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Analyzing And Visualizing Data With Excel 2016
 
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In this workshop, get an introduction to the latest analysis and visualization capabilities in Excel 2016. See how to import data from different sources, create mash/ups between data sources, and prepare the data for analysis. After preparing the data, learn about how business calculations - from simple to more advanced - can be expressed using DAX, how the result can be visualized and shared.
Views: 34163 Microsoft Power BI
Business Analytics with Excel | Data Science Tutorial | Simplilearn
 
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Business Analytics with excel training has been designed to help initiate you to the world of analytics. For this we use the most commonly used analytics tool i.e. Microsoft Excel. The training will equip you with all the concepts and hard skills required to kick start your analytics career. If you already have some experience in the IT or any core industry, this course will quickly teach you how to understand data and take data driven decisions relative to your domain using Microsoft excel. Data Science Certification Training - R Programming: https://www.simplilearn.com/big-data-and-analytics/data-scientist-certification-sas-r-excel-training?utm_campaign=Data-Excel-W3vrMSah3rc&utm_medium=SC&utm_source=youtube For a new-comer to the analytics field, this course provides the best required foundation. The training also delves into statistical concepts which are important to derive the best insights from available data and to present the same using executive level dashboards. Finally we introduce Power BI, which is the latest and the best tool provided by Microsoft for analytics and data visualization. What are the course objectives? This course will enable you to: 1. Gain a foundational understanding of business analytics 2. Install R, R-studio, and workspace setup. You will also learn about the various R packages 3. Master the R programming and understand how various statements are executed in R 4. Gain an in-depth understanding of data structure used in R and learn to import/export data in R 5. Define, understand and use the various apply functions and DPLYP functions 6. Understand and use the various graphics in R for data visualization 7. Gain a basic understanding of the various statistical concepts 8. Understand and use hypothesis testing method to drive business decisions 9. Understand and use linear, non-linear regression models, and classification techniques for data analysis 10. Learn and use the various association rules and Apriori algorithm 11. Learn and use clustering methods including K-means, DBSCAN, and hierarchical clustering Who should take this course? There is an increasing demand for skilled data scientists across all industries which makes this course suited for participants at all levels of experience. We recommend this Data Science training especially for the following professionals: IT professionals looking for a career switch into data science and analytics Software developers looking for a career switch into data science and analytics Professionals working in data and business analytics Graduates looking to build a career in analytics and data science Anyone with a genuine interest in the data science field Experienced professionals who would like to harness data science in their fields Who should take this course? There is an increasing demand for skilled data scientists across all industries which makes this course suited for participants at all levels of experience. We recommend this Data Science training especially for the following professionals: 1. IT professionals looking for a career switch into data science and analytics 2. Software developers looking for a career switch into data science and analytics 3. Professionals working in data and business analytics 4. Graduates looking to build a career in analytics and data science 5. Anyone with a genuine interest in the data science field 6. Experienced professionals who would like to harness data science in their fields For more updates on courses and tips follow us on: - Facebook : https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn Get the android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 39215 Simplilearn
Excel Data Analysis: Sort, Filter, PivotTable, Formulas (25 Examples): HCC Professional Day 2012
 
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Download workbook: http://people.highline.edu/mgirvin/ExcelIsFun.htm Learn the basics of Data Analysis at Highline Community College Professional Development Day 2012: Topics in Video: 1. What is Data Analysis? ( 00:53 min mark) 2. How Data Must Be Setup ( 02:53 min mark) Sort: 3. Sort with 1 criteria ( 04:35 min mark) 4. Sort with 2 criteria or more ( 06:27 min mark) 5. Sort by color ( 10:01 min mark) Filter: 6. Filter with 1 criteria ( 11:26 min mark) 7. Filter with 2 criteria or more ( 15:14 min mark) 8. Filter by color ( 16:28 min mark) 9. Filter Text, Numbers, Dates ( 16:50 min mark) 10. Filter by Partial Text ( 20:16 min mark) Pivot Tables: 11. What is a PivotTable? ( 21:05 min mark) 12. Easy 3 step method, Cross Tabulation ( 23:07 min mark) 13. Change the calculation ( 26:52 min mark) 14. More than one calculation ( 28:45 min mark) 15. Value Field Settings (32:36 min mark) 16. Grouping Numbers ( 33:24 min mark) 17. Filter in a Pivot Table ( 35:45 min mark) 18. Slicers ( 37:09 min mark) Charts: 19. Column Charts from Pivot Tables ( 38:37 min mark) Formulas: 20. SUMIFS ( 42:17 min mark) 21. Data Analysis Formula or PivotTables? ( 45:11 min mark) 22. COUNTIF ( 46:12 min mark) 23. Formula to Compare Two Lists: ISNA and MATCH functions ( 47:00 min mark) Getting Data Into Excel 24. Import from CSV file ( 51:21 min mark) 25. Import from Access ( 54:00 min mark) Highline Community College Professional Development Day 2012 Buy excelisfun products: https://teespring.com/stores/excelisfun-store
Views: 1584216 ExcelIsFun
Module 1: Data Analysis in Excel
 
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This video is part of the Analyzing and Visualizing Data with Excel course available on EdX. To sign up for the course, visit: http://aka.ms/edxexcelbi
Views: 430213 DAT206x
Tips And Tricks For Advanced Visualizations In Excel
 
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We're constantly amazed at what customers do with charts in Excel. Come to learn more about tips and tricks for commonly requested visualizations scenarios in Excel.
Views: 296578 Microsoft Power BI
Data Analysis with MATLAB for Excel Users
 
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This webinar highlights how MATLAB can work with Excel. Get a Free MATLAB Trial: https://goo.gl/C2Y9A5 Ready to Buy: https://goo.gl/vsIeA5 Learn MATLAB for Free: https://goo.gl/xIiHyG Many technical professionals find that they run into limitations using Excel for their data analysis applications. This webinar highlights how MATLAB can supplement the capabilities of Excel by providing access to thousands of pre-built engineering and advanced analysis functions and versatile visualization tools. Learn more about using MATLAB with Excel: http://goo.gl/3vkFMW Learn more about MATLAB: http://goo.gl/YKadxi Through product demonstrations you will see how to: • Access data from spreadsheets • Plot data and customize figures • Perform statistical analysis and fitting • Automatically generate reports to document your analysis • Freely distribute your MATLAB functions as Excel add-ins This webinar will show new features from the latest versions of MATLAB including new data types to store and manage data commonly found in spreadsheets. Previous knowledge of MATLAB is not required. About the Presenter: Adam Filion holds a BS and MS in Aerospace Engineering from Virginia Tech. His research involved nonlinear controls of spacecraft and periodic orbits in the three-body problem. After graduating he joined the MathWorks Engineering Development Group in 2010 and moved to Applications Engineering in 2012.
Views: 242428 MATLAB
Comprehensive Power BI Desktop Example: Visualize Excel Data & Build Dynamic Dashboard (EMT 1360)
 
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Download File: http://people.highline.edu/mgirvin/excelisfun.htm See how to use Power BI Desktop to import, clean and transform Sales Tables from Multiple Excel Files and consolidate into a Single Proper Data Set that can be linked in a Relationship to other tables, and then build DAX Calculated Columns & Measures for Gross Profit that can be used in a Dynamic Dashboard with Map, Column Chart, Line Chart, Card and Slicer visualizations. During the whole process we will compare and contrast how the process is similar and different from Excel’s Power Query and Power Pivot DAX. The steps we will see in this video are: 1. (00:17) Introduction to entire process for Power BI Desktop, including looking at the finished Dashboard 2. (04:50) Import Multiple Excel Files From Folder 3. (05:44) Name Query 4. (06:02) Transform extension column to lowercase 5. (06:34) Filter Files to only include “.xlsx” file extensions 6. (07:05) Remove Columns 7. (07:18) November 2016 Power Query Update Problem 8. (08:05) Add Custom Column with Excel.Workbook Function to extract the Excel Objects from each File. 9. (09:40) Delete Content Column 10. (10:41) Filter to only include Excel Sheet Objects 11. (11:06) Filter to exclude sheets that contain the word “Sheet” 12. (11:40) Remove Columns 13. (11:51) Expand Data and Sheet Name Columns 14. (12:06) Change Field Names 15. (12:22) Change Data Types 16. (14:05) Add Custom Column to calculate Net Revenue Column then round Number.Round function. Then Add Fixed Decimal Data Type. 17. (15:59) Remove columns for Amount and Revenue Discount 18. (16:10) Close and Apply to add to Data Model 19. (17:05) Import Excel Manager Table. Change Data Types to Text. Close and Apply 20. (18:10) Create Relationship between Zip Code Columns 21. (19:03) Create DAX Calculated Column with the IF Function to Categorize Retail Data. Change Data Type. 22. (21:53) Create DAX Measures for: Total Revenue, Total COGS and Gross Profit. Add Currency Number Formatting with No Decimals Showing. 23. (24:28) Create DAX Measures for: Gross Profit Percentage. Add Percentage Number Formatting with Two Decimals Showing. 24. (25:35) Create Map Visualization for Zip Code & Gross Profit Data (Zip Code with relationship to Managers) 25. (26:20) Create Clustered Bar for Manager Names & Gross Profit Data (Zip Code with relationship to Managers) 26. (27:15) Create Clustered Column for Product & Gross Profit Data, with a Line Chart for Gross Profit Percentage 27. (28:19) Create Clustered Column for Payment Method & Gross Profit Data, with a Line Chart for Gross Profit Percentage 28. (28:45) Create Slicer for States. 29. (29:00) Create Card Visualization for Total Revenue, Total COGS, Gross Profit and Gross Profit Percentage. 30. (29:57) Summary Learn Power BI Desktop Basics. Introduction to Power BI Desktop. Getting Started with Power BI Desktop. Create Impactful Reports With Power BI Desktop. Microsoft Power BI.
Views: 137351 ExcelIsFun
Power BI Basic Tutorial: Learn Data Analysis and Visualization with Dr. Nitin Paranjape
 
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Learn how to stop wasting time in cleaning up data. Invest that time in understanding the hidden information and grow faster than you ever imagined. Create stunning charts in seconds. All this using the familiar Excel, along with the new Power BI toolkit (Power Query, Power Map). Dr. Nitin Paranjape (Office MVP)
Views: 4254 Efficiency 365
Module 7: Visualizing Data in Excel
 
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This video is part of the Analyzing and Visualizing Data with Excel course available on EdX. To sign up for the course, visit: http://aka.ms/edxexcelbi
Views: 53091 DAT206x
E-DAB 05: Visualizing Data with Tables, Charts, Conditional Formatting & Dashboards
 
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Download Start Files: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/EDAB/E-DAB-05-Visualizations-Start.xlsx Download Finished Files: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/EDAB/E-DAB-05-Visualizations-Finished.xlsx Pdf notes: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/EDAB/E-DAB-05-Visualizations.pdf This video teaches about how to visualize in Excel with Tables, Conditional Formatting, Column and Bar Charts, Cross Tab Char (Clustered Column / Bar & Stacked Column / Bar), Line Chart, X Y Scatter Chart and Dashboards. Comprehensive Dashboard Example at end. This class : Data Analysis & Business Intelligence Made Easy with Excel Power Tools - Excel Data Analysis Basics = E-DAB Class – Sponsored by YouTube and taught by Mike Girvin, Highline College Instructor, Microsoft Excel MVP and founder of the excelisfun channel at YouTube. This is a free educational resource for people how want to learn about the Basics of Data Analysis and Business Intelligence using Microsoft Power Tools such as, PivotTables, Power Query, Power Pivot, Power BI Desktop and more. Topics: 1. (00:15) Introduction to topics, downloading files and visualizing examples in video. 2. (01:48) Why Visualize? Table or Visualization? 3. (03:47) Edward R. Tufte and High Data/Ink Ratio Rule and “No Chart Junk Rule” 4. (05:57) Tables Formatting Rules 5. (12:05) Conditional Formatting 6. (15:45) Column and Bar Charts 7. (24:04) Cross Tab Chart: Clustered Column / Bar & Stacked Column / Bar 8. (27:10) Line Chart: 1 Number 9. (29:47) Line Chart and IF Function for line chart that shows revenue and emphasizes promotions for company. 10. (35:40) X-Y Scatter Chart: 2 Numbers 11. (37:02) Comprehensive Dashboard example with PivotTables and Charts. Print Setup to allow printing. 12. (39:26) PivotTable Custom Style 13. (53:44) Summary The Power Query logo used in this video is copyright of and used with the express permission of https://powerquery.training Thanks to Ken Puls and Miguel Escobar for letting me use their logo!!!!
Views: 14938 ExcelIsFun
Introduction to Pivot Tables, Charts, and Dashboards in Excel (Part 1)
 
