'title': 'Creating visualizations for survey data', 'summary': 'Covers creating visualizations for survey data, including a card to display the count of survey takers, an average age visual, a clustered bar chart to display average salaries by job title, and a clustered column chart for favorite programming languages, aiming to provide high-level insights for easy interpretation.', 'duration': 566.983, 'highlights': ['The chapter starts with creating a card to display the count of survey takers, with 630 people taking the survey, followed by an average age visual showing the average age of survey takers to be almost 30 years old.', 'A clustered bar chart is then created to display average salaries by job title, revealing data scientists making the most at an average of 93,000, followed by data engineers at 65,000, data architects at 63,000, and data analysts at 55,000, with 630 people taking the survey.', 'Another visualization is a clustered column chart for favorite programming languages, where Python is the most popular, followed by C++, JavaScript, and Java, providing insights into the popularity of programming languages among the survey takers.', 'Lastly, a tree map is chosen to represent geographical distribution and its impact on average salaries for different roles, demonstrating the varying average salaries for data scientists and data analysts in different countries, highlighting the importance of considering geographical factors in salary analysis.']}], 'duration': 679.583, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/pixlHHe_lNQ/pics/pixlHHe_lNQ1063352.jpg', 'highlights': ['Creating visualizations for survey data to provide high-level insights for easy interpretation', 'Guidance on adding a title, adjusting the size, making it bold, centering it, and changing the background for a dashboard', 'Starting the visualization building process with the transformed data', 'Emphasizing the potential for further enhancements beyond the minimum requirements for the project', 'Creating a card to display the count of survey takers, with 630 people taking the survey', 'Creating an average age visual showing the average age of survey takers to be almost 30 years old', 'Creating a clustered bar chart to display average salaries by job title, revealing data scientists making the most at an average of 93,000', 'Creating a clustered column chart for favorite programming languages, where Python is the most popular, followed by C++, JavaScript, and Java', 'Choosing a tree map to represent geographical distribution and its impact on average salaries for different roles']}, {'end': 1961.387, 'segs': [{'end': 1770.703, 'src': 'embed', 'start': 1742.955, 'weight': 0, 'content': [{'end': 1745.536, 'text': "That doesn't mean that they make less money in India.", 'start': 1742.955, 'duration': 2.581}, {'end': 1749.318, 'text': 'That just means that the cost of living is probably lower in India.', 'start': 1745.556, 'duration': 3.762}, {'end': 1752.459, 'text': "Therefore they don't need the higher us dollars salary.", 'start': 1749.378, 'duration': 3.081}, {'end': 1754.28, 'text': 'Cause again, this was all done in us dollars.', 'start': 1752.479, 'duration': 1.801}, {'end': 1756.079, 'text': 'So just something to think about.', 'start': 1754.599, 'duration': 1.48}, {'end': 1757.16, 'text': "Let's click out of that.", 'start': 1756.399, 'duration': 0.761}, {'end': 1758.7, 'text': "So we'll keep that one as well.", 'start': 1757.34, 'duration': 1.36}, {'end': 1760.96, 'text': "So now let's create our next visualization.", 'start': 1759.08, 'duration': 1.88}, {'end': 1764.141, 'text': 'This is one that I do not get to use enough in my actual job.', 'start': 1760.98, 'duration': 3.161}, {'end': 1765.762, 'text': "So we're going to use it in this project.", 'start': 1764.181, 'duration': 1.581}, {'end': 1767.722, 'text': "And it's going to be this gauge right here.", 'start': 1766.002, 'duration': 1.72}, {'end': 1769.342, 'text': "So let's add that one.", 'start': 1768.362, 'duration': 0.98}, {'end': 1770.703, 'text': 'Put it right over here.', 'start': 1769.863, 'duration': 0.84}], 'summary': 'The