title
Cleaning Data in Excel | Excel Tutorials for Beginners

description
Take my Full Excel for Data Analytics Course! https://www.analystbuilder.com/courses/excel-for-data-analytics Excel is one of the most used skills in the data world. In this series we will be walking through all of the most important topics that Data Analysts need to know in order to be proficient in Excel. Excel Data Cleaning File: https://github.com/AlexTheAnalyst/Excel-Tutorial/blob/main/Data%20Cleaning%20Excel%20Tutorial.xlsx Unlocked by Z by HP: Click this link (https://www.clkmg.com/learnmedia/alexfreberg) to participate in the data challenges and have a chance to win the prizes! And don't forget to RSVP for the hackathon on Saturday, March 12th from 7am PST/8:30am IST until 1pm PST/2:30am IST: https://hopin.com/events/hp-hackathon (Spots limited) "No purchase necessary. Ends April 30, 2022. See official rules at www.hp.com/us-en/workstations/industries/data-science/unlocked-with-z/rules.html for how to enter, eligibility, odds, prize details, and restrictions. " ____________________________________________ 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: 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': 'Cleaning Data in Excel | Excel Tutorials for Beginners', 'heatmap': [{'end': 279.294, 'start': 251.376, 'weight': 1}], 'summary': 'This tutorial series on cleaning data in excel for beginners covers techniques for data cleaning, data visualization, and error-free data trimming, emphasizing the importance of thorough understanding of the dataset and best practices, with opportunities to participate in data science challenges and hackathons sponsored by unlocked by z by hp.', 'chapters': [{'end': 90.761, 'segs': [{'end': 30.65, 'src': 'embed', 'start': 0.169, 'weight': 0, 'content': [{'end': 2.976, 'text': "What's going on, everybody? Welcome back to the Excel tutorial series.", 'start': 0.169, 'duration': 2.807}, {'end': 5.381, 'text': 'Today, we will be looking at how to clean data in Excel.', 'start': 3.056, 'duration': 2.325}, {'end': 14.719, 'text': 'Now knowing how to clean data in Excel is actually extremely useful.', 'start': 11.857, 'duration': 2.862}, {'end': 16.7, 'text': 'And there are a ton of techniques to do this.', 'start': 14.759, 'duration': 1.941}, {'end': 19.542, 'text': "I'm going to be showing you the ones that I probably use the most.", 'start': 16.72, 'duration': 2.822}, {'end': 25.646, 'text': "I feel like are the most helpful to kind of do the bulk or the majority of the data clean that you're going to do in Excel.", 'start': 19.562, 'duration': 6.084}, {'end': 30.65, 'text': "Like I said, there's so many different ways and very specific things that you can do,", 'start': 25.787, 'duration': 4.863}], 'summary': 'Excel tutorial on cleaning data, with useful techniques and majority coverage.', 'duration': 30.481, 'max_score': 0.169, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/_jmiEGZ6PIY/pics/_jmiEGZ6PIY169.jpg'}], 'start': 0.169, 'title': 'Excel data cleaning techniques', 'summary': "Covers the importance of learning how to clean data in excel, highlighting the usefulness of these techniques and the opportunity to win prizes through unlocked by z by hp's data science challenges.", 'chapters': [{'end': 90.761, 'start': 0.169, 'title': 'Excel data cleaning techniques', 'summary': "Covers the importance of learning how to clean data in excel, highlighting the usefulness of these techniques and the opportunity to win prizes through unlocked by z by hp's data science challenges.", 'duration': 90.592, 'highlights': ['Learning how to clean data in Excel is extremely useful The speaker emphasizes the extreme usefulness of learning how to clean data in Excel.', 'Unlocked by Z by HP offers data science challenges with prizes including ZBook Studio laptops and a free trip to the Kaggle World Championships The sponsor, Unlocked by Z by HP, offers data science challenges with prizes such as ZBook Studio laptops and a free trip to the Kaggle World Championships.', 'There are a ton of techniques to clean data in Excel The speaker mentions that there are numerous techniques to clean data in Excel.']