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WATCH PART 2: https://www.youtube.com/watch?v=g530cnFfk8Y Download file used in the video: http://www.excelcampus.com/pivot-table-checklist-yt In this video series you will learn how to create an interactive dashboard using Pivot Tables and Pivot Charts. Works with Excel 2003, 2007, 2010, 2013 for Windows & Excel 2011 for Mac Don't worry if you have never created a Pivot Table before, I cover the basics of formatting your source data and creating your first Pivot Table as well. You will also get to see an add-in I developed named PivotPal that makes it easier to work with some aspects of Pivot Tables. Download the files to follow along at the following link. http://www.excelcampus.com/pivot-table-checklist-yt I have another video that shows how to reformat the pivot chart in Excel 2010. In the video above I'm using Excel 2013 and the menus are different from Excel 2007/2010. Here is the link to that video. http://www.youtube.com/watch?v=Jt_QqG-vRRw Get PivotPal: http://www.excelcampus.com/pivotpal Free webinar on The 5 Secrets to Understanding Pivot Tables: https://www.excelcampus.com/pivot-webinar-yt Subscribe to my free newsletter: http://www.excelcampus.com/newsletter
Views: 7211040 Excel Campus - Jon
01| Visualization in excel - Data Analysis and Visualization
 
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Data Analysis and Visualization is a Richfull series Directed to all students interested in Analysing and Visualizing Data using Excel, MATLAB and Wolfram Mathematica. This Course has been made by an expert prophesors in University of Wistern Australia, and Contains the main folowing Topics: 1 Data Visualization in Excel 2 Array Formula in Excel 3 2D Array Formula in Excel 4 Excel Macros 5 Why Matlab 6 Problem Solving in MATLAB 7 MATLAB Orientation - Data Types and Expressions 8 MATLAB Scripts and Functions, Storing Instructions in Files, Getting Help on Build-in Functions 9 Matrices in MATLAB 10 MATLAB Scripts and Functions 11 Random Numbers, Gaussian Random Numbers, Complex Numbers 12 An Examples of Script and Function Files 13 Control Flow, Flow Chart, Relational Operators, Logical Operators, Truth Table, if clause, elseif, Nested if statments, Switch Structure, 14 MATLAB Loops, Nested Loops, Repetition, while, For, 15 Problems with Scripts, Workspace, Why Functions, How to Write a MATLAB Function, Anonymous Functions, 16 MATLAB Programs Input / Output, Escape Characters, Formatted Output, Syntax of Conversion Sequence, 17 Defensive Programming, error, warning, msg, isnumeric, ischar, nargin, nargout, nargchk, narginchk, all, 18 Cell Arrays, Array Types to Store data, Normal Arrays, Curly Brackets, Round Brackets, 19 MATLAB Structures, What is a Structure?, Adding a Field to a Structure, Struct Function, Manipulate the Fields, Preallocate Memory for a Structure Array 20 Basic 2D Plotting, title, xlabel, ylabel, grid, plot 21 Multiple Plots, figure, hold on, off, legend Function, String, Axis Scaling, Subplot, 22 Types of 2D Plots, Polar Plot, Logarithmic Plot, Bar Graphs, Pie Charts, Histograms, X-Y Graphs with 2 y Axes, Function Plots, 23 3D Plot, Line Plot, Surface Plot, Contour plots, Cylinder Plots, mesh, surf, contour, meshgrid, 24 Parametric Surfaces, Earth, Triangular Prism, Generating Points, Default Shading, Shading Flat, Shading Interp, 25 Arrays vs. Matrix Operations, 26 Dot Products, Example Calculating Center of Mass, Center of Gravity, 27 Matrix Multiplication and Division, Matrix Powers, Matrix Inverse, Determinatnts, Cross Products, 28 Applications of Matrix Operations, Solving Linear Equations, Linear Transformations, Eigenvectors 29 Engineering Application of Solving Systems of Linear Equations, Systems of Linear Equations, Kirchhoff's Circuit Laws, 30 Symbolic Differentiation, sym, syms, diff 31 Numerical Differentiation, fplot, Forward Difference, Backward Difference, Central Difference, 32 Numerical Integration, Engineering Applications, Integration, Trapezoid Rule, Simpson's Rule, 33 Monte Carlo Integration, 34 Introduction to ODE in System Biology 35 Introduction to System Biology, Gene Circuits, 36 Solving ODEs in Matlab, Repressilator, Programming steps 37 Interpolation, Cubic Spline Interpolation, Nearest Neighbor, Cubic, Two Dimensional, Three Dimensional, 38 Curve Fitting, Empirical Modelling, Linear Regression, Polynomial Regression, polyfit, polyval, Least Squres, 39 Introduction to Mathematica, 40 Programming in Mathematica 41 Basic Function in Mathematica, Strings, Characters, Polynomials, Solving Equations, Trigonometry, Calculus, 2D Ploting, Interactive Plots, Functions, Matlab vs. MAthematica 42 Numerical Data, Arthematic Operators, Data Types, Lists, Vectors, Matrices, String, Characters, 43 Mathematica Rule Based Programming, Functional Programming, 44 MAthematica Procedural Programming, Procedural Programs, Conditionals and Compositions, Looping Constructs, Errors, Modules, 45 Mathematica Predicates in Rule Based Programming, Patterns and Rules, Rules and Lists, Predicates, Blank, Blanksequence, BlackNullSequence, Number Puzzle, 46 Symbolic Mathematics and Programming, Rule Based Computation, Simplify, Expand, Solve, NSolve, Symbolic Visualisation, 47 Symbolic Computing in Matlab, Symbolic Algebra, sym, syms, Equations, Expressions, Systems of Equations, Calculus,
Views: 634 TO Courses
How to build Interactive Excel Dashboards
 
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Download file used in the video with step by step instructions and links to more tutorials: https://www.myonlinetraininghub.com/workbook-downloads In this video you will learn how to create an interactive dashboard from scratch using the built in Excel tools. No add-ins or VBA/Macros. Just plain Excel. Applies to Excel 2007 onward for Windows & Excel 2016 onward for Mac. Subscribe to my free newsletter and get my 100 Tips & Tricks eBook here: https://www.myonlinetraininghub.com/sign-up-for-100-excel-tips-and-tricks
Views: 2126168 MyOnlineTrainingHub
Realtime data analysis (visualization) in Ms Excel using macros and graphs
 
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Subscribe and hit bell icon to receive notifications of my upcoming posts. In this tutorial, we will see how to do realtime visualization of data in excel. You'll see graphs refreshing every second and show you the latest data. Music : www.bensound.com
do all data analysis with excel spss r and dashboard programming modeling visualization summarizatio
 
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Note:All work in this gig is CUSTOM made and my Previous work. Hi am Bio-Statistician .I will perform Data analyzes for any field of statistics at different levels of research work and Business Analysis. Visualization Summarized Analysis Detailed Analysis Forecasting Statistical Dashboard Eye Catching Presenting analysis Charts Tables Graphs Totals Pivot Others stata, spss, eviews, ms excel, computer, pro, data analysis statistical, spss, r programming data visualization, statistics data analysis, Microsoft excel, research analysis, data processing, r studio, tableau, visualization, infographics, flow charts, pie chart, graphic design, pivot table , charts, spreadsheet ,statistics scripting, data mining, r programming. Key Statistical Skills: -SPSS -R -EXCEL Finally, my priorities are customer satisfaction.
Intro to Data Analysis / Visualization with Python, Matplotlib and Pandas | Matplotlib Tutorial
 
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Python data analysis / data science tutorial. Let’s go! For more videos like this, I’d recommend my course here: https://www.csdojo.io/moredata Sample data and sample code: https://www.csdojo.io/data My explanation about Jupyter Notebook and Anaconda: https://bit.ly/2JAtjF8 Also, keep in touch on Twitter: https://twitter.com/ykdojo And Facebook: https://www.facebook.com/entercsdojo Outline - check the comment section for a clickable version: 0:37: Why data visualization? 1:05: Why Python? 1:39: Why Matplotlib? 2:23: Installing Jupyter through Anaconda 3:20: Launching Jupyter 3:41: DEMO begins: create a folder and download data 4:27: Create a new Jupyter Notebook file 5:09: Importing libraries 6:04: Simple examples of how to use Matplotlib / Pyplot 7:21: Plotting multiple lines 8:46: Importing data from a CSV file 10:46: Plotting data you’ve imported 13:19: Using a third argument in the plot() function 13:42: A real analysis with a real data set - loading data 14:49: Isolating the data for the U.S. and China 16:29: Plotting US and China’s population growth 18:22: Comparing relative growths instead of the absolute amount 21:21: About how to get more videos like this - it’s at https://www.csdojo.io/moredata
Views: 293651 CS Dojo
03| 2D Array Formula in Excel - Data Analysis and Visualization
 
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Data Analysis and Visualization is a Richfull series Directed to all students interested in Analysing and Visualizing Data using Excel, MATLAB and Wolfram Mathematica. This Course has been made by an expert prophesors in University of Wistern Australia, and Contains the main folowing Topics: 1 Data Visualization in Excel 2 Array Formula in Excel 3 2D Array Formula in Excel 4 Excel Macros 5 Why Matlab 6 Problem Solving in MATLAB 7 MATLAB Orientation - Data Types and Expressions 8 MATLAB Scripts and Functions, Storing Instructions in Files, Getting Help on Build-in Functions 9 Matrices in MATLAB 10 MATLAB Scripts and Functions 11 Random Numbers, Gaussian Random Numbers, Complex Numbers 12 An Examples of Script and Function Files 13 Control Flow, Flow Chart, Relational Operators, Logical Operators, Truth Table, if clause, elseif, Nested if statments, Switch Structure, 14 MATLAB Loops, Nested Loops, Repetition, while, For, 15 Problems with Scripts, Workspace, Why Functions, How to Write a MATLAB Function, Anonymous Functions, 16 MATLAB Programs Input / Output, Escape Characters, Formatted Output, Syntax of Conversion Sequence, 17 Defensive Programming, error, warning, msg, isnumeric, ischar, nargin, nargout, nargchk, narginchk, all, 18 Cell Arrays, Array Types to Store data, Normal Arrays, Curly Brackets, Round Brackets, 19 MATLAB Structures, What is a Structure?, Adding a Field to a Structure, Struct Function, Manipulate the Fields, Preallocate Memory for a Structure Array 20 Basic 2D Plotting, title, xlabel, ylabel, grid, plot 21 Multiple Plots, figure, hold on, off, legend Function, String, Axis Scaling, Subplot, 22 Types of 2D Plots, Polar Plot, Logarithmic Plot, Bar Graphs, Pie Charts, Histograms, X-Y Graphs with 2 y Axes, Function Plots, 23 3D Plot, Line Plot, Surface Plot, Contour plots, Cylinder Plots, mesh, surf, contour, meshgrid, 24 Parametric Surfaces, Earth, Triangular Prism, Generating Points, Default Shading, Shading Flat, Shading Interp, 25 Arrays vs. Matrix Operations, 26 Dot Products, Example Calculating Center of Mass, Center of Gravity, 27 Matrix Multiplication and Division, Matrix Powers, Matrix Inverse, Determinatnts, Cross Products, 28 Applications of Matrix Operations, Solving Linear Equations, Linear Transformations, Eigenvectors 29 Engineering Application of Solving Systems of Linear Equations, Systems of Linear Equations, Kirchhoff's Circuit Laws, 30 Symbolic Differentiation, sym, syms, diff 31 Numerical Differentiation, fplot, Forward Difference, Backward Difference, Central Difference, 32 Numerical Integration, Engineering Applications, Integration, Trapezoid Rule, Simpson's Rule, 33 Monte Carlo Integration, 34 Introduction to ODE in System Biology 35 Introduction to System Biology, Gene Circuits, 36 Solving ODEs in Matlab, Repressilator, Programming steps 37 Interpolation, Cubic Spline Interpolation, Nearest Neighbor, Cubic, Two Dimensional, Three Dimensional, 38 Curve Fitting, Empirical Modelling, Linear Regression, Polynomial Regression, polyfit, polyval, Least Squres, 39 Introduction to Mathematica, 40 Programming in Mathematica 41 Basic Function in Mathematica, Strings, Characters, Polynomials, Solving Equations, Trigonometry, Calculus, 2D Ploting, Interactive Plots, Functions, Matlab vs. MAthematica 42 Numerical Data, Arthematic Operators, Data Types, Lists, Vectors, Matrices, String, Characters, 43 Mathematica Rule Based Programming, Functional Programming, 44 MAthematica Procedural Programming, Procedural Programs, Conditionals and Compositions, Looping Constructs, Errors, Modules, 45 Mathematica Predicates in Rule Based Programming, Patterns and Rules, Rules and Lists, Predicates, Blank, Blanksequence, BlackNullSequence, Number Puzzle, 46 Symbolic Mathematics and Programming, Rule Based Computation, Simplify, Expand, Solve, NSolve, Symbolic Visualisation, 47 Symbolic Computing in Matlab, Symbolic Algebra, sym, syms, Equations, Expressions, Systems of Equations, Calculus,
Views: 77 TO Courses
Analyze and Visualize Data using Excel and Access Together
 