cost of living in india is lower, so the higher us dollar salary may not be needed.', 'duration': 27.748, 'max_score': 1742.955, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/pixlHHe_lNQ/pics/pixlHHe_lNQ1742955.jpg'}, {'end': 1806.627, 'src': 'embed', 'start': 1779.888, 'weight': 1, 'content': [{'end': 1784.07, 'text': 'The first one, and these ones are really good for kind of looking at these kinds of surveys.', 'start': 1779.888, 'duration': 4.182}, {'end': 1786.811, 'text': "And I don't get to work with surveys enough, but we can see.", 'start': 1784.17, 'duration': 2.641}, {'end': 1790.032, 'text': 'you know how happy are they in terms of work-life balance?', 'start': 1786.811, 'duration': 3.221}, {'end': 1793.093, 'text': "So we can add that we're going to add work-life balance.", 'start': 1790.512, 'duration': 2.581}, {'end': 1799.916, 'text': "Um, and right now it's doing a count and if we don't have minimum or maximum values in there yet, so it's going to look kind of weird,", 'start': 1793.493, 'duration': 6.423}, {'end': 1803.517, 'text': "but we're gonna look at the average rate or the average score of these.", 'start': 1799.916, 'duration': 3.601}, {'end': 1806.627, 'text': "Then we're gonna pull this over to the minimum value.", 'start': 1804.906, 'duration': 1.721}], 'summary': 'Analyzing work-life balance survey data for average scores.', 'duration': 26.739, 'max_score': 1779.888, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/pixlHHe_lNQ/pics/pixlHHe_lNQ1779888.jpg'}, {'end': 1864.94, 'src': 'embed', 'start': 1813.211, 'weight': 2, 'content': [{'end': 1819.896, 'text': 'So now it actually has zero to 10, and it shows that the average person is happy with which one was this?', 'start': 1813.211, 'duration': 6.685}, {'end': 1823.058, 'text': 'The average person is happy with their work-life balance.', 'start': 1820.456, 'duration': 2.602}, {'end': 1826.02, 'text': 'They rate about a 5.74 overall.', 'start': 1823.838, 'duration': 2.182}, {'end': 1832.284, 'text': "Now, let's really quickly change the title of this, because this is ridiculous.", 'start': 1826.12, 'duration': 6.164}, {'end': 1836.486, 'text': 'I want to say happy with work-life balance.', 'start': 1833.064, 'duration': 3.422}, {'end': 1838.066, 'text': 'So this is their rating.', 'start': 1837.126, 'duration': 0.94}, {'end': 1840.608, 'text': 'You know, change it to whatever title you want.', 'start': 1838.567, 'duration': 2.041}, {'end': 1841.748, 'text': "That's what I'm going to do.", 'start': 1841.088, 'duration': 0.66}, {'end': 1844.81, 'text': "And we'll also do happy with their salary.", 'start': 1841.908, 'duration': 2.902}, {'end': 1846.59, 'text': 'Click on salary.', 'start': 1844.83, 'duration': 1.76}, {'end': 1848.911, 'text': "We'll add that to minimum.", 'start': 1847.291, 'duration': 1.62}, {'end': 1854.334, 'text': "And we'll add the maximum value as well to make sure that we know how to use that.", 'start': 1850.072, 'duration': 4.262}, {'end': 1857.275, 'text': "And then we'll take the average.", 'start': 1855.755, 'duration': 1.52}, {'end': 1860.417, 'text': "So not many people are happy with their salary, I'm just finding out.", 'start': 1857.556, 'duration': 2.861}, {'end': 1861.377, 'text': 'I mean, this is a real survey.', 'start': 1860.437, 'duration': 0.94}, {'end': 1862.138, 'text': 'This is real data.', 'start': 1861.417, 'duration': 0.721}, {'end': 1864.94, 'text': 'uh, pretty interesting.', 'start': 1863.639, 'duration': 1.301}], 'summary': 'On average, people rate work-life balance at 5.74, but not satisfied with salary.', 'duration': 51.729, 'max_score': 1813.211, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/pixlHHe_lNQ/pics/pixlHHe_lNQ1813211.jpg'}, {'end': 1961.387, 'src': 'embed', 'start': 1910.34, 'weight': 3, 'content': [{'end': 1912.34, 'text': 'So we have male, female.', 'start': 1910.34, 'duration': 2}, {'end': 1917.889, 'text': 'And what do we wanna look at? Like what do we wanna measure? So we have male versus female.', 'start': 1913.687, 'duration': 4.202}, {'end': 1923.631, 'text': "We can measure anything, but maybe what we'll do is the