}], 'duration': 90.592, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/_jmiEGZ6PIY/pics/_jmiEGZ6PIY169.jpg', 'highlights': ['Unlocked by Z by HP offers data science challenges with prizes including ZBook Studio laptops and a free trip to the Kaggle World Championships', 'Learning how to clean data in Excel is extremely useful', 'There are a ton of techniques to clean data in Excel']}, {'end': 563.371, 'segs': [{'end': 225.994, 'src': 'embed', 'start': 185.541, 'weight': 0, 'content': [{'end': 190.844, 'text': "And then, you know, there are things like additional spaces where there shouldn't be spaces.", 'start': 185.541, 'duration': 5.303}, {'end': 193.605, 'text': 'There are things like currencies that you need to be aware of.', 'start': 191.264, 'duration': 2.341}, {'end': 198.348, 'text': 'If you were importing this into, or going to be importing this into a SQL database,', 'start': 194.005, 'duration': 4.343}, {'end': 205.319, 'text': 'things like currencies can be just a problem or be really unnecessary.', 'start': 198.348, 'duration': 6.971}, {'end': 207.18, 'text': 'it may actually cause more issues in the long run.', 'start': 205.319, 'duration': 1.861}, {'end': 208.801, 'text': 'so you may just want to, you know.', 'start': 207.18, 'duration': 1.621}, {'end': 213.925, 'text': 'take that to the base value, and then dates are always an issue.', 'start': 208.801, 'duration': 5.124}, {'end': 215.867, 'text': 'always, always, always, so always.', 'start': 213.925, 'duration': 1.942}, {'end': 216.587, 'text': 'look at your dates.', 'start': 215.867, 'duration': 0.72}, {'end': 218.329, 'text': "make sure they're they're formatted correctly.", 'start': 216.587, 'duration': 1.742}, {'end': 220.17, 'text': "make sure they're all the same.", 'start': 218.329, 'duration': 1.841}, {'end': 225.994, 'text': "these are the types of things that, right when i glance at this data set, these are things that i'm looking for.", 'start': 220.17, 'duration': 5.824}], 'summary': 'Data issues: extra spaces, currencies, and date formatting can cause problems when importing into sql database.', 'duration': 40.453, 'max_score': 185.541, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/_jmiEGZ6PIY/pics/_jmiEGZ6PIY185541.jpg'}, {'end': 282.498, 'src': 'heatmap', 'start': 248.775, 'weight': 3, 'content': [{'end': 249.575, 'text': "the first thing we're going to do.", 'start': 248.775, 'duration': 0.8}, {'end': 251.376, 'text': "we're going to go to this data tab.", 'start': 249.575, 'duration': 1.801}, {'end': 255.977, 'text': "we're going to go right over here and we're going to get see if there's any duplicates in our data.", 'start': 251.376, 'duration': 4.601}, {'end': 258.378, 'text': "so we're just going to go up to remove duplicates.", 'start': 255.977, 'duration': 2.401}, {'end': 262.519, 'text': "it's going to automatically choose all of your columns to to check against.", 'start': 258.378, 'duration': 4.141}, {'end': 265.42, 'text': "so it's going to for from a all the way through.", 'start': 262.519, 'duration': 2.901}, {'end': 270.542, 'text': "i it's going to see is the exact same data in all these rows and if it is, it's going to get rid of it.", 'start': 265.42, 'duration': 5.122}, {'end': 279.294, 'text': "and so we're going to click ok, and it did find one duplicate and I'll show you that one real quick, because you know it was right here.", 'start': 270.542, 'duration': 8.752}, {'end': 282.498, 'text': "So Barack Obama was here twice and then I'm gonna hit Control.", 'start': 279.775, 'duration': 2.723}], 'summary': 'Identified and removed 1 duplicate entry, including example of barack obama being duplicated.', 'duration': 33.723, 'max_score': 248.775, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/_jmiEGZ6PIY/pics/_jmiEGZ6PIY248775.jpg'}, {'end': 362.182, 'src': 'embed', 'start': 328.41, 'weight': 5, 'content': [{'end': 329.151, 'text': 'And this is what I actually do.', 'start': 328.41, 'duration': 0.741}, {'end': 332.073, 'text': "I usually create a separate column, especially when I'm working with this.", 'start': 329.231, 'duration': 2.842}, {'end': 341.488, 'text': "change this one, um, i don't want to go in here and you know, say equals upper, equals proper, etc.", 'start': 333.703, 'duration': 7.785}, {'end': 345.771, 'text': "there's a lot of different ways that you can change names or not a lot, but the main ones,", 'start': 341.488, 'duration': 4.283}, {'end': 349.434, 'text': 'that you can change names and all of them are completely okay.', 'start': 345.771, 'duration': 3.663}, {'end': 356.138, 'text': "so, for example, i'm going to hit equal upper, upper, and i'm going to go like this and close my parentheses.", 'start': 349.434, 'duration': 6.704}, {'end': 357.179, 'text': 'so i selected this cell.', 'start': 356.138, 'duration': 1.041}, {'end': 362.182, 'text': "i closed my parentheses, i hit enter, it is complete and i'm going to hit um in the bottom right.", 'start': 357.179, 'duration': 5.003}], 'summary': 'Demonstrates data manipulation using upper function, changing names, and completing the task.', 'duration': 33.772, 'max_score': 328.41, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/_jmiEGZ6PIY/pics/_jmiEGZ6PIY328410.jpg'}], 'start': 90.901, 'title': 'Data visualization and cleaning techniques', 'summary': 'Covers a data visualization tutorial with a us presidents dataset and mentions a hackathon sponsored by unlocked by z by hp. it also discusses data cleaning techniques in