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When your data is available partially in Excel and Partially in Access we can bring it All together, then create calculations and functions using the data from multiple sources. We can then Export our data back to Excel and perform our analysis by creating nice looking impressive Charts in Excel. You can download the exercise files and follow along by going to my website www.OfficeInstructor.ca and click on "Downloads" then select the exercise file to download. To be notified when new videos are published, make sure you subscribe to this channel... Your comments are always appreciated.
Views: 1339 Officeinstructor
Data Visualization With Excel | Edureka
 
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Explore the art of data visualization with Excel. This webinar covers the following topics: Types of Charts Speedometer Charts Thermometer Charts Combinational Charts Usage of Tables to make dynamically updated Charts Learn more at: http://www.edureka.co/advanced-ms-excel
Views: 3226 edureka!
Excel Data Analysis: Visualize data  with Sparklines.
 
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Track and highlight important data trends with Sparklines. With new data analysis and visualization tools Sparklines are mini-charts placed inside cells so that you can view the data and the chart on the same table. http://www.trainsignal.com/Office-2010-Training-Package.aspx?utm_source=YouTube&utm_medium=Social%20Media&utm_campaign=YouTubeOffice%20Referral&utm_content=excel%202010
Excel for Data Analysis and Visualization | Microsoft on edX | Course About Video
 
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Take this course for free on edX: https://www.edx.org/course/excel-data-analysis-visualization-microsoft-dat206x ↓ More info below. ↓ Follow on Facebook: https://www.facebook.com/edX Follow on Twitter: https://www.twitter.com/edxonline Follow on YouTube: https://www.youtube.com/user/edxonline About this course Microsoft Excel is one of the most widely used solutions for analyzing and visualizing data. Beginning with Excel 2010, new tools were introduced to enable the analysis of more data, resulting in less time spent creating and maintaining the solutions and enabling a better understanding of what the data means. This better understanding is facilitated by improved visualizations and more sophisticated business logics. Do you want to take your advanced Excel skills to the next level? Are you exploring new ways to get and transform your data and create visualization? Check out this practical new course, taught in short, lecture-based videos, complete with demos, quizzes, and hands-on labs, and skill up on many of the built-in business intelligence (BI) tools and features in Excel. ​Learn how to present the most relevant data with dynamic reports and presentations, as expert Dany Hoter walks you through all the important details. In this course, get an introduction to the latest versions of these new tools in Excel 2016. See how to import data from different sources, create mashups between data sources, and prepare the data for analysis. After preparing the data, learn about how business calculations—from simple to more advanced—can be expressed using the DAX calculation engine. And see how these different technologies work together inside Excel. Learn how the data can be visualized and shared to the Power BI cloud service, after which it can be used in dashboards, queried using plain English sentences, and consumed on mobile devices.
Views: 13741 edX
How to visualize Excel data in Tableau
 
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Here I have shown the high-level view on how to visualize the excel data in Tableau. Tableau Public 10.2 Data - Hollywood most profitable Movie
Views: 20471 visualizer bi
40| Mathematica Introduction to Programming - Data Analysis and Visualization
 
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Data Analysis and Visualization is a Rich-full series Directed to all students interested in Analyzing and Visualizing Data using Excel, MATLAB and Wolfram Mathematica. This Course has been made by an expert prophesiers in University of Western Australia, and Contains the main flowing Topics: 1 Data Visualization in Excel 2 Array Formula in Excel 3 2D Array Formula in Excel 4 Excel Macros 5 Why Matlab 6 Problem Solving in MATLAB 7 MATLAB Orientation - Data Types and Expressions 8 MATLAB Scripts and Functions, Storing Instructions in Files, Getting Help on Build-in Functions 9 Matrices in MATLAB 10 MATLAB Scripts and Functions 11 Random Numbers, Gaussian Random Numbers, Complex Numbers 12 An Examples of Script and Function Files 13 Control Flow, Flow Chart, Relational Operators, Logical Operators, Truth Table, if clause, elseif, Nested if statments, Switch Structure, 14 MATLAB Loops, Nested Loops, Repetition, while, For, 15 Problems with Scripts, Workspace, Why Functions, How to Write a MATLAB Function, Anonymous Functions, 16 MATLAB Programs Input / Output, Escape Characters, Formatted Output, Syntax of Conversion Sequence, 17 Defensive Programming, error, warning, msg, isnumeric, ischar, nargin, nargout, nargchk, narginchk, all, 18 Cell Arrays, Array Types to Store data, Normal Arrays, Curly Brackets, Round Brackets, 19 MATLAB Structures, What is a Structure?, Adding a Field to a Structure, Struct Function, Manipulate the Fields, Preallocate Memory for a Structure Array 20 Basic 2D Plotting, title, xlabel, ylabel, grid, plot 21 Multiple Plots, figure, hold on, off, legend Function, String, Axis Scaling, Subplot, 22 Types of 2D Plots, Polar Plot, Logarithmic Plot, Bar Graphs, Pie Charts, Histograms, X-Y Graphs with 2 y Axes, Function Plots, 23 3D Plot, Line Plot, Surface Plot, Contour plots, Cylinder Plots, mesh, surf, contour, meshgrid, 24 Parametric Surfaces, Earth, Triangular Prism, Generating Points, Default Shading, Shading Flat, Shading Interp, 25 Arrays vs. Matrix Operations, 26 Dot Products, Example Calculating Center of Mass, Center of Gravity, 27 Matrix Multiplication and Division, Matrix Powers, Matrix Inverse, Determinatnts, Cross Products, 28 Applications of Matrix Operations, Solving Linear Equations, Linear Transformations, Eigenvectors 29 Engineering Application of Solving Systems of Linear Equations, Systems of Linear Equations, Kirchhoff's Circuit Laws, 30 Symbolic Differentiation, sym, syms, diff 31 Numerical Differentiation, fplot, Forward Difference, Backward Difference, Central Difference, 32 Numerical Integration, Engineering Applications, Integration, Trapezoid Rule, Simpson's Rule, 33 Monte Carlo Integration, 34 Introduction to ODE in System Biology 35 Introduction to System Biology, Gene Circuits, 36 Solving ODEs in Matlab, Repressilator, Programming steps 37 Interpolation, Cubic Spline Interpolation, Nearest Neighbor, Cubic, Two Dimensional, Three Dimensional, 38 Curve Fitting, Empirical Modelling, Linear Regression, Polynomial Regression, polyfit, polyval, Least Squres, 39 Introduction to Mathematica, 40 Programming in Mathematica 41 Basic Function in Mathematica, Strings, Characters, Polynomials, Solving Equations, Trigonometry, Calculus, 2D Ploting, Interactive Plots, Functions, Matlab vs. MAthematica 42 Numerical Data, Arthematic Operators, Data Types, Lists, Vectors, Matrices, String, Characters, 43 Mathematica Rule Based Programming, Functional Programming, 44 MAthematica Procedural Programming, Procedural Programs, Conditionals and Compositions, Looping Constructs, Errors, Modules, 45 Mathematica Predicates in Rule Based Programming, Patterns and Rules, Rules and Lists, Predicates, Blank, Blanksequence, BlackNullSequence, Number Puzzle, 46 Symbolic Mathematics and Programming, Rule Based Computation, Simplify, Expand, Solve, NSolve, Symbolic Visualisation, 47 Symbolic Computing in Matlab, Symbolic Algebra, sym, syms, Equations, Expressions, Systems of Equations, Calculus,
Views: 231 TO Courses
Analyze Stock Data with Microsoft Excel
 
17:50
Visualization of data is a powerful method to see trends and make decisions. Microsoft Excel trending capabilities are tools to visualize large data sets, such as financial information on company performance.
Views: 19612 APMonitor.com
23| 3D Plot in Matlab - Data Analysis and Visualization
 
29:29
Data Analysis and Visualization is a Rich-full series Directed to all students interested in Analyzing and Visualizing Data using Excel, MATLAB and Wolfram Mathematica. This Course has been made by an expert prophesiers in University of Western Australia, and Contains the main flowing Topics: 1 Data Visualization in Excel 2 Array Formula in Excel 3 2D Array Formula in Excel 4 Excel Macros 5 Why Matlab 6 Problem Solving in MATLAB 7 MATLAB Orientation - Data Types and Expressions 8 MATLAB Scripts and Functions, Storing Instructions in Files, Getting Help on Build-in Functions 9 Matrices in MATLAB 10 MATLAB Scripts and Functions 11 Random Numbers, Gaussian Random Numbers, Complex Numbers 12 An Examples of Script and Function Files 13 Control Flow, Flow Chart, Relational Operators, Logical Operators, Truth Table, if clause, elseif, Nested if statments, Switch Structure, 14 MATLAB Loops, Nested Loops, Repetition, while, For, 15 Problems with Scripts, Workspace, Why Functions, How to Write a MATLAB Function, Anonymous Functions, 16 MATLAB Programs Input / Output, Escape Characters, Formatted Output, Syntax of Conversion Sequence, 17 Defensive Programming, error, warning, msg, isnumeric, ischar, nargin, nargout, nargchk, narginchk, all, 18 Cell Arrays, Array Types to Store data, Normal Arrays, Curly Brackets, Round Brackets, 19 MATLAB Structures, What is a Structure?, Adding a Field to a Structure, Struct Function, Manipulate the Fields, Preallocate Memory for a Structure Array 20 Basic 2D Plotting, title, xlabel, ylabel, grid, plot 21 Multiple Plots, figure, hold on, off, legend Function, String, Axis Scaling, Subplot, 22 Types of 2D Plots, Polar Plot, Logarithmic Plot, Bar Graphs, Pie Charts, Histograms, X-Y Graphs with 2 y Axes, Function Plots, 23 3D Plot, Line Plot, Surface Plot, Contour plots, Cylinder Plots, mesh, surf, contour, meshgrid, 24 Parametric Surfaces, Earth, Triangular Prism, Generating Points, Default Shading, Shading Flat, Shading Interp, 25 Arrays vs. Matrix Operations, 26 Dot Products, Example Calculating Center of Mass, Center of Gravity, 27 Matrix Multiplication and Division, Matrix Powers, Matrix Inverse, Determinatnts, Cross Products, 28 Applications of Matrix Operations, Solving Linear Equations, Linear Transformations, Eigenvectors 29 Engineering Application of Solving Systems of Linear Equations, Systems of Linear Equations, Kirchhoff's Circuit Laws, 30 Symbolic Differentiation, sym, syms, diff 31 Numerical Differentiation, fplot, Forward Difference, Backward Difference, Central Difference, 32 Numerical Integration, Engineering Applications, Integration, Trapezoid Rule, Simpson's Rule, 33 Monte Carlo Integration, 34 Introduction to ODE in System Biology 35 Introduction to System Biology, Gene Circuits, 36 Solving ODEs in Matlab, Repressilator, Programming steps 37 Interpolation, Cubic Spline Interpolation, Nearest Neighbor, Cubic, Two Dimensional, Three Dimensional, 38 Curve Fitting, Empirical Modelling, Linear Regression, Polynomial Regression, polyfit, polyval, Least Squres, 39 Introduction to Mathematica, 40 Programming in Mathematica 41 Basic Function in Mathematica, Strings, Characters, Polynomials, Solving Equations, Trigonometry, Calculus, 2D Ploting, Interactive Plots, Functions, Matlab vs. MAthematica 42 Numerical Data, Arthematic Operators, Data Types, Lists, Vectors, Matrices, String, Characters, 43 Mathematica Rule Based Programming, Functional Programming, 44 MAthematica Procedural Programming, Procedural Programs, Conditionals and Compositions, Looping Constructs, Errors, Modules, 45 Mathematica Predicates in Rule Based Programming, Patterns and Rules, Rules and Lists, Predicates, Blank, Blanksequence, BlackNullSequence, Number Puzzle, 46 Symbolic Mathematics and Programming, Rule Based Computation, Simplify, Expand, Solve, NSolve, Symbolic Visualisation, 47 Symbolic Computing in Matlab, Symbolic Algebra, sym, syms, Equations, Expressions, Systems of Equations, Calculus,
Views: 344 TO Courses
Data Visualization Tutorial For Beginners | Big Data Analytics Tutorial | Simplilearn
 