average salary again.", 'start': 1918.449, 'duration': 5.182}, {'end': 1930.514, 'text': "I mean, we've kind of only looked at salary once in this one right here, and a little bit of like how happy they are.", 'start': 1923.651, 'duration': 6.863}, {'end': 1934.716, 'text': "But we'll look at the average salary between males and females.", 'start': 1930.854, 'duration': 3.862}, {'end': 1938.958, 'text': "And then we'll look at not the current age.", 'start': 1935.556, 'duration': 3.402}, {'end': 1941.619, 'text': 'Oops, I meant average salary.', 'start': 1939.578, 'duration': 2.041}, {'end': 1944.72, 'text': "And then we'll look at the average.", 'start': 1942.499, 'duration': 2.221}, {'end': 1952.463, 'text': 'And it looks like the average salary is actually really close versus males versus females.', 'start': 1946.321, 'duration': 6.142}, {'end': 1955.024, 'text': '55 for female versus 53 for male.', 'start': 1952.483, 'duration': 2.541}, {'end': 1957.205, 'text': 'So actually the females are a little bit higher.', 'start': 1955.044, 'duration': 2.161}, {'end': 1961.387, 'text': "Congratulations So they're just a little bit higher in terms of pay.", 'start': 1957.605, 'duration': 3.782}], 'summary': 'Average salary: 55 for female, 53 for male, indicating females earn slightly more.', 'duration': 51.047, 'max_score': 1910.34, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/pixlHHe_lNQ/pics/pixlHHe_lNQ1910340.jpg'}], 'start': 1742.955, 'title': 'Cost of living and work-life balance analysis', 'summary': "Delves into the cost of living in india, highlighting the lower us dollar salary need, and provides insights from a survey indicating an average work-life balance score of 5.74. additionally, it explores gender pay comparison visualization, revealing females' slightly higher average salary of 55 compared to 53 for males.", 'chapters': [{'end': 1793.093, 'start': 1742.955, 'title': 'Cost of living in india', 'summary': 'Explores the concept of cost of living in india, indicating that individuals may not need a higher us dollar salary due to the lower cost of living, and proceeds to demonstrate the creation of visualizations for a project using gauges to analyze work-life balance.', 'duration': 50.138, 'highlights': ['Individuals in India may not need a higher US dollar salary due to the lower cost of living The concept of cost of living in India was discussed, indicating that individuals in India may not need a higher US dollar salary due to the lower cost of living.', 'Demonstration of creating visualizations using gauges to analyze work-life balance The chapter proceeds to demonstrate the creation of visualizations for a project using gauges to analyze work-life balance, specifically looking at the survey results related to work-life balance.']}, {'end': 1887.415, 'start': 1793.493, 'title': 'Survey analysis: work-life balance and salary', 'summary': 'Discusses the analysis of a survey on work-life balance and salary, revealing an average score of 5.74 for work-life balance and an observation that not many people are happy with their salary based on real data.', 'duration': 93.922, 'highlights': ['The average person rates their work-life balance at 5.74 overall.', 'Observation that not many people are happy with their salary based on real survey data.']}, {'end': 1961.387, 'start': 1887.975, 'title': 'Gender pay comparison visualization', 'summary': 'Discusses creating a visualization to compare average salaries of males and females, revealing that females have a slightly higher average salary of 55 compared to 53 for males.', 'duration': 73.412, 'highlights': ['The average salary comparison between males and females reveals that females have a slightly higher average salary of 55 compared to 53 for males, indicating a gender pay gap favoring females.', 'The speaker expresses initial reluctance towards using pie and donut charts but decides to visualize the male versus female comparison, emphasizing the significance of including this comparison in the visualization.', 'The chapter emphasizes the importance of including male versus female visualization, indicating a focus on gender pay comparison and equity in the analysis.']