excel, including identifying and standardizing data issues, emphasizing the importance of thorough understanding of the dataset.', 'chapters': [{'end': 126.577, 'start': 90.901, 'title': 'Data visualization tutorial with us presidents dataset', 'summary': 'Discusses a data visualization tutorial using a us presidents dataset, incorporating added and manipulated data, and mentions a hackathon sponsored by unlocked by z by hp.', 'duration': 35.676, 'highlights': ['The chapter mentions a hackathon sponsored by Unlocked by Z by HP, where participants can collaborate on projects and submit them to win.', 'The tutorial involves a US presidents dataset with added and manipulated data, used for creating visualizations and demonstrations. ', 'The speaker obtained a base dataset from Kaggle and then added personal data for the tutorial.']}, {'end': 563.371, 'start': 126.577, 'title': 'Data cleaning techniques in excel', 'summary': 'Discusses data cleaning techniques in excel, including identifying and standardizing data issues such as formatting, duplicate data removal, and grouping inconsistencies, emphasizing the importance of data standardization and thorough understanding of the dataset to avoid potential issues.', 'duration': 436.794, 'highlights': ['Identifying and standardizing data issues The chapter emphasizes the importance of identifying and standardizing data issues such as formatting, duplicate data, and grouping inconsistencies.', 'Importance of data standardization It highlights the significance of standardizing data to ensure consistency, citing examples of uppercase/lowercase, spelling errors, additional spaces, and currencies.', 'Removing duplicate data The chapter demonstrates the process of easily removing duplicate data in Excel, stressing its importance in large datasets to avoid manual detection errors.', 'Grouping inconsistencies It emphasizes the need to carefully examine and correct grouping inconsistencies, such as spelling errors in data, to ensure accurate data analysis and visualization.']}], 'duration': 472.47, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/_jmiEGZ6PIY/pics/_jmiEGZ6PIY90901.jpg', 'highlights': ['The tutorial involves a US presidents dataset with added and manipulated data, used for creating visualizations and demonstrations.', 'The chapter mentions a hackathon sponsored by Unlocked by Z by HP, where participants can collaborate on projects and submit them to win.', 'The speaker obtained a base dataset from Kaggle and then added personal data for the tutorial.', 'The chapter emphasizes the importance of identifying and standardizing data issues such as formatting, duplicate data, and grouping inconsistencies.', 'It highlights the significance of standardizing data to ensure consistency, citing examples of uppercase/lowercase, spelling errors, additional spaces, and currencies.', 'The chapter demonstrates the process of easily removing duplicate data in Excel, stressing its importance in large datasets to avoid manual detection errors.', 'It emphasizes the need to carefully examine and correct grouping inconsistencies, such as spelling errors in data, to ensure accurate data analysis and visualization.']}, {'end': 768.151, 'segs': [{'end': 731.294, 'src': 'embed', 'start': 701.813, 'weight': 0, 'content': [{'end': 705.716, 'text': "If you have spaces at the end that you cannot see, Let's take this one, for example.", 'start': 701.813, 'duration': 3.903}, {'end': 712.441, 'text': 'Like if I had spaces at the end, that can cause issues when you insert or put that into a database.', 'start': 705.816, 'duration': 6.625}, {'end': 713.902, 'text': 'That happens a lot with numbers.', 'start': 712.461, 'duration': 1.441}, {'end': 718.045, 'text': "You know, when you're putting that into SQL, that can cause issues.", 'start': 714.983, 'duration': 3.062}, {'end': 720.847, 'text': 'And so you really, it is important to actually do that trim.', 'start': 718.085, 'duration': 2.762}, {'end': 725.89, 'text': "And you can do that on all of your columns or just ones that you know you're having issues with.", 'start': 721.387, 'duration': 4.503}, {'end': 731.294, 'text': "But once you import that data into SQL, you will know if there's an issue or not when you actually try to start using it.", 'start': 726.33, 'duration': 4.964}], 'summary': 'Trimming spaces at the end is important when inserting data into sql to avoid issues, especially with numbers.', 'duration': 29.481, 'max_score': 701.813, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/_jmiEGZ6PIY/pics/_jmiEGZ6PIY701813.jpg'}], 'start': 563.371, 'title': 'Data cleaning and trimming for error-free data', 'summary': 'Covers the process of fixing errors in data by updating it, keeping a copy of the raw data, and addressing issues such as blank rows and extra spaces in numerical data. it