27:21
This Data Visualization Tutorial will start by explain what Data Visualization is, Why we use Data Visualization, major considerations for Data Visualization and the basics of different types of graphs. Subscribe to Simplilearn channel for more Big Data and Hadoop Tutorials - https://www.youtube.com/user/Simplilearn?sub_confirmation=1 Check our Big Data Training Video Playlist: https://www.youtube.com/playlist?list=PLEiEAq2VkUUJqp1k-g5W1mo37urJQOdCZ Big Data and Analytics Articles - https://www.simplilearn.com/resources/big-data-and-analytics?utm_campaign=BigData-Visualization-MiiANxRHSv4&utm_medium=Tutorials&utm_source=youtube To gain in-depth knowledge of Big Data and Hadoop, check our Big Data Hadoop and Spark Developer Certification Training Course: https://www.simplilearn.com/big-data-and-analytics/big-data-and-hadoop-training?utm_campaign=BigData-Visualization-MiiANxRHSv4&utm_medium=Tutorials&utm_source=youtube #bigdata #bigdatatutorialforbeginners #bigdataanalytics #bigdatahadooptutorialforbeginners #bigdatacertification #HadoopTutorial - - - - - - - - - About Simplilearn's Big Data and Hadoop Certification Training Course: The Big Data Hadoop and Spark developer course have been designed to impart an in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab. Mastering real-time data processing using Spark: You will learn to do functional programming in Spark, implement Spark applications, understand parallel processing in Spark, and use Spark RDD optimization techniques. You will also learn the various interactive algorithm in Spark and use Spark SQL for creating, transforming, and querying data form. As a part of the course, you will be required to execute real-life industry-based projects using CloudLab. The projects included are in the domains of Banking, Telecommunication, Social media, Insurance, and E-commerce. This Big Data course also prepares you for the Cloudera CCA175 certification. - - - - - - - - What are the course objectives of this Big Data and Hadoop Certification Training Course? This course will enable you to: 1. Understand the different components of Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark 2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management 3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts 4. Get an overview of Sqoop and Flume and describe how to ingest data using them 5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning 6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution 7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations 8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS 9. Gain a working knowledge of Pig and its components 10. Do functional programming in Spark 11. Understand resilient distribution datasets (RDD) in detail 12. Implement and build Spark applications 13. Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques 14. Understand the common use-cases of Spark and the various interactive algorithms 15. Learn Spark SQL, creating, transforming, and querying Data frames - - - - - - - - - - - Who should take up this Big Data and Hadoop Certification Training Course? Big Data career opportunities are on the rise, and Hadoop is quickly becoming a must-know technology for the following professionals: 1. Software Developers and Architects 2. Analytics Professionals 3. Senior IT professionals 4. Testing and Mainframe professionals 5. Data Management Professionals 6. Business Intelligence Professionals 7. Project Managers 8. Aspiring Data Scientists - - - - - - - - For more updates on courses and tips follow us on: - Facebook : https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn - LinkedIn: https://www.linkedin.com/company/simplilearn - Website: https://www.simplilearn.com Get the android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 4678 Simplilearn
Visualizing table data in a chart | Excel cluster analysis | lynda.com
 
04:33
When you analyze your Excel data using cluster analysis, it often helps to visualize the clusters using an XY scatter chart. Find out how to visualize table data in a chart in this tutorial. Watch more at http://www.lynda.com/Excel-tutorials/Up-Running-Excel-Cluster-Analysis/165438-2.html?utm_campaign=55QCaggZ9Lw&utm_medium=social&utm_source=youtube-earned. This tutorial is a single movie from the Up and Running with Excel Cluster Analysis course by lynda.com author Curt Frye. The complete course is 1 hour and 10 minutes and shows how to perform cluster analysis using Excel. Connect with lynda.com: Facebook: ‪http://bit.ly/fbldc‬ Twitter: ‪http://bit.ly/ldctw‬ Google Plus: ‪http://bit.ly/gplusldc‬ LinkedIn: ‪http://bit.ly/linkldc‬
Views: 6500 LinkedIn Learning
Getting Started with Python | Data Analysis and Visualization
 
16:27
Uses yhat rodeo that has IDE similar to RStudio and matlab. Data file link: https://drive.google.com/open?id=1tHAdr3V1N8BzZShg0A5ZU6eAUN_9kZZf
Views: 1276 Bharatendra Rai
05| Why Matlab - Data Analysis and Visualization
 
12:07
Data Analysis and Visualization is a Richfull series Directed to all students interested in Analysing and Visualizing Data using Excel, MATLAB and Wolfram Mathematica. This Course has been made by an expert prophesors in University of Wistern Australia, and Contains the main folowing Topics: 1 Data Visualization in Excel 2 Array Formula in Excel 3 2D Array Formula in Excel 4 Excel Macros 5 Why Matlab 6 Problem Solving in MATLAB 7 MATLAB Orientation - Data Types and Expressions 8 MATLAB Scripts and Functions, Storing Instructions in Files, Getting Help on Build-in Functions 9 Matrices in MATLAB 10 MATLAB Scripts and Functions 11 Random Numbers, Gaussian Random Numbers, Complex Numbers 12 An Examples of Script and Function Files 13 Control Flow, Flow Chart, Relational Operators, Logical Operators, Truth Table, if clause, elseif, Nested if statments, Switch Structure, 14 MATLAB Loops, Nested Loops, Repetition, while, For, 15 Problems with Scripts, Workspace, Why Functions, How to Write a MATLAB Function, Anonymous Functions, 16 MATLAB Programs Input / Output, Escape Characters, Formatted Output, Syntax of Conversion Sequence, 17 Defensive Programming, error, warning, msg, isnumeric, ischar, nargin, nargout, nargchk, narginchk, all, 18 Cell Arrays, Array Types to Store data, Normal Arrays, Curly Brackets, Round Brackets, 19 MATLAB Structures, What is a Structure?, Adding a Field to a Structure, Struct Function, Manipulate the Fields, Preallocate Memory for a Structure Array 20 Basic 2D Plotting, title, xlabel, ylabel, grid, plot 21 Multiple Plots, figure, hold on, off, legend Function, String, Axis Scaling, Subplot, 22 Types of 2D Plots, Polar Plot, Logarithmic Plot, Bar Graphs, Pie Charts, Histograms, X-Y Graphs with 2 y Axes, Function Plots, 23 3D Plot, Line Plot, Surface Plot, Contour plots, Cylinder Plots, mesh, surf, contour, meshgrid, 24 Parametric Surfaces, Earth, Triangular Prism, Generating Points, Default Shading, Shading Flat, Shading Interp, 25 Arrays vs. Matrix Operations, 26 Dot Products, Example Calculating Center of Mass, Center of Gravity, 27 Matrix Multiplication and Division, Matrix Powers, Matrix Inverse, Determinatnts, Cross Products, 28 Applications of Matrix Operations, Solving Linear Equations, Linear Transformations, Eigenvectors 29 Engineering Application of Solving Systems of Linear Equations, Systems of Linear Equations, Kirchhoff's Circuit Laws, 30 Symbolic Differentiation, sym, syms, diff 31 Numerical Differentiation, fplot, Forward Difference, Backward Difference, Central Difference, 32 Numerical Integration, Engineering Applications, Integration, Trapezoid Rule, Simpson's Rule, 33 Monte Carlo Integration, 34 Introduction to ODE in System Biology 35 Introduction to System Biology, Gene Circuits, 36 Solving ODEs in Matlab, Repressilator, Programming steps 37 Interpolation, Cubic Spline Interpolation, Nearest Neighbor, Cubic, Two Dimensional, Three Dimensional, 38 Curve Fitting, Empirical Modelling, Linear Regression, Polynomial Regression, polyfit, polyval, Least Squres, 39 Introduction to Mathematica, 40 Programming in Mathematica 41 Basic Function in Mathematica, Strings, Characters, Polynomials, Solving Equations, Trigonometry, Calculus, 2D Ploting, Interactive Plots, Functions, Matlab vs. MAthematica 42 Numerical Data, Arthematic Operators, Data Types, Lists, Vectors, Matrices, String, Characters, 43 Mathematica Rule Based Programming, Functional Programming, 44 MAthematica Procedural Programming, Procedural Programs, Conditionals and Compositions, Looping Constructs, Errors, Modules, 45 Mathematica Predicates in Rule Based Programming, Patterns and Rules, Rules and Lists, Predicates, Blank, Blanksequence, BlackNullSequence, Number Puzzle, 46 Symbolic Mathematics and Programming, Rule Based Computation, Simplify, Expand, Solve, NSolve, Symbolic Visualisation, 47 Symbolic Computing in Matlab, Symbolic Algebra, sym, syms, Equations, Expressions, Systems of Equations, Calculus,
Views: 158 TO Courses
Graphing/visualization - Data Analysis with Python and Pandas p.2
 
27:44
Doing some basic visualizations with our Pandas dataframe in Python with Matplotlib. Text-based tutorial: https://pythonprogramming.net/graph-visualization-python3-pandas-data-analysis/ Channel membership: https://www.youtube.com/channel/UCfzlCWGWYyIQ0aLC5w48gBQ/join Discord: https://discord.gg/sentdex Support the content: https://pythonprogramming.net/support-donate/ Twitter: https://twitter.com/sentdex Facebook: https://www.facebook.com/pythonprogramming.net/ Twitch: https://www.twitch.tv/sentdex G+: https://plus.google.com/+sentdex
Views: 21345 sentdex
18| Cell Arrays in MATLAB - Data Analysis and Visualization
 