}], 'duration': 218.432, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/pixlHHe_lNQ/pics/pixlHHe_lNQ1742955.jpg', 'highlights': ['The concept of cost of living in India was discussed, indicating that individuals in India may not need a higher US dollar salary due to the lower cost of living.', 'The chapter proceeds to demonstrate the creation of visualizations for a project using gauges to analyze work-life balance, specifically looking at the survey results related to work-life balance.', 'The average person rates their work-life balance at 5.74 overall.', 'The average salary comparison between males and females reveals that females have a slightly higher average salary of 55 compared to 53 for males, indicating a gender pay gap favoring females.', 'The chapter emphasizes the importance of including male versus female visualization, indicating a focus on gender pay comparison and equity in the analysis.', 'Observation that not many people are happy with their salary based on real survey data.']}, {'end': 2544.257, 'segs': [{'end': 2035.293, 'src': 'embed', 'start': 1961.735, 'weight': 4, 'content': [{'end': 1967.897, 'text': 'So now we need to start organizing all of this, cleaning it up, making it look a lot better than it does right now.', 'start': 1961.735, 'duration': 6.162}, {'end': 1968.617, 'text': 'It looks great.', 'start': 1967.957, 'duration': 0.66}, {'end': 1972.198, 'text': 'Uh, you know, but we can do a lot more with this.', 'start': 1969.357, 'duration': 2.841}, {'end': 1976.56, 'text': "So I'm going to, we're going to keep these are all these kind of over on this left-hand side.", 'start': 1972.218, 'duration': 4.342}, {'end': 1979.561, 'text': "I'm going to put this, I want this up here.", 'start': 1977.1, 'duration': 2.461}, {'end': 1981.061, 'text': 'We also need to change that title.', 'start': 1979.581, 'duration': 1.48}, {'end': 1982.102, 'text': 'I want this up here.', 'start': 1981.121, 'duration': 0.981}, {'end': 1985.543, 'text': "Um, and again, we're going to kind of change the theme as we go.", 'start': 1983.082, 'duration': 2.461}, {'end': 1989.544, 'text': 'I just want to format it right.', 'start': 1985.563, 'duration': 3.981}, {'end': 1992.565, 'text': 'Have it just like this.', 'start': 1991.684, 'duration': 0.881}, {'end': 1994.667, 'text': "Let's change the title of this.", 'start': 1993.185, 'duration': 1.482}, {'end': 1997.95, 'text': "Let's go to title.", 'start': 1994.687, 'duration': 3.263}, {'end': 2001.893, 'text': "I'm going to say country of survey takers.", 'start': 1998.45, 'duration': 3.443}, {'end': 2006.737, 'text': "I'm not, the survey takers, I'm not really stuck on that.", 'start': 2003.435, 'duration': 3.302}, {'end': 2010.02, 'text': 'If you find something better, you think of something better, I would go with that.', 'start': 2006.798, 'duration': 3.222}, {'end': 2013.604, 'text': "But, you know, it definitely doesn't look bad.", 'start': 2010.681, 'duration': 2.923}, {'end': 2016.507, 'text': 'And where did this, where are my other visualizations? There it goes.', 'start': 2013.644, 'duration': 2.863}, {'end': 2019.568, 'text': 'I think this one I want to make kind of more tall.', 'start': 2016.927, 'duration': 2.641}, {'end': 2022.049, 'text': 'So I might move it this way.', 'start': 2020.689, 'duration': 1.36}, {'end': 2026.15, 'text': 'I hate having a lot of visualizations on here.', 'start': 2022.069, 'duration': 4.081}, {'end': 2028.211, 'text': 'It just really is annoying to me.', 'start': 2026.17, 'duration': 2.041}, {'end': 2035.293, 'text': "So what we're going to do, I think we're going to step this to the side, put this to the side as well.", 'start': 2028.231, 'duration': 7.062}], 'summary': 'Organizing and improving visualizations, changing titles, and adjusting layouts for better presentation.', 'duration': 73.558, 'max_score': 1961.735, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/pixlHHe_lNQ/pics/pixlHHe_lNQ1961735.jpg'}, {'end': 2099.889, 'src': 'embed', 'start': 2071.605, 'weight': 3, 'content': [{'end': 2075.228, 'text': "Um, I added a few different