Data Science 101: Python Plus Excel - Printable Version +- Softwarez.Info - Software's World! (https://softwarez.info) +-- Forum: Library Zone (https://softwarez.info/Forum-Library-Zone) +--- Forum: Video Tutorials (https://softwarez.info/Forum-Video-Tutorials) +--- Thread: Data Science 101: Python Plus Excel (/Thread-Data-Science-101-Python-Plus-Excel--65197) |
Data Science 101: Python Plus Excel - BaDshaH - 05-28-2023 Published 5/2023 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz Language: English | Size: 3.56 GB | Duration: 8h 15m Learn excel and python with real world case study. [b]What you'll learn[/b] Write excel advanced conditional, text, and lookup functions Excel automation using python Learn Microsoft Excel 2016 and many of its advanced features Learn data science skills using Python and Excel Excel features using numpy and pandas Visualization using Excel and Python [b]Requirements[/b] Python basics (data types, loops, functions etc.) Install Microsoft 2