25:28
Data Analysis and Visualization is a Rich-full series Directed to all students interested in Analyzing and Visualizing Data using Excel, MATLAB and Wolfram Mathematica. This Course has been made by an expert prophesiers in University of Western Australia, and Contains the main flowing Topics: 1 Data Visualization in Excel 2 Array Formula in Excel 3 2D Array Formula in Excel 4 Excel Macros 5 Why Matlab 6 Problem Solving in MATLAB 7 MATLAB Orientation - Data Types and Expressions 8 MATLAB Scripts and Functions, Storing Instructions in Files, Getting Help on Build-in Functions 9 Matrices in MATLAB 10 MATLAB Scripts and Functions 11 Random Numbers, Gaussian Random Numbers, Complex Numbers 12 An Examples of Script and Function Files 13 Control Flow, Flow Chart, Relational Operators, Logical Operators, Truth Table, if clause, elseif, Nested if statments, Switch Structure, 14 MATLAB Loops, Nested Loops, Repetition, while, For, 15 Problems with Scripts, Workspace, Why Functions, How to Write a MATLAB Function, Anonymous Functions, 16 MATLAB Programs Input / Output, Escape Characters, Formatted Output, Syntax of Conversion Sequence, 17 Defensive Programming, error, warning, msg, isnumeric, ischar, nargin, nargout, nargchk, narginchk, all, 18 Cell Arrays, Array Types to Store data, Normal Arrays, Curly Brackets, Round Brackets, 19 MATLAB Structures, What is a Structure?, Adding a Field to a Structure, Struct Function, Manipulate the Fields, Preallocate Memory for a Structure Array 20 Basic 2D Plotting, title, xlabel, ylabel, grid, plot 21 Multiple Plots, figure, hold on, off, legend Function, String, Axis Scaling, Subplot, 22 Types of 2D Plots, Polar Plot, Logarithmic Plot, Bar Graphs, Pie Charts, Histograms, X-Y Graphs with 2 y Axes, Function Plots, 23 3D Plot, Line Plot, Surface Plot, Contour plots, Cylinder Plots, mesh, surf, contour, meshgrid, 24 Parametric Surfaces, Earth, Triangular Prism, Generating Points, Default Shading, Shading Flat, Shading Interp, 25 Arrays vs. Matrix Operations, 26 Dot Products, Example Calculating Center of Mass, Center of Gravity, 27 Matrix Multiplication and Division, Matrix Powers, Matrix Inverse, Determinatnts, Cross Products, 28 Applications of Matrix Operations, Solving Linear Equations, Linear Transformations, Eigenvectors 29 Engineering Application of Solving Systems of Linear Equations, Systems of Linear Equations, Kirchhoff's Circuit Laws, 30 Symbolic Differentiation, sym, syms, diff 31 Numerical Differentiation, fplot, Forward Difference, Backward Difference, Central Difference, 32 Numerical Integration, Engineering Applications, Integration, Trapezoid Rule, Simpson's Rule, 33 Monte Carlo Integration, 34 Introduction to ODE in System Biology 35 Introduction to System Biology, Gene Circuits, 36 Solving ODEs in Matlab, Repressilator, Programming steps 37 Interpolation, Cubic Spline Interpolation, Nearest Neighbor, Cubic, Two Dimensional, Three Dimensional, 38 Curve Fitting, Empirical Modelling, Linear Regression, Polynomial Regression, polyfit, polyval, Least Squres, 39 Introduction to Mathematica, 40 Programming in Mathematica 41 Basic Function in Mathematica, Strings, Characters, Polynomials, Solving Equations, Trigonometry, Calculus, 2D Ploting, Interactive Plots, Functions, Matlab vs. MAthematica 42 Numerical Data, Arthematic Operators, Data Types, Lists, Vectors, Matrices, String, Characters, 43 Mathematica Rule Based Programming, Functional Programming, 44 MAthematica Procedural Programming, Procedural Programs, Conditionals and Compositions, Looping Constructs, Errors, Modules, 45 Mathematica Predicates in Rule Based Programming, Patterns and Rules, Rules and Lists, Predicates, Blank, Blanksequence, BlackNullSequence, Number Puzzle, 46 Symbolic Mathematics and Programming, Rule Based Computation, Simplify, Expand, Solve, NSolve, Symbolic Visualisation, 47 Symbolic Computing in Matlab, Symbolic Algebra, sym, syms, Equations, Expressions, Systems of Equations, Calculus,
Views: 186 TO Courses
41| Basic Functions in Mathematica - Data Analysis and Visualization
 
37:06
Data Analysis and Visualization is a Rich-full series Directed to all students interested in Analyzing and Visualizing Data using Excel, MATLAB and Wolfram Mathematica. This Course has been made by an expert prophesiers in University of Western Australia, and Contains the main flowing Topics: 1 Data Visualization in Excel 2 Array Formula in Excel 3 2D Array Formula in Excel 4 Excel Macros 5 Why Matlab 6 Problem Solving in MATLAB 7 MATLAB Orientation - Data Types and Expressions 8 MATLAB Scripts and Functions, Storing Instructions in Files, Getting Help on Build-in Functions 9 Matrices in MATLAB 10 MATLAB Scripts and Functions 11 Random Numbers, Gaussian Random Numbers, Complex Numbers 12 An Examples of Script and Function Files 13 Control Flow, Flow Chart, Relational Operators, Logical Operators, Truth Table, if clause, elseif, Nested if statments, Switch Structure, 14 MATLAB Loops, Nested Loops, Repetition, while, For, 15 Problems with Scripts, Workspace, Why Functions, How to Write a MATLAB Function, Anonymous Functions, 16 MATLAB Programs Input / Output, Escape Characters, Formatted Output, Syntax of Conversion Sequence, 17 Defensive Programming, error, warning, msg, isnumeric, ischar, nargin, nargout, nargchk, narginchk, all, 18 Cell Arrays, Array Types to Store data, Normal Arrays, Curly Brackets, Round Brackets, 19 MATLAB Structures, What is a Structure?, Adding a Field to a Structure, Struct Function, Manipulate the Fields, Preallocate Memory for a Structure Array 20 Basic 2D Plotting, title, xlabel, ylabel, grid, plot 21 Multiple Plots, figure, hold on, off, legend Function, String, Axis Scaling, Subplot, 22 Types of 2D Plots, Polar Plot, Logarithmic Plot, Bar Graphs, Pie Charts, Histograms, X-Y Graphs with 2 y Axes, Function Plots, 23 3D Plot, Line Plot, Surface Plot, Contour plots, Cylinder Plots, mesh, surf, contour, meshgrid, 24 Parametric Surfaces, Earth, Triangular Prism, Generating Points, Default Shading, Shading Flat, Shading Interp, 25 Arrays vs. Matrix Operations, 26 Dot Products, Example Calculating Center of Mass, Center of Gravity, 27 Matrix Multiplication and Division, Matrix Powers, Matrix Inverse, Determinatnts, Cross Products, 28 Applications of Matrix Operations, Solving Linear Equations, Linear Transformations, Eigenvectors 29 Engineering Application of Solving Systems of Linear Equations, Systems of Linear Equations, Kirchhoff's Circuit Laws, 30 Symbolic Differentiation, sym, syms, diff 31 Numerical Differentiation, fplot, Forward Difference, Backward Difference, Central Difference, 32 Numerical Integration, Engineering Applications, Integration, Trapezoid Rule, Simpson's Rule, 33 Monte Carlo Integration, 34 Introduction to ODE in System Biology 35 Introduction to System Biology, Gene Circuits, 36 Solving ODEs in Matlab, Repressilator, Programming steps 37 Interpolation, Cubic Spline Interpolation, Nearest Neighbor, Cubic, Two Dimensional, Three Dimensional, 38 Curve Fitting, Empirical Modelling, Linear Regression, Polynomial Regression, polyfit, polyval, Least Squres, 39 Introduction to Mathematica, 40 Programming in Mathematica 41 Basic Function in Mathematica, Strings, Characters, Polynomials, Solving Equations, Trigonometry, Calculus, 2D Ploting, Interactive Plots, Functions, Matlab vs. MAthematica 42 Numerical Data, Arthematic Operators, Data Types, Lists, Vectors, Matrices, String, Characters, 43 Mathematica Rule Based Programming, Functional Programming, 44 MAthematica Procedural Programming, Procedural Programs, Conditionals and Compositions, Looping Constructs, Errors, Modules, 45 Mathematica Predicates in Rule Based Programming, Patterns and Rules, Rules and Lists, Predicates, Blank, Blanksequence, BlackNullSequence, Number Puzzle, 46 Symbolic Mathematics and Programming, Rule Based Computation, Simplify, Expand, Solve, NSolve, Symbolic Visualisation, 47 Symbolic Computing in Matlab, Symbolic Algebra, sym, syms, Equations, Expressions, Systems of Equations, Calculus,
Views: 175 TO Courses
Intro to Data Visualization with R & ggplot2
 
01:11:15
The R programming language is experiencing rapid increases in popularity and wide adoption across industries. This popularity is due, in part, to R’s rich and powerful data visualization capabilities. While tools like Excel, Power BI, and Tableau are often the go-to solutions for data visualizations, none of these tools can compete with R in terms of the sheer breadth of, and control over, crafted data visualizations. As an example, R’s ggplot2 package provides the R programmer with dozens of print-quality visualizations – where any visualization can be heavily customized with a minimal amount of code. In this webinar Dave Langer will provide an introduction to data visualization with the ggplot2 package. The focus of the webinar will be using ggplot2 to analyze your data visually with a specific focus on discovering the underlying signals/patterns of your business. Attendees will learn how to: • Craft ggplot visualizations, including customization of rendered output. • Choose optimal visualizations for the type of data and the nature of the analysis at hand. • Leverage ggplot2’s powerful segmentation capabilities to achieve “visual drill-in of data”. • Export ggplot2 visualizations from RStudio for use in documents and presentations. Repository: https://code.datasciencedojo.com/datasciencedojo/tutorials/tree/master/Introduction%20to%20Data%20Visualization%20with%20R%20and%20ggplot2 -- Learn more about Data Science Dojo here: https://hubs.ly/H0hz6V50 Watch the latest video tutorials here: https://hubs.ly/H0hz6W80 See what our past attendees are saying here: https://hubs.ly/H0hz5ZJ0 -- Like Us: https://www.facebook.com/datasciencedojo/ Follow Us: https://twitter.com/DataScienceDojo Connect with Us: https://www.linkedin.com/company/data-science-dojo Also find us on: Instagram: https://www.instagram.com/data_science_dojo/ Vimeo: https://vimeo.com/datasciencedojo #rtutorial #datavisualization
Views: 113104 Data Science Dojo
Import Data and Analyze with Python
 
11:58
Python programming language allows sophisticated data analysis and visualization. This tutorial is a basic step-by-step introduction on how to import a text file (CSV), perform simple data analysis, export the results as a text file, and generate a trend. See https://youtu.be/pQv6zMlYJ0A for updated video for Python 3.
Views: 213707 APMonitor.com
37| Interpolation in MATLAB - Data Analysis and Visualization
 
14:48
Data Analysis and Visualization is a Rich-full series Directed to all students interested in Analyzing and Visualizing Data using Excel, MATLAB and Wolfram Mathematica. This Course has been made by an expert prophesiers in University of Western Australia, and Contains the main flowing Topics: 1 Data Visualization in Excel 2 Array Formula in Excel 3 2D Array Formula in Excel 4 Excel Macros 5 Why Matlab 6 Problem Solving in MATLAB 7 MATLAB Orientation - Data Types and Expressions 8 MATLAB Scripts and Functions, Storing Instructions in Files, Getting Help on Build-in Functions 9 Matrices in MATLAB 10 MATLAB Scripts and Functions 11 Random Numbers, Gaussian Random Numbers, Complex Numbers 12 An Examples of Script and Function Files 13 Control Flow, Flow Chart, Relational Operators, Logical Operators, Truth Table, if clause, elseif, Nested if statments, Switch Structure, 14 MATLAB Loops, Nested Loops, Repetition, while, For, 15 Problems with Scripts, Workspace, Why Functions, How to Write a MATLAB Function, Anonymous Functions, 16 MATLAB Programs Input / Output, Escape Characters, Formatted Output, Syntax of Conversion Sequence, 17 Defensive Programming, error, warning, msg, isnumeric, ischar, nargin, nargout, nargchk, narginchk, all, 18 Cell Arrays, Array Types to Store data, Normal Arrays, Curly Brackets, Round Brackets, 19 MATLAB Structures, What is a Structure?, Adding a Field to a Structure, Struct Function, Manipulate the Fields, Preallocate Memory for a Structure Array 20 Basic 2D Plotting, title, xlabel, ylabel, grid, plot 21 Multiple Plots, figure, hold on, off, legend Function, String, Axis Scaling, Subplot, 22 Types of 2D Plots, Polar Plot, Logarithmic Plot, Bar Graphs, Pie Charts, Histograms, X-Y Graphs with 2 y Axes, Function Plots, 23 3D Plot, Line Plot, Surface Plot, Contour plots, Cylinder Plots, mesh, surf, contour, meshgrid, 24 Parametric Surfaces, Earth, Triangular Prism, Generating Points, Default Shading, Shading Flat, Shading Interp, 25 Arrays vs. Matrix Operations, 26 Dot Products, Example Calculating Center of Mass, Center of Gravity, 27 Matrix Multiplication and Division, Matrix Powers, Matrix Inverse, Determinatnts, Cross Products, 28 Applications of Matrix Operations, Solving Linear Equations, Linear Transformations, Eigenvectors 29 Engineering Application of Solving Systems of Linear Equations, Systems of Linear Equations, Kirchhoff's Circuit Laws, 30 Symbolic Differentiation, sym, syms, diff 31 Numerical Differentiation, fplot, Forward Difference, Backward Difference, Central Difference, 32 Numerical Integration, Engineering Applications, Integration, Trapezoid Rule, Simpson's Rule, 33 Monte Carlo Integration, 34 Introduction to ODE in System Biology 35 Introduction to System Biology, Gene Circuits, 36 Solving ODEs in Matlab, Repressilator, Programming steps 37 Interpolation, Cubic Spline Interpolation, Nearest Neighbor, Cubic, Two Dimensional, Three Dimensional, 38 Curve Fitting, Empirical Modelling, Linear Regression, Polynomial Regression, polyfit, polyval, Least Squres, 39 Introduction to Mathematica, 40 Programming in Mathematica 41 Basic Function in Mathematica, Strings, Characters, Polynomials, Solving Equations, Trigonometry, Calculus, 2D Ploting, Interactive Plots, Functions, Matlab vs. MAthematica 42 Numerical Data, Arthematic Operators, Data Types, Lists, Vectors, Matrices, String, Characters, 43 Mathematica Rule Based Programming, Functional Programming, 44 MAthematica Procedural Programming, Procedural Programs, Conditionals and Compositions, Looping Constructs, Errors, Modules, 45 Mathematica Predicates in Rule Based Programming, Patterns and Rules, Rules and Lists, Predicates, Blank, Blanksequence, BlackNullSequence, Number Puzzle, 46 Symbolic Mathematics and Programming, Rule Based Computation, Simplify, Expand, Solve, NSolve, Symbolic Visualisation, 47 Symbolic Computing in Matlab, Symbolic Algebra, sym, syms, Equations, Expressions, Systems of Equations, Calculus,
Views: 283 TO Courses
Charting Survey Results in Excel (Visualize Employee Satisfaction results)
 