visualizations that I didn't have in my original.", 'start': 2071.605, 'duration': 3.623}, {'end': 2077.248, 'text': "So now I'm kind of having to do this on the fly.", 'start': 2075.648, 'duration': 1.6}, {'end': 2083.331, 'text': "So um, I might fast forward some of the parts where I'm like really thinking about it or taking too much time on it,", 'start': 2077.309, 'duration': 6.022}, {'end': 2085.233, 'text': "but I'm gonna bring this down a little bit actually.", 'start': 2083.331, 'duration': 1.902}, {'end': 2090.116, 'text': "Cause I don't like how close that is to, um, the, the text above it.", 'start': 2085.273, 'duration': 4.843}, {'end': 2093.118, 'text': 'But one thing we do need to do.', 'start': 2091.117, 'duration': 2.001}, {'end': 2099.889, 'text': "I'm going to put this up kind of like this.", 'start': 2097.568, 'duration': 2.321}], 'summary': 'Adding new visualizations, adjusting layout, and making real-time adjustments to improve presentation.', 'duration': 28.284, 'max_score': 2071.605, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/pixlHHe_lNQ/pics/pixlHHe_lNQ2071605.jpg'}, {'end': 2333.426, 'src': 'embed', 'start': 2300.679, 'weight': 2, 'content': [{'end': 2302.721, 'text': 'But this looks better to me.', 'start': 2300.679, 'duration': 2.042}, {'end': 2307.086, 'text': 'But we need to change up some stuff as well, like the title.', 'start': 2303.382, 'duration': 3.704}, {'end': 2312.693, 'text': 'Difficulty to break into data.', 'start': 2308.748, 'duration': 3.945}, {'end': 2315.754, 'text': 'There we go.', 'start': 2315.094, 'duration': 0.66}, {'end': 2321.078, 'text': "And we're also going to change this title right here.", 'start': 2315.774, 'duration': 5.304}, {'end': 2322.799, 'text': "We're just say difficulty.", 'start': 2321.178, 'duration': 1.621}, {'end': 2328.723, 'text': 'Difficulty This looks better to me.', 'start': 2325.461, 'duration': 3.262}, {'end': 2330.804, 'text': 'Um, again, not perfect.', 'start': 2329.143, 'duration': 1.661}, {'end': 2333.426, 'text': "And there's a thousand different things you could have done, but that's just what we're going to do.", 'start': 2330.864, 'duration': 2.562}], 'summary': 'Proposing changes to improve data accessibility and readability.', 'duration': 32.747, 'max_score': 2300.679, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/pixlHHe_lNQ/pics/pixlHHe_lNQ2300679.jpg'}, {'end': 2462.437, 'src': 'embed', 'start': 2434.662, 'weight': 1, 'content': [{'end': 2438.325, 'text': "we can come in here, customize this theme, however we'd like.", 'start': 2434.662, 'duration': 3.663}, {'end': 2443.87, 'text': "I personally don't want color five, which is the data analyst color.", 'start': 2439.546, 'duration': 4.324}, {'end': 2444.83, 'text': "I don't like it.", 'start': 2444.29, 'duration': 0.54}, {'end': 2447.989, 'text': "want to go out go and change it because I don't like it.", 'start': 2445.868, 'duration': 2.121}, {'end': 2450.39, 'text': "But I don't really like that color per se.", 'start': 2448.409, 'duration': 1.981}, {'end': 2453.032, 'text': 'You know, I might want to choose a different color.', 'start': 2450.45, 'duration': 2.582}, {'end': 2456.914, 'text': 'But it has to be like this muted like that it has a style to it.', 'start': 2453.932, 'duration': 2.982}, {'end': 2458.435, 'text': 'So you can come in here.', 'start': 2457.374, 'duration': 1.061}, {'end': 2462.437, 'text': "You can customize this and make it however you'd like.", 'start': 2459.555, 'duration': 2.882}], 'summary': 'Customize theme with muted colors, not color five, as per user preference.', 'duration': 27.775, 'max_score': 2434.662, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/pixlHHe_lNQ/pics/pixlHHe_lNQ2434662.jpg'}, {'end': 2513.459, 'src': 'embed', 'start': 2485.67, 'weight': 0, 'content': [{'end': 2488.252, 'text': "I'm going to go really in-depth in another project.", 'start': 2485.67, 'duration': 2.582}, {'end': 2489.773, 'text': "It's probably going to be like a two-hour project.", 'start': 2488.272, 'duration': 1.501}, {'end': 2490.614, 'text': "It's going to be crazy long.", 'start': 2489.793, 'duration': 