also emphasizes the importance of trimming data to remove extra spaces and highlights the need for data cleaning and preparation before importing into sql.', 'chapters': [{'end': 676.585, 'start': 563.371, 'title': 'Data cleaning and error fixing', 'summary': 'Discusses the process of fixing errors in the data by updating it, keeping a copy of the raw data, and addressing issues such as blank rows and extra spaces in numerical data.', 'duration': 113.214, 'highlights': ['The process of fixing errors in the data by updating it and keeping a copy of the raw data is emphasized, ensuring data integrity and accuracy.', 'Addressing issues such as blank rows and extra spaces in numerical data is highlighted, showcasing the meticulous approach to data cleaning.', 'The importance of maintaining a copy of the raw data for data integrity and not overwriting the original file is stressed, ensuring data preservation and traceability.', 'The mention of encountering blank rows and confirming their insignificance, indicating a thorough data review process.', "The specific example of fixing extra spaces in numerical data by using the 'trim' function is demonstrated, presenting a practical solution to a common data issue."]}, {'end': 768.151, 'start': 677.265, 'title': 'Importance of trimming data', 'summary': 'Highlights the importance of trimming data to remove extra spaces, which can cause issues when inserting into a database, particularly with numerical data and currency symbols, emphasizing the need for data cleaning and preparation before importing into sql.', 'duration': 90.886, 'highlights': ['Trimming data is important to remove extra spaces, which can cause issues when inserting into a database, particularly with numerical data and currency symbols.', 'Working with numerical data can lead to encountering various issues, such as dealing with currency symbols like dollar signs and pound signs when importing into SQL.', 'The trim function is intuitive and automatically removes spaces at the beginning, middle, and end of the data, preventing potential issues in SQL.', "It's crucial to trim all columns or specific ones known to have issues before importing data into SQL to avoid encountering issues during usage."]}], 'duration': 204.78, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/_jmiEGZ6PIY/pics/_jmiEGZ6PIY563371.jpg', 'highlights': ['The process of fixing errors in the data by updating it and keeping a copy of the raw data is emphasized, ensuring data integrity and accuracy.', 'Trimming data is important to remove extra spaces, which can cause issues when inserting into a database, particularly with numerical data and currency symbols.', 'Addressing issues such as blank rows and extra spaces in numerical data is highlighted, showcasing the meticulous approach to data cleaning.', 'The importance of maintaining a copy of the raw data for data integrity and not overwriting the original file is stressed, ensuring data preservation and traceability.', 'The trim function is intuitive and automatically removes spaces at the beginning, middle, and end of the data, preventing potential issues in SQL.']}, {'end': 1064.64, 'segs': [{'end': 882.163, 'src': 'embed', 'start': 854.879, 'weight': 3, 'content': [{'end': 860.521, 'text': 'in this example, they are not the same and we just want them to all be similar.', 'start': 854.879, 'duration': 5.642}, {'end': 861.761, 'text': 'they say date on.', 'start': 860.521, 'duration': 1.24}, {'end': 863.982, 'text': 'if you look right here, it says date.', 'start': 861.761, 'duration': 2.221}, {'end': 864.662, 'text': 'it says date.', 'start': 863.982, 'duration': 0.68}, {'end': 872.393, 'text': 'it looks like it should be the same, but if we go like this, it all looks the same, right?', 'start': 864.662, 'duration': 7.731}, {'end': 873.714, 'text': "There's no issues at all.", 'start': 872.433, 'duration': 1.281}, {'end': 877.979, 'text': 'If we were to try to use that.', 'start': 874.675, 'duration': 3.304}, {'end': 882.163, 'text': "it may or may not be an issue, but we don't want to leave that to chance later on.", 'start': 877.979, 'duration': 4.184}], 'summary': "Ensuring uniformity of 'date' entries to avoid potential issues.", 'duration': 27.284, 'max_score': 854.879, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/_jmiEGZ6PIY/pics/_jmiEGZ6PIY854879.jpg'}, {'end': 933.942, 'src': 'embed', 'start': 905.625, 'weight': 0, 'content': [{'end': 907.326, 'text': 'I usually do that on date fields as well.', 'start': 905.625, 'duration': 1.701}, {'end': 914.291, 'text': 'And oftentimes, just for demonstration purposes, oftentimes I will get something like that.', 'start': 907.747, 'duration': 6.544}, {'end': 921.611, 'text': "And then I'll come up here and I'll notice that there's this one random number that happens all the time.", 