10:38
Find out how you can visualize survey results in Excel. This is specially good if you have conducted an employee satisfaction survey and you'd like to present the results. Of course the chart can also be applied to any survey data that uses a Likert scale (which is based on people's attitudes or emotions to a topic). This can range from strongly disagree, disagree, neutral, agree and strongly agree. I show how you can create a stacked bar chart, as well as a diverging stacked bar chart as shown on Jon Peltier's website here (https://peltiertech.com/charting-survey-results/). Peltier Tech Chart Utility for Excel: https://peltiertech.com/Utility20/PeltierTechUtility.html Link to Custom Formatting Blog Post: https://www.xelplus.com/excel-custom-number-formatting_1/ ⯆ DOWNLOAD the workbook here: https://www.xelplus.com/charting-survey-results-excel/ ★ My Online Excel Courses ► https://courses.xelplus.com ✉ Subscribe & get my TOP 10 Excel formulas e-book for free https://www.xelplus.com/free-ebook/ EXCEL RESOURCES I Recommend: https://www.xelplus.com/resources/ Get Office 365: https://microsoft.msafflnk.net/15OEg Microsoft Surface: https://microsoft.msafflnk.net/c/1327040/451518/7593 GEAR Camera: https://amzn.to/2FLiFho Screen recorder: http://techsmith.pxf.io/c/1252781/347799/5161 Microphone: https://amzn.to/2DVKstA Lights: http://amzn.to/2eJKg1U More resources on my Amazon page: https://www.amazon.com/shop/leilagharani Note: This description contains affiliate links, which means at no additional cost to you, we will receive a small commission if you make a purchase using the links. This helps support the channel and allows us to continue to make videos like this. Thank you for your support! #MsExcel
Views: 13993 Leila Gharani
38| Curve Fitting in MATLAB - Data Analysis and Visualization
 
17:46
Data Analysis and Visualization is a Rich-full series Directed to all students interested in Analyzing and Visualizing Data using Excel, MATLAB and Wolfram Mathematica. This Course has been made by an expert prophesiers in University of Western Australia, and Contains the main flowing Topics: 1 Data Visualization in Excel 2 Array Formula in Excel 3 2D Array Formula in Excel 4 Excel Macros 5 Why Matlab 6 Problem Solving in MATLAB 7 MATLAB Orientation - Data Types and Expressions 8 MATLAB Scripts and Functions, Storing Instructions in Files, Getting Help on Build-in Functions 9 Matrices in MATLAB 10 MATLAB Scripts and Functions 11 Random Numbers, Gaussian Random Numbers, Complex Numbers 12 An Examples of Script and Function Files 13 Control Flow, Flow Chart, Relational Operators, Logical Operators, Truth Table, if clause, elseif, Nested if statments, Switch Structure, 14 MATLAB Loops, Nested Loops, Repetition, while, For, 15 Problems with Scripts, Workspace, Why Functions, How to Write a MATLAB Function, Anonymous Functions, 16 MATLAB Programs Input / Output, Escape Characters, Formatted Output, Syntax of Conversion Sequence, 17 Defensive Programming, error, warning, msg, isnumeric, ischar, nargin, nargout, nargchk, narginchk, all, 18 Cell Arrays, Array Types to Store data, Normal Arrays, Curly Brackets, Round Brackets, 19 MATLAB Structures, What is a Structure?, Adding a Field to a Structure, Struct Function, Manipulate the Fields, Preallocate Memory for a Structure Array 20 Basic 2D Plotting, title, xlabel, ylabel, grid, plot 21 Multiple Plots, figure, hold on, off, legend Function, String, Axis Scaling, Subplot, 22 Types of 2D Plots, Polar Plot, Logarithmic Plot, Bar Graphs, Pie Charts, Histograms, X-Y Graphs with 2 y Axes, Function Plots, 23 3D Plot, Line Plot, Surface Plot, Contour plots, Cylinder Plots, mesh, surf, contour, meshgrid, 24 Parametric Surfaces, Earth, Triangular Prism, Generating Points, Default Shading, Shading Flat, Shading Interp, 25 Arrays vs. Matrix Operations, 26 Dot Products, Example Calculating Center of Mass, Center of Gravity, 27 Matrix Multiplication and Division, Matrix Powers, Matrix Inverse, Determinatnts, Cross Products, 28 Applications of Matrix Operations, Solving Linear Equations, Linear Transformations, Eigenvectors 29 Engineering Application of Solving Systems of Linear Equations, Systems of Linear Equations, Kirchhoff's Circuit Laws, 30 Symbolic Differentiation, sym, syms, diff 31 Numerical Differentiation, fplot, Forward Difference, Backward Difference, Central Difference, 32 Numerical Integration, Engineering Applications, Integration, Trapezoid Rule, Simpson's Rule, 33 Monte Carlo Integration, 34 Introduction to ODE in System Biology 35 Introduction to System Biology, Gene Circuits, 36 Solving ODEs in Matlab, Repressilator, Programming steps 37 Interpolation, Cubic Spline Interpolation, Nearest Neighbor, Cubic, Two Dimensional, Three Dimensional, 38 Curve Fitting, Empirical Modelling, Linear Regression, Polynomial Regression, polyfit, polyval, Least Squres, 39 Introduction to Mathematica, 40 Programming in Mathematica 41 Basic Function in Mathematica, Strings, Characters, Polynomials, Solving Equations, Trigonometry, Calculus, 2D Ploting, Interactive Plots, Functions, Matlab vs. MAthematica 42 Numerical Data, Arthematic Operators, Data Types, Lists, Vectors, Matrices, String, Characters, 43 Mathematica Rule Based Programming, Functional Programming, 44 MAthematica Procedural Programming, Procedural Programs, Conditionals and Compositions, Looping Constructs, Errors, Modules, 45 Mathematica Predicates in Rule Based Programming, Patterns and Rules, Rules and Lists, Predicates, Blank, Blanksequence, BlackNullSequence, Number Puzzle, 46 Symbolic Mathematics and Programming, Rule Based Computation, Simplify, Expand, Solve, NSolve, Symbolic Visualisation, 47 Symbolic Computing in Matlab, Symbolic Algebra, sym, syms, Equations, Expressions, Systems of Equations, Calculus,
Views: 90 TO Courses
Highline Excel 2016 Class 15: Excel Charts to Visualize Data: Comprehensive Lesson 11 Chart Examples
 
52:27
Download Files: https://people.highline.edu/mgirvin/AllClasses/218_2016/218Excel2016.htm In this video learn about: (00:28) Define Charts. What do Charts do? (01:12) Effective Charts: No Chart Junk. Example of Chart Junk. (02:54) Types of Charts: 11 different chart types. (06:55) Terminology for Chart Elements: 1. (08:15) Column Charts 2. (12:15) Bar Charts 3. (13:41) Pie Charts 4. (14:25) Stacked Column Charts 5. (14:25) Clustered Column Charts 6. (17:44) Histogram. Two Examples: 1) Retail Sales Data Histogram with FREQUENCY Array Function. 2) Count Web Transactions by Hour with PivotTable. 7. (28:45) Line Charts. Time Series Chart. 8. (31:54) X-Y Scatter for Sample Data. 9. (34:45) Break Even Chart X-Y Scatter 10. (46:05) Combo Charts 11. (47:30) Bubble Chart (51:19) Summary
Views: 82626 ExcelIsFun
Analyzing & visualizing regional trends in Excel - Case study
 
11:19
In part 2 of our customer complaint data analysis case study, we analyze regional trends and visualize the results using sparklines, tables, 3D maps. Check out http://chandoo.org/wp/2016/02/18/analyzing-customer-complaints-2/ for full explanation & download workbooks.
33| MonteCarlo Integration in MATLAB - Data Analysis and Visualization
 
22:43
Data Analysis and Visualization is a Rich-full series Directed to all students interested in Analyzing and Visualizing Data using Excel, MATLAB and Wolfram Mathematica. This Course has been made by an expert prophesiers in University of Western Australia, and Contains the main flowing Topics: 1 Data Visualization in Excel 2 Array Formula in Excel 3 2D Array Formula in Excel 4 Excel Macros 5 Why Matlab 6 Problem Solving in MATLAB 7 MATLAB Orientation - Data Types and Expressions 8 MATLAB Scripts and Functions, Storing Instructions in Files, Getting Help on Build-in Functions 9 Matrices in MATLAB 10 MATLAB Scripts and Functions 11 Random Numbers, Gaussian Random Numbers, Complex Numbers 12 An Examples of Script and Function Files 13 Control Flow, Flow Chart, Relational Operators, Logical Operators, Truth Table, if clause, elseif, Nested if statments, Switch Structure, 14 MATLAB Loops, Nested Loops, Repetition, while, For, 15 Problems with Scripts, Workspace, Why Functions, How to Write a MATLAB Function, Anonymous Functions, 16 MATLAB Programs Input / Output, Escape Characters, Formatted Output, Syntax of Conversion Sequence, 17 Defensive Programming, error, warning, msg, isnumeric, ischar, nargin, nargout, nargchk, narginchk, all, 18 Cell Arrays, Array Types to Store data, Normal Arrays, Curly Brackets, Round Brackets, 19 MATLAB Structures, What is a Structure?, Adding a Field to a Structure, Struct Function, Manipulate the Fields, Preallocate Memory for a Structure Array 20 Basic 2D Plotting, title, xlabel, ylabel, grid, plot 21 Multiple Plots, figure, hold on, off, legend Function, String, Axis Scaling, Subplot, 22 Types of 2D Plots, Polar Plot, Logarithmic Plot, Bar Graphs, Pie Charts, Histograms, X-Y Graphs with 2 y Axes, Function Plots, 23 3D Plot, Line Plot, Surface Plot, Contour plots, Cylinder Plots, mesh, surf, contour, meshgrid, 24 Parametric Surfaces, Earth, Triangular Prism, Generating Points, Default Shading, Shading Flat, Shading Interp, 25 Arrays vs. Matrix Operations, 26 Dot Products, Example Calculating Center of Mass, Center of Gravity, 27 Matrix Multiplication and Division, Matrix Powers, Matrix Inverse, Determinatnts, Cross Products, 28 Applications of Matrix Operations, Solving Linear Equations, Linear Transformations, Eigenvectors 29 Engineering Application of Solving Systems of Linear Equations, Systems of Linear Equations, Kirchhoff's Circuit Laws, 30 Symbolic Differentiation, sym, syms, diff 31 Numerical Differentiation, fplot, Forward Difference, Backward Difference, Central Difference, 32 Numerical Integration, Engineering Applications, Integration, Trapezoid Rule, Simpson's Rule, 33 Monte Carlo Integration, 34 Introduction to ODE in System Biology 35 Introduction to System Biology, Gene Circuits, 36 Solving ODEs in Matlab, Repressilator, Programming steps 37 Interpolation, Cubic Spline Interpolation, Nearest Neighbor, Cubic, Two Dimensional, Three Dimensional, 38 Curve Fitting, Empirical Modelling, Linear Regression, Polynomial Regression, polyfit, polyval, Least Squres, 39 Introduction to Mathematica, 40 Programming in Mathematica 41 Basic Function in Mathematica, Strings, Characters, Polynomials, Solving Equations, Trigonometry, Calculus, 2D Ploting, Interactive Plots, Functions, Matlab vs. MAthematica 42 Numerical Data, Arthematic Operators, Data Types, Lists, Vectors, Matrices, String, Characters, 43 Mathematica Rule Based Programming, Functional Programming, 44 MAthematica Procedural Programming, Procedural Programs, Conditionals and Compositions, Looping Constructs, Errors, Modules, 45 Mathematica Predicates in Rule Based Programming, Patterns and Rules, Rules and Lists, Predicates, Blank, Blanksequence, BlackNullSequence, Number Puzzle, 46 Symbolic Mathematics and Programming, Rule Based Computation, Simplify, Expand, Solve, NSolve, Symbolic Visualisation, 47 Symbolic Computing in Matlab, Symbolic Algebra, sym, syms, Equations, Expressions, Systems of Equations, Calculus,
Views: 266 TO Courses
36| Solving ODEs in Matlab - Data Analysis and Visualization
 