0.821}, {'end': 2492.555, 'text': 'Well, for a YouTube video.', 'start': 2491.514, 'duration': 1.041}, {'end': 2501.481, 'text': 'But I can see doing a thousand different things with this data, creating a really great dashboard, really cleaning the data,', 'start': 2492.795, 'duration': 8.686}, {'end': 2504.023, 'text': 'which is a large part of actually doing this.', 'start': 2501.481, 'duration': 2.542}, {'end': 2505.744, 'text': "And we didn't do much data cleaning at all.", 'start': 2504.083, 'duration': 1.661}, {'end': 2507.968, 'text': "There's just so much you can do with this.", 'start': 2506.425, 'duration': 1.543}, {'end': 2513.459, 'text': "And so really dig into this, see what you like, see what you don't like, see what you want to clean, what you don't want to clean.", 'start': 2508.008, 'duration': 5.451}], 'summary': 'Planning a two-hour in-depth project for youtube, emphasizing data cleaning and dashboard creation.', 'duration': 27.789, 'max_score': 2485.67, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/pixlHHe_lNQ/pics/pixlHHe_lNQ2485670.jpg'}], 'start': 1961.735, 'title': 'Data organization and visualization project tips', 'summary': 'Covers organizing and enhancing data presentation, suggesting changes and discusses creating visualizations, adjusting size, layout, and color schemes, while addressing potential challenges and further data exploration.', 'chapters': [{'end': 2010.02, 'start': 1961.735, 'title': 'Data organization and presentation', 'summary': "Focuses on organizing and enhancing the presentation of data, emphasizing the need to improve the current format and suggesting changes such as repositioning elements and modifying the title to 'country of survey takers'.", 'duration': 48.285, 'highlights': ['The speaker emphasizes the need to organize and improve the current presentation of data, highlighting the potential for significant enhancement (quantifiable data: none).', "The speaker suggests repositioning elements and modifying the title to 'Country of Survey Takers', demonstrating a proactive approach to enhancing the data's presentation (quantifiable data: none)."]}, {'end': 2544.257, 'start': 2010.681, 'title': 'Visualization project tips', 'summary': 'Covers the process of creating visualizations, including adjustments made to the size, layout, and color schemes, as well as the addition of new visualizations. the presenter also discusses the challenges faced and the potential for further data exploration and dashboard creation.', 'duration': 533.576, 'highlights': ['The presenter makes adjustments to the size, layout, and position of visualizations, expressing a preference for taller visualizations and internal text placement.', 'The presenter discusses the addition of new visualizations to the project, highlighting the need to adapt and make adjustments on the fly.', 'The presenter addresses the challenges faced, such as changing titles, adjusting decimal formatting, and reordering data categories for improved visualization.', 'The presenter explores different color schemes and themes for the visualizations, encouraging customization and experimentation with the appearance of the project.', 'The presenter expresses the potential for further data exploration, dashboard creation, and data cleaning to maximize the usability and impact of the project.']}], 'duration': 582.522, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/pixlHHe_lNQ/pics/pixlHHe_lNQ1961735.jpg', 'highlights': ['The presenter expresses the potential for further data exploration, dashboard creation, and data cleaning to maximize the usability and impact of the project.', 'The presenter explores different color schemes and themes for the visualizations, encouraging customization and experimentation with the appearance of the project.', 'The presenter addresses the challenges faced, such as changing titles, adjusting decimal formatting, and reordering data categories for improved visualization.', 'The presenter discusses the addition of new visualizations to the project, highlighting the need to adapt and make adjustments on the fly.', 'The presenter makes adjustments to the size, layout, and position of visualizations, expressing a preference for taller visualizations and internal text placement.', "The speaker suggests repositioning elements and modifying the title to 'Country of Survey Takers', demonstrating a proactive approach to enhancing the data's presentation.", 'The speaker emphasizes the need to organize and improve the current presentation of data, highlighting the potential for significant enhancement.']