'start': 915.352, 'duration': 6.259}, {'end': 923.154, 'text': 'all the time.', 'start': 922.674, 'duration': 0.48}, {'end': 933.942, 'text': 'And so you want to make sure that you look at these things and just do at least a quick glance, if not kind of doing a kind of a deep dive into it.', 'start': 923.915, 'duration': 10.027}], 'summary': 'Emphasize scrutinizing date fields for consistency and anomalies to ensure data accuracy.', 'duration': 28.317, 'max_score': 905.625, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/_jmiEGZ6PIY/pics/_jmiEGZ6PIY905625.jpg'}, {'end': 994.128, 'src': 'embed', 'start': 947.733, 'weight': 2, 'content': [{'end': 951.114, 'text': "We're gonna go back through here We're gonna get rid of these.", 'start': 947.733, 'duration': 3.381}, {'end': 957.217, 'text': 'Again, this is a working, this is a working document.', 'start': 951.554, 'duration': 5.663}, {'end': 963.241, 'text': "Oops We need to, I'm gonna do control shift down.", 'start': 957.237, 'duration': 6.004}, {'end': 965.503, 'text': 'Oops Let me go back up.', 'start': 964.022, 'duration': 1.481}, {'end': 968.244, 'text': 'Do control shift down and copy.', 'start': 966.143, 'duration': 2.101}, {'end': 972.567, 'text': "And what I'm gonna do right now is I'm actually going to copy.", 'start': 969.125, 'duration': 3.442}, {'end': 973.608, 'text': 'All right, let me do it right here.', 'start': 972.707, 'duration': 0.901}, {'end': 973.968, 'text': "I'll show you.", 'start': 973.628, 'duration': 0.34}, {'end': 974.929, 'text': 'Sometimes I do this.', 'start': 974.228, 'duration': 0.701}, {'end': 975.709, 'text': 'It just depends.', 'start': 975.189, 'duration': 0.52}, {'end': 976.59, 'text': "I'm gonna go right here.", 'start': 975.909, 'duration': 0.681}, {'end': 978.231, 'text': "I'm gonna hit right click.", 'start': 976.95, 'duration': 1.281}, {'end': 986.103, 'text': "and I'm gonna paste as a value, which means it's not gonna take the calculation or the formula that I just did.", 'start': 979.099, 'duration': 7.004}, {'end': 989.145, 'text': "It's gonna actually paste it as that value.", 'start': 987.224, 'duration': 1.921}, {'end': 990.245, 'text': 'So we just replaced it.', 'start': 989.185, 'duration': 1.06}, {'end': 994.128, 'text': 'Right here you can see up here it says equals trim of G2.', 'start': 991.166, 'duration': 2.962}], 'summary': 'Demonstrating copying and pasting data as values for formulas in a working document.', 'duration': 46.395, 'max_score': 947.733, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/_jmiEGZ6PIY/pics/_jmiEGZ6PIY947733.jpg'}, {'end': 1064.64, 'src': 'embed', 'start': 1025.105, 'weight': 1, 'content': [{'end': 1030.348, 'text': "And again, it has this proper and now it doesn't have the proper, it's actually the value that was here.", 'start': 1025.105, 'duration': 5.243}, {'end': 1032.148, 'text': "So that's really important to note.", 'start': 1030.949, 'duration': 1.199}, {'end': 1034.431, 'text': "And we're gonna get rid of that one.", 'start': 1032.169, 'duration': 2.262}, {'end': 1038.81, 'text': 'And so now what we have is already looking much better.', 'start': 1035.509, 'duration': 3.301}, {'end': 1042.751, 'text': "Now one of the last things that we're gonna look at is deleting columns that we are not gonna use.", 'start': 1039.51, 'duration': 3.241}, {'end': 1048.653, 'text': "And this is why it's so important to keep a backup or the raw data not in this file.", 'start': 1043.412, 'duration': 5.241}, {'end': 1053.415, 'text': 'Because if you start saving over this file and this is your raw file, that can mess up a lot of things.', 'start': 1049.014, 'duration': 4.401}, {'end': 1056.536, 'text': "And that's happened to me before and it's terrible.", 'start': 1053.995, 'duration': 2.541}, {'end': 1061.678, 'text': "And then you have to request another file or you have to go back and bind it or something like that and it's terrible.", 'start': 1056.916, 'duration': 4.762}, {'end': 1064.64, 'text': 'So this is our working document.', 'start': 1062.738, 'duration': 1.902}], 'summary': 'Data cleaning and backup are crucial for file integrity and accuracy.', 'duration': 39.535, 'max_score': 1025.105, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/_jmiEGZ6PIY/pics/_jmiEGZ6PIY1025105.jpg'}], 'start': 768.691, 'title': 'Data preparation', 'summary': 'Covers the importance of formatting and cleaning data for analysis, including converting currency to numbers, ensuring uniform date formats, and maintaining a backup, resulting in a more consistent and organized dataset.', 'chapters': [{'end': 923.154, 'start': 768.691, 'title': 'Data formatting for analysis', 'summary': 'Discusses formatting data by converting currency to numbers and ensuring uniformity in date formats, highlighting the common issues faced and the importance of data consistency for analysis.', 'duration': 154.463, 'highlights': ['The importance of converting currency to numbers for easier calculations and usability in different systems, such as Excel and Python, is emphasized.', 'The significance of ensuring uniformity in date formats to avoid potential issues, with a focus on the impact on different systems like Python and SQL.', 'The common occurrence of date format issues in data, with the rarity of receiving perfectly formatted date fields highlighted as a challenge for data analysis.']