28:49
Data Analysis and Visualization is a Rich-full series Directed to all students interested in Analyzing and Visualizing Data using Excel, MATLAB and Wolfram Mathematica. This Course has been made by an expert prophesiers in University of Western Australia, and Contains the main flowing Topics: 1 Data Visualization in Excel 2 Array Formula in Excel 3 2D Array Formula in Excel 4 Excel Macros 5 Why Matlab 6 Problem Solving in MATLAB 7 MATLAB Orientation - Data Types and Expressions 8 MATLAB Scripts and Functions, Storing Instructions in Files, Getting Help on Build-in Functions 9 Matrices in MATLAB 10 MATLAB Scripts and Functions 11 Random Numbers, Gaussian Random Numbers, Complex Numbers 12 An Examples of Script and Function Files 13 Control Flow, Flow Chart, Relational Operators, Logical Operators, Truth Table, if clause, elseif, Nested if statments, Switch Structure, 14 MATLAB Loops, Nested Loops, Repetition, while, For, 15 Problems with Scripts, Workspace, Why Functions, How to Write a MATLAB Function, Anonymous Functions, 16 MATLAB Programs Input / Output, Escape Characters, Formatted Output, Syntax of Conversion Sequence, 17 Defensive Programming, error, warning, msg, isnumeric, ischar, nargin, nargout, nargchk, narginchk, all, 18 Cell Arrays, Array Types to Store data, Normal Arrays, Curly Brackets, Round Brackets, 19 MATLAB Structures, What is a Structure?, Adding a Field to a Structure, Struct Function, Manipulate the Fields, Preallocate Memory for a Structure Array 20 Basic 2D Plotting, title, xlabel, ylabel, grid, plot 21 Multiple Plots, figure, hold on, off, legend Function, String, Axis Scaling, Subplot, 22 Types of 2D Plots, Polar Plot, Logarithmic Plot, Bar Graphs, Pie Charts, Histograms, X-Y Graphs with 2 y Axes, Function Plots, 23 3D Plot, Line Plot, Surface Plot, Contour plots, Cylinder Plots, mesh, surf, contour, meshgrid, 24 Parametric Surfaces, Earth, Triangular Prism, Generating Points, Default Shading, Shading Flat, Shading Interp, 25 Arrays vs. Matrix Operations, 26 Dot Products, Example Calculating Center of Mass, Center of Gravity, 27 Matrix Multiplication and Division, Matrix Powers, Matrix Inverse, Determinatnts, Cross Products, 28 Applications of Matrix Operations, Solving Linear Equations, Linear Transformations, Eigenvectors 29 Engineering Application of Solving Systems of Linear Equations, Systems of Linear Equations, Kirchhoff's Circuit Laws, 30 Symbolic Differentiation, sym, syms, diff 31 Numerical Differentiation, fplot, Forward Difference, Backward Difference, Central Difference, 32 Numerical Integration, Engineering Applications, Integration, Trapezoid Rule, Simpson's Rule, 33 Monte Carlo Integration, 34 Introduction to ODE in System Biology 35 Introduction to System Biology, Gene Circuits, 36 Solving ODEs in Matlab, Repressilator, Programming steps 37 Interpolation, Cubic Spline Interpolation, Nearest Neighbor, Cubic, Two Dimensional, Three Dimensional, 38 Curve Fitting, Empirical Modelling, Linear Regression, Polynomial Regression, polyfit, polyval, Least Squres, 39 Introduction to Mathematica, 40 Programming in Mathematica 41 Basic Function in Mathematica, Strings, Characters, Polynomials, Solving Equations, Trigonometry, Calculus, 2D Ploting, Interactive Plots, Functions, Matlab vs. MAthematica 42 Numerical Data, Arthematic Operators, Data Types, Lists, Vectors, Matrices, String, Characters, 43 Mathematica Rule Based Programming, Functional Programming, 44 MAthematica Procedural Programming, Procedural Programs, Conditionals and Compositions, Looping Constructs, Errors, Modules, 45 Mathematica Predicates in Rule Based Programming, Patterns and Rules, Rules and Lists, Predicates, Blank, Blanksequence, BlackNullSequence, Number Puzzle, 46 Symbolic Mathematics and Programming, Rule Based Computation, Simplify, Expand, Solve, NSolve, Symbolic Visualisation, 47 Symbolic Computing in Matlab, Symbolic Algebra, sym, syms, Equations, Expressions, Systems of Equations, Calculus,
Views: 56 TO Courses
Excel for Data Analysis and Visualization Microsoft on edX Course
 
00:32
Learn Excel in 6 Weeks Earn a verified certificate. Get started, sign up today. https://www.edx.org/course/excel-data-analysis-visualization-microsoft-dat206x About this course Microsoft Excel is one of the most widely used solutions for analyzing and visualizing data. Beginning with Excel 2010, new tools were introduced to enable the analysis of more data, resulting in less time spent creating and maintaining the solutions and enabling a better understanding of what the data means. This better understanding is facilitated by improved visualizations and more sophisticated business logics. Do you want to take your advanced Excel skills to the next level? Are you exploring new ways to get and transform your data and create visualization? Check out this practical new course, taught in short, lecture-based videos, complete with demos, quizzes, and hands-on labs, and skill up on many of the built-in business intelligence (BI) tools and features in Excel. ​Learn how to present the most relevant data with dynamic reports and presentations, as expert Dany Hoter walks you through all the important details. In this course, get an introduction to the latest versions of these new tools in Excel 2016. See how to import data from different sources, create mashups between data sources, and prepare the data for analysis. After preparing the data, learn about how business calculations—from simple to more advanced—can be expressed using the DAX calculation engine. And see how these different technologies work together inside Excel. Learn how the data can be visualized and shared to the Power BI cloud service, after which it can be used in dashboards, queried using plain English sentences, and consumed on mobile devices.
Views: 61 Bobby News Hub
Python for Data Analysis and Visualization | Webinar by Vinod Venkatraman | Hackerearth
 
01:06:57
About the webinar: Data analytics using Python's numpy, scikit, pandas modules Data Visualisation using Python's matplotlib module Big Data Analytics using PySpark with spark-core and mllib About the Speaker: The Speaker is Vinod Venkatraman. A passionate technology man of multiple talents, Vinod is spearheading the core technology initiatives at Great Learning. Be it a seamless user experience, the collection of thousands of critical user action data points daily or rolling out a great new feature, Vinod obsesses about it as fervently as he does create a new tune on his guitar. Vinod holds a B.Tech from IIT Bombay in Computer Science. He spent 7 years at Stratify Inc, a Silicon Valley-based product firm, to start his career, followed by 4 years at Flipkart, where he rose to be Software Architect. He now looks forward to leading the effort to build his own unicorn. Subscribe Our Channel For More Updates : https://goo.gl/suzeTB About us: HackerEarth is the most comprehensive developer assessment software that helps companies to accurately measure the skills of developers during the recruiting process. More than 500 companies across the globe use HackerEarth to improve the quality of their engineering hires and reduce the time spent by recruiters on screening candidates. Over the years, we have also built a thriving community of 2.5M+ developers that come to HackerEarth to participate in hackathons and coding challenges to assess their skills and compete in the community.
Views: 3177 HackerEarth
15| Matlab Functions - Data Analysis and Visualization
 
14:58
Data Analysis and Visualization is a Rich-full series Directed to all students interested in Analyzing and Visualizing Data using Excel, MATLAB and Wolfram Mathematica. This Course has been made by an expert prophesiers in University of Western Australia, and Contains the main flowing Topics: 1 Data Visualization in Excel 2 Array Formula in Excel 3 2D Array Formula in Excel 4 Excel Macros 5 Why Matlab 6 Problem Solving in MATLAB 7 MATLAB Orientation - Data Types and Expressions 8 MATLAB Scripts and Functions, Storing Instructions in Files, Getting Help on Build-in Functions 9 Matrices in MATLAB 10 MATLAB Scripts and Functions 11 Random Numbers, Gaussian Random Numbers, Complex Numbers 12 An Examples of Script and Function Files 13 Control Flow, Flow Chart, Relational Operators, Logical Operators, Truth Table, if clause, elseif, Nested if statments, Switch Structure, 14 MATLAB Loops, Nested Loops, Repetition, while, For, 15 Problems with Scripts, Workspace, Why Functions, How to Write a MATLAB Function, Anonymous Functions, 16 MATLAB Programs Input / Output, Escape Characters, Formatted Output, Syntax of Conversion Sequence, 17 Defensive Programming, error, warning, msg, isnumeric, ischar, nargin, nargout, nargchk, narginchk, all, 18 Cell Arrays, Array Types to Store data, Normal Arrays, Curly Brackets, Round Brackets, 19 MATLAB Structures, What is a Structure?, Adding a Field to a Structure, Struct Function, Manipulate the Fields, Preallocate Memory for a Structure Array 20 Basic 2D Plotting, title, xlabel, ylabel, grid, plot 21 Multiple Plots, figure, hold on, off, legend Function, String, Axis Scaling, Subplot, 22 Types of 2D Plots, Polar Plot, Logarithmic Plot, Bar Graphs, Pie Charts, Histograms, X-Y Graphs with 2 y Axes, Function Plots, 23 3D Plot, Line Plot, Surface Plot, Contour plots, Cylinder Plots, mesh, surf, contour, meshgrid, 24 Parametric Surfaces, Earth, Triangular Prism, Generating Points, Default Shading, Shading Flat, Shading Interp, 25 Arrays vs. Matrix Operations, 26 Dot Products, Example Calculating Center of Mass, Center of Gravity, 27 Matrix Multiplication and Division, Matrix Powers, Matrix Inverse, Determinatnts, Cross Products, 28 Applications of Matrix Operations, Solving Linear Equations, Linear Transformations, Eigenvectors 29 Engineering Application of Solving Systems of Linear Equations, Systems of Linear Equations, Kirchhoff's Circuit Laws, 30 Symbolic Differentiation, sym, syms, diff 31 Numerical Differentiation, fplot, Forward Difference, Backward Difference, Central Difference, 32 Numerical Integration, Engineering Applications, Integration, Trapezoid Rule, Simpson's Rule, 33 Monte Carlo Integration, 34 Introduction to ODE in System Biology 35 Introduction to System Biology, Gene Circuits, 36 Solving ODEs in Matlab, Repressilator, Programming steps 37 Interpolation, Cubic Spline Interpolation, Nearest Neighbor, Cubic, Two Dimensional, Three Dimensional, 38 Curve Fitting, Empirical Modelling, Linear Regression, Polynomial Regression, polyfit, polyval, Least Squres, 39 Introduction to Mathematica, 40 Programming in Mathematica 41 Basic Function in Mathematica, Strings, Characters, Polynomials, Solving Equations, Trigonometry, Calculus, 2D Ploting, Interactive Plots, Functions, Matlab vs. MAthematica 42 Numerical Data, Arthematic Operators, Data Types, Lists, Vectors, Matrices, String, Characters, 43 Mathematica Rule Based Programming, Functional Programming, 44 MAthematica Procedural Programming, Procedural Programs, Conditionals and Compositions, Looping Constructs, Errors, Modules, 45 Mathematica Predicates in Rule Based Programming, Patterns and Rules, Rules and Lists, Predicates, Blank, Blanksequence, BlackNullSequence, Number Puzzle, 46 Symbolic Mathematics and Programming, Rule Based Computation, Simplify, Expand, Solve, NSolve, Symbolic Visualisation, 47 Symbolic Computing in Matlab, Symbolic Algebra, sym, syms, Equations, Expressions, Systems of Equations, Calculus,
Views: 58 TO Courses
Introduction to Data Analysis using Excel | Microsoft on edX | Course About Video
 