}], 'highlights': ['Real data collected from a survey of data professionals about a month ago is being utilized for the project, adding authenticity and relevance.', "The dataset includes questions on job titles, yearly salary, industry, favorite programming language, satisfaction levels, and job preferences, providing diverse insights into the data professionals' backgrounds and preferences.", 'The final project of the Power BI tutorial series is the main focus, indicating the culmination of the series.', 'Challenges related to data cleaning are mentioned, with the speaker identifying over 20 different tasks that could be done to improve the data quality.', 'The process involves collecting demographic data such as gender, age range, and country of origin, with a focus on data cleaning and potential improvements (e.g., using sliding bars for age input and identifying gender and nationality).', 'The chapter focuses on streamlining the data for improved visualization and analysis, aiming to reduce complexity and standardize categories to facilitate effective data representation and interpretation.', 'The tutorial demonstrates the use of custom delimiters to separate and organize data, showcasing the practical application of this technique to simplify and structure the dataset for efficient analysis and visualization.', "The process involves duplicating columns, splitting them by digit to non-digit, and removing unwanted values such as 'K' and special characters, resulting in a cleaner dataset for analysis.", "The average salary is calculated by replacing values such as 'plus' with the intended numeric values and then performing the calculation, ensuring accurate representation of salary data.", 'Creating visualizations for survey data to provide high-level insights for easy interpretation', 'Guidance on adding a title, adjusting the size, making it bold, centering it, and changing the background for a dashboard', 'Starting the visualization building process with the transformed data', 'Emphasizing the potential for further enhancements beyond the minimum requirements for the project', 'The concept of cost of living in India was discussed, indicating that individuals in India may not need a higher US dollar salary due to the lower cost of living.', 'The chapter proceeds to demonstrate the creation of visualizations for a project using gauges to analyze work-life balance, specifically looking at the survey results related to work-life balance.', 'The average person rates their work-life balance at 5.74 overall.', 'The average salary comparison between males and females reveals that females have a slightly higher average salary of 55 compared to 53 for males, indicating a gender pay gap favoring females.', 'The presenter expresses the potential for further data exploration, dashboard creation, and data cleaning to maximize the usability and impact of the project.', 'The presenter explores different color schemes and themes for the visualizations, encouraging customization and experimentation with the appearance of the project.', 'The presenter addresses the challenges faced, such as changing titles, adjusting decimal formatting, and reordering data categories for improved visualization.', 'The presenter discusses the addition of new visualizations to the project, highlighting the need to adapt and make adjustments on the fly.', "The speaker suggests repositioning elements and modifying the title to 'Country of Survey Takers', demonstrating a proactive approach to enhancing the data's presentation.", 'The speaker emphasizes the need to organize and improve the current presentation of data, highlighting the potential for significant enhancement.']}