}, {'end': 1064.64, 'start': 923.915, 'title': 'Data cleaning and formatting', 'summary': 'Entails the process of cleaning and formatting data, including the importance of maintaining a backup, deleting unnecessary columns, and converting formulas to values, ultimately resulting in a more uniform and organized dataset.', 'duration': 140.725, 'highlights': ['The importance of maintaining a backup or raw data outside of the working file is emphasized. Emphasizes the importance of keeping a backup or raw data outside of the working file to avoid potential data loss or corruption.', 'The process of converting formulas to values is demonstrated to ensure the data is represented as intended. Demonstrates the process of converting formulas to values to ensure the data is accurately represented and prevent potential errors.', 'The significance of deleting unnecessary columns in the dataset is highlighted to improve data organization. Emphasizes the importance of deleting unnecessary columns in the dataset to enhance data organization and streamline the dataset.']}], 'duration': 295.949, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/_jmiEGZ6PIY/pics/_jmiEGZ6PIY768691.jpg', 'highlights': ['Emphasizes the importance of converting currency to numbers for easier calculations and usability in different systems, such as Excel and Python.', 'The importance of maintaining a backup or raw data outside of the working file is emphasized.', 'The significance of ensuring uniformity in date formats to avoid potential issues, with a focus on the impact on different systems like Python and SQL.', 'Demonstrates the process of converting formulas to values to ensure the data is accurately represented and prevent potential errors.', 'Emphasizes the importance of deleting unnecessary columns in the dataset to enhance data organization and streamline the dataset.', 'The common occurrence of date format issues in data, with the rarity of receiving perfectly formatted date fields highlighted as a challenge for data analysis.']}, {'end': 1250.926, 'segs': [{'end': 1120.197, 'src': 'embed', 'start': 1089.178, 'weight': 0, 'content': [{'end': 1089.619, 'text': 'eight or nine.', 'start': 1089.178, 'duration': 0.441}, {'end': 1091.681, 'text': "Now, that's a small dataset.", 'start': 1089.759, 'duration': 1.922}, {'end': 1093.904, 'text': "I've had ones with literally like hundreds.", 'start': 1091.802, 'duration': 2.102}, {'end': 1098.51, 'text': 'And it has so many columns, so much data.', 'start': 1094.886, 'duration': 3.624}, {'end': 1102.335, 'text': "And sometimes it's good to just trim it back to the things you know you're gonna use.", 'start': 1099.151, 'duration': 3.184}, {'end': 1104.238, 'text': 'This to me is absolutely useless.', 'start': 1102.776, 'duration': 1.462}, {'end': 1105.9, 'text': "We're going to delete that.", 'start': 1104.759, 'duration': 1.141}, {'end': 1108.688, 'text': "And then right over here, it's pretty redundant.", 'start': 1106.806, 'duration': 1.882}, {'end': 1110.769, 'text': "It's just one number off.", 'start': 1109.368, 'duration': 1.401}, {'end': 1115.953, 'text': 'But if we scroll down just a little bit, it basically just counts.', 'start': 1111.49, 'duration': 4.463}, {'end': 1120.197, 'text': 'You could even call it a unique identifier if you want.', 'start': 1116.974, 'duration': 3.223}], 'summary': 'Data set has few rows, many columns. trimming unnecessary data. identifying unique identifier.', 'duration': 31.019, 'max_score': 1089.178, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/_jmiEGZ6PIY/pics/_jmiEGZ6PIY1089178.jpg'}, {'end': 1198.41, 'src': 'embed', 'start': 1130.423, 'weight': 1, 'content': [{'end': 1134.805, 'text': 'These date updated and date created, we may never use them, but we might.', 'start': 1130.423, 'duration': 4.382}, {'end': 1137.727, 'text': "So it doesn't hurt to keep it on hand.", 'start': 1135.686, 'duration': 2.041}, {'end': 1140.688, 'text': 'Those other ones are ones that we are almost certain we will never use.', 'start': 1137.767, 'duration': 2.921}, {'end': 1143.65, 'text': 'Again, keep a backup just in case you need it.', 'start': 1141.289, 'duration': 2.361}, {'end': 1144.73, 'text': 'You can always go back and get it.', 'start': 1143.81, 'duration': 0.92}, {'end': 1152.363, 