01:48
Learn the basics of Excel, one of the most popular data analysis tools, to help visualize and gain insights from your data. Take this course free on edX: https://www.edx.org/course/introduction-data-analysis-using-excel-microsoft-dat205x#! ABOUT THIS COURSE The ability to analyze data is a powerful skill that helps you make better decisions. Microsoft Excel is one of the top tools for data analysis and the built-in pivot tables are arguably the most popular analytic tool. In this course, you will learn how to perform data analysis using Excel’s most popular features. You will learn how to create pivot tables from a range with rows and columns in Excel. You will see the power of Excel pivots in action and their ability to summarize data in flexible ways, enabling quick exploration of data and producing valuable insights from the accumulated data. Pivots are used in many different industries by millions of users who share the goal of reporting the performance of companies and organizations. In addition, Excel formulas can be used to aggregate data to create meaningful reports. To complement, pivot charts and slicers can be used together to visualize data and create easy to use dashboards. You don’t need any previous knowledge of Excel to take this course and you are welcome to use any supported version of Excel you have installed in your computer. After taking this course you’ll be ready to continue to our more advanced Excel course, Analyzing and Visualizing Data with Excel. WHAT YOU'LL LEARN - Create flexible data aggregations using pivot tables - Represent data visually using pivot charts - Calculate margins and other common ratios using calculation on pivot table - Filter data using slicers in multiple pivot tables - Create aggregate reports using formula based techniques
Views: 17210 edX
Data Analysis using MATLAB: Reading Excel File and visualizing the data interactively 1
 
18:58
This is an introduction to data analysis using MATLAB. This will be particularly useful for people interested in analysis of data for research purposes. We will see data import, visualization, statistics, writing data, reading data, basic simulation, image analysis...and so on. P.S: MATLAB is easy to learn and start with for those who are new to programming. For programs, write me at [email protected]
Views: 863 Utpal Kumar
11| Random and Complex Numbers - Data Analysis and Visualization
 
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Data Analysis and Visualization is a Rich-full series Directed to all students interested in Analyzing and Visualizing Data using Excel, MATLAB and Wolfram Mathematica. This Course has been made by an expert prophesiers in University of Western Australia, and Contains the main flowing Topics: 1 Data Visualization in Excel 2 Array Formula in Excel 3 2D Array Formula in Excel 4 Excel Macros 5 Why Matlab 6 Problem Solving in MATLAB 7 MATLAB Orientation - Data Types and Expressions 8 MATLAB Scripts and Functions, Storing Instructions in Files, Getting Help on Build-in Functions 9 Matrices in MATLAB 10 MATLAB Scripts and Functions 11 Random Numbers, Gaussian Random Numbers, Complex Numbers 12 An Examples of Script and Function Files 13 Control Flow, Flow Chart, Relational Operators, Logical Operators, Truth Table, if clause, elseif, Nested if statments, Switch Structure, 14 MATLAB Loops, Nested Loops, Repetition, while, For, 15 Problems with Scripts, Workspace, Why Functions, How to Write a MATLAB Function, Anonymous Functions, 16 MATLAB Programs Input / Output, Escape Characters, Formatted Output, Syntax of Conversion Sequence, 17 Defensive Programming, error, warning, msg, isnumeric, ischar, nargin, nargout, nargchk, narginchk, all, 18 Cell Arrays, Array Types to Store data, Normal Arrays, Curly Brackets, Round Brackets, 19 MATLAB Structures, What is a Structure?, Adding a Field to a Structure, Struct Function, Manipulate the Fields, Preallocate Memory for a Structure Array 20 Basic 2D Plotting, title, xlabel, ylabel, grid, plot 21 Multiple Plots, figure, hold on, off, legend Function, String, Axis Scaling, Subplot, 22 Types of 2D Plots, Polar Plot, Logarithmic Plot, Bar Graphs, Pie Charts, Histograms, X-Y Graphs with 2 y Axes, Function Plots, 23 3D Plot, Line Plot, Surface Plot, Contour plots, Cylinder Plots, mesh, surf, contour, meshgrid, 24 Parametric Surfaces, Earth, Triangular Prism, Generating Points, Default Shading, Shading Flat, Shading Interp, 25 Arrays vs. Matrix Operations, 26 Dot Products, Example Calculating Center of Mass, Center of Gravity, 27 Matrix Multiplication and Division, Matrix Powers, Matrix Inverse, Determinatnts, Cross Products, 28 Applications of Matrix Operations, Solving Linear Equations, Linear Transformations, Eigenvectors 29 Engineering Application of Solving Systems of Linear Equations, Systems of Linear Equations, Kirchhoff's Circuit Laws, 30 Symbolic Differentiation, sym, syms, diff 31 Numerical Differentiation, fplot, Forward Difference, Backward Difference, Central Difference, 32 Numerical Integration, Engineering Applications, Integration, Trapezoid Rule, Simpson's Rule, 33 Monte Carlo Integration, 34 Introduction to ODE in System Biology 35 Introduction to System Biology, Gene Circuits, 36 Solving ODEs in Matlab, Repressilator, Programming steps 37 Interpolation, Cubic Spline Interpolation, Nearest Neighbor, Cubic, Two Dimensional, Three Dimensional, 38 Curve Fitting, Empirical Modelling, Linear Regression, Polynomial Regression, polyfit, polyval, Least Squres, 39 Introduction to Mathematica, 40 Programming in Mathematica 41 Basic Function in Mathematica, Strings, Characters, Polynomials, Solving Equations, Trigonometry, Calculus, 2D Ploting, Interactive Plots, Functions, Matlab vs. MAthematica 42 Numerical Data, Arthematic Operators, Data Types, Lists, Vectors, Matrices, String, Characters, 43 Mathematica Rule Based Programming, Functional Programming, 44 MAthematica Procedural Programming, Procedural Programs, Conditionals and Compositions, Looping Constructs, Errors, Modules, 45 Mathematica Predicates in Rule Based Programming, Patterns and Rules, Rules and Lists, Predicates, Blank, Blanksequence, BlackNullSequence, Number Puzzle, 46 Symbolic Mathematics and Programming, Rule Based Computation, Simplify, Expand, Solve, NSolve, Symbolic Visualisation, 47 Symbolic Computing in Matlab, Symbolic Algebra, sym, syms, Equations, Expressions, Systems of Equations, Calculus,
Views: 86 TO Courses
Basic Excel Business Analytics #14: Logical Formulas & Conditional Formatting to Visualizing Data
 
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Download file from “Highline BI 348 Class” section: https://people.highline.edu/mgirvin/excelisfun.htm Review how to use Logical Formulas to add Conditional Formatting to Data Sets: 1) (00:11) Introduction 2) (00:33) Built-in Feature: Conditionally Format Budget Data when Actual Exceeds Budgeted Amounts. 3) (02:26) Logical Formula & Mixed Cell References to Format Row: Conditionally Format Budget Data when Actual Exceeds Budgeted Amounts: 4) (05:24) Cell Chart with Data Bars: Conditionally Format Budget Data when Actual Exceeds Budgeted Amounts: 5) (07:29) AND Function and Mixed Cell References to Conditionally Format Records that math two Criteria. Download Excel File Not: After clicking on link, Use Ctrl + F (Find) and search for “Highline BI 348 Class” or for the file name as seen at the beginning of the video.
Views: 13314 ExcelIsFun
How to Create Dashboard in Excel ☑️
 
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Download Link http://bit.ly/2H1GsYR New to Excel dashboards? Learn how to create dashboard in Excel to improve your Excel, data analysis and data visualization skills. You can make dashboard in excel in under 5 minutes after watching this video without any additional software of plugin. Download this excel dashboard template for free from my website http://www.myelesson.org/excel-training-videos/create-excel-dashboard to make excel dashboard and reports for yourself. 10 Most Used Formulas MS Excel https://www.youtube.com/watch?v=KyMj8HEBNAk Learn Basic Excel Skills For Beginners || Part 1 https://www.youtube.com/watch?v=3kNEv3s8TuA 10 Most Used Excel Formula https://www.youtube.com/watch?v=2t3FDi98GBk **Most Imporant Excel Formuls Tutorials** Learn Vlookup Formula For Beginners in Excel https://www.youtube.com/watch?v=vomClevScJQ 5 Excel Questions Asked in Job Interviews https://www.youtube.com/watch?v=7Iwx4AMdij8 Create Speedometer Chart In Excel https://www.youtube.com/watch?v=f6c93-fQlCs Learn the Basic of Excel for Beginners || Part 2 https://www.youtube.com/watch?v=qeMSV9T1PoI Create Pareto Chart In Excel https://www.youtube.com/watch?v=2UdajrDMjRE How to Create Dashboard in Excel https://www.youtube.com/watch?v=RM8T1eYBjQY Excel Interview Questions & Answers https://www.youtube.com/watch?v=Zjv1If63nGU To watch more videos and download the files visit http://www.myelesson.org To Buy The Full Excel Course visit . http://www.myelesson.org/product or call 9752003788 Connect with us on Facebook - https://www.facebook.com/excelmadeasy/ Connect with us on Twitter - https://twitter.com/Excelmadeasy 10 Most Used Formulas MS Excel https://www.youtube.com/watch?v=KyMj8HEBNAk Learn Basic Excel Skills For Beginners || Part 1 https://www.youtube.com/watch?v=3kNEv3s8TuA 10 Most Used Excel Formula https://www.youtube.com/watch?v=2t3FDi98GBk **Most Imporant Excel Formuls Tutorials** Learn Vlookup Formula For Beginners in Excel https://www.youtube.com/watch?v=vomClevScJQ 5 Excel Questions Asked in Job Interviews https://www.youtube.com/watch?v=7Iwx4AMdij8 Create Speedometer Chart In Excel https://www.youtube.com/watch?v=f6c93-fQlCs Learn the Basic of Excel for Beginners || Part 2 https://www.youtube.com/watch?v=qeMSV9T1PoI Create Pareto Chart In Excel https://www.youtube.com/watch?v=2UdajrDMjRE How to Create Dashboard in Excel https://www.youtube.com/watch?v=RM8T1eYBjQY Excel Interview Questions & Answers https://www.youtube.com/watch?v=Zjv1If63nGU
Views: 455622 My E-Lesson
5 Excel 2016 Tips Learn how to Visualize Data Using Charts
 
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Learn how Visualize to Visualize Data in Excel 2016 with these 5 amazing Visualization Tips. In this tutorial our Excel instructor will have you teach you how to use Microsoft Excel 2016 to visualize your data using excel charts. Please subscribe to your Youtube Channel today!
Views: 5459 Learn iT! Training