'text': "You know, if you go back to what we started with and you look at what we have now, it is much cleaner, it's much more usable.", 'start': 1146.459, 'duration': 5.904}, {'end': 1159.647, 'text': 'And these are small, subtle changes, especially with this very small data set of only like 50 rows or 46 rows.', 'start': 1153.163, 'duration': 6.484}, {'end': 1165.411, 'text': "But you're gonna be working with data sets that are thousands, tens of thousands, hundreds of thousands of rows,", 'start': 1160.528, 'duration': 4.883}, {'end': 1172.495, 'text': "and you need to know how to kinda look at this data, standardize it, format it properly for what you're going to be using it for.", 'start': 1165.411, 'duration': 7.084}, {'end': 1173.616, 'text': "If you're keeping it in Excel,", 'start': 1172.515, 'duration': 1.101}, {'end': 1179.939, 'text': "there are different things that you may do than if you're putting it into a database or going to be using Python to access it.", 'start': 1174.196, 'duration': 5.743}, {'end': 1186.517, 'text': 'So you need to kind of know your use case,', 'start': 1184.315, 'duration': 2.202}, {'end': 1193.365, 'text': 'but these are some things that I do all the time to kind of clean up the data before I use it for something,', 'start': 1186.517, 'duration': 6.848}, {'end': 1198.41, 'text': "whether I'm creating pivot tables or I'm inserting it into or I'm putting it into SQL.", 'start': 1193.365, 'duration': 5.045}], 'summary': 'Importance of keeping backup data for potential use, making small changes for better usability, and preparing data for varied use cases.', 'duration': 67.987, 'max_score': 1130.423, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/_jmiEGZ6PIY/pics/_jmiEGZ6PIY1130423.jpg'}], 'start': 1064.96, 'title': 'Data cleaning best practices', 'summary': 'Discusses the process of trimming and cleaning the dataset, reducing it from a small dataset of 8 columns to a more useful and relevant set, emphasizing the importance of understanding data cleaning techniques, particularly when working with large datasets, and highlighting the need to tailor the approach based on specific use cases, with the example of cleaning a small dataset of 50 rows.', 'chapters': [{'end': 1152.363, 'start': 1064.96, 'title': 'Data trimming and cleaning', 'summary': 'Discusses the process of trimming and cleaning the dataset, reducing it from a small dataset of 8 columns to a more useful and relevant set, highlighting the importance of keeping potentially useful data while discarding unnecessary information.', 'duration': 87.403, 'highlights': ['The chapter emphasizes the need to trim and clean the dataset, reducing it from a small dataset of 8 columns to a more useful and relevant set, highlighting the importance of keeping potentially useful data while discarding unnecessary information.', 'It mentions handling larger datasets with hundreds of columns and the importance of trimming back to the essential data to make it more usable.', "The discussion stresses the significance of keeping potentially useful data like 'date updated' and 'date created' on hand while discarding irrelevant data that is almost certain to never be used."]}, {'end': 1250.926, 'start': 1153.163, 'title': 'Data cleaning best practices', 'summary': 'Emphasizes the importance of understanding data cleaning techniques, particularly when working with large datasets, and highlights the need to tailor the approach based on specific use cases, with the example of cleaning a small dataset of 50 rows.', 'duration': 97.763, 'highlights': ['The chapter stresses the significance of understanding data cleaning techniques, especially when dealing with large datasets, and highlights the necessity of customizing the approach based on specific use cases, with the example of cleaning a small dataset of 50 rows.', 'The speaker discusses the importance of knowing the specific use case for data, such as working with Excel, a database, or Python, and emphasizes the need to standardize and format data appropriately, particularly for larger datasets.', 'The speaker advises caution in applying the mentioned data cleaning techniques to different datasets, as the specific needs and purposes may vary, highlighting the importance of understanding the reasons behind making these changes.', 'The chapter concludes with a reminder to apply the presented techniques with a degree of adaptability to individual datasets, and expresses gratitude to the audience, encouraging them to like and subscribe for future content.']}], 'duration': 185.966, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/_jmiEGZ6PIY/pics/_jmiEGZ6PIY1064960.jpg', 'highlights': ['The chapter emphasizes the need to trim and clean the dataset, reducing it from a small dataset of 8 columns to a more useful and relevant set, highlighting the importance of keeping potentially useful data while discarding unnecessary information.', 'The chapter stresses the significance of understanding data cleaning techniques, especially when dealing with large datasets, and highlights the necessity of customizing the approach based on specific use cases, with the example of cleaning a small dataset of 50 rows.', "The discussion stresses the significance of keeping potentially useful data like 'date updated' and 'date created' on hand while discarding irrelevant data that is almost certain to never be used.", 'The speaker discusses the importance of knowing the specific use case for data, such as working with Excel, a database, or Python, and emphasizes the need to standardize and format data appropriately, particularly for larger datasets.', 'The chapter stresses the significance of understanding data cleaning techniques, especially when dealing with large datasets, and highlights the necessity of customizing the approach based on specific use cases, with the example of cleaning a small dataset of 50 rows.']}], 'highlights': ['Unlocked by Z by HP offers data science challenges with prizes including ZBook Studio laptops and a free trip to the Kaggle World Championships', 'Learning how to clean data in Excel is extremely useful', 'There are a ton of techniques to clean data in Excel', 'The tutorial involves a US presidents dataset with added and manipulated data, used for creating visualizations and demonstrations.', 'The chapter mentions a hackathon sponsored by Unlocked by Z by HP, where participants can collaborate on projects and submit them to win.', 'The speaker obtained a base dataset from Kaggle and then added personal data for the tutorial.', 'The chapter emphasizes the importance of identifying and standardizing data issues such as formatting, duplicate data, and grouping inconsistencies.', 'It highlights the significance of standardizing data to ensure consistency, citing examples of uppercase/lowercase, spelling errors, additional spaces, and currencies.', 'The chapter demonstrates the process of easily removing duplicate data in Excel, stressing its importance in large datasets to avoid manual detection errors.', 'It emphasizes the need to carefully examine and correct grouping inconsistencies, such as spelling errors in data, to ensure accurate data analysis and visualization.', 'The process of fixing errors in the data by updating it and keeping a copy of the raw data is emphasized, ensuring data integrity and accuracy.', 'Trimming data is important to remove extra spaces, which can cause issues when inserting into a database, particularly with numerical data and currency symbols.', 'Addressing issues such as blank rows and extra spaces in numerical data is highlighted, showcasing the meticulous approach to data cleaning.', 'The importance of maintaining a copy of the raw data for data integrity and not overwriting the original file is stressed, ensuring data preservation and traceability.', 'The trim function is intuitive and automatically removes spaces at the beginning, middle, and end of the data, preventing potential issues in SQL.', 'Emphasizes the importance of converting currency to numbers for easier calculations and usability in different systems, such as Excel and Python.', 'The significance of ensuring uniformity in date formats to avoid potential issues, with a focus on the impact on different systems like Python and SQL.', 'Demonstrates the process of converting formulas to values to ensure the data is accurately represented and prevent potential errors.', 'Emphasizes the importance of deleting unnecessary columns in the dataset to enhance data organization and streamline the dataset.', 'The common occurrence of date format issues in data, with the rarity of receiving perfectly formatted date fields highlighted as a challenge for data analysis.', 'The chapter emphasizes the need to trim and clean the dataset, reducing it from a small dataset of 8 columns to a more useful and relevant set, highlighting the importance of keeping potentially useful data while discarding unnecessary information.', 'The chapter stresses the significance of understanding data cleaning techniques, especially when dealing with large datasets, and highlights the necessity of customizing the approach based on specific use cases, with the example of cleaning a small dataset of 50 rows.', "The discussion stresses the significance of keeping potentially useful data like 'date updated' and 'date created' on hand while discarding irrelevant data that is almost certain to never be used.", 'The speaker discusses the importance of knowing the specific use case for data, such as working with Excel, a database, or Python, and emphasizes the need to standardize and format data appropriately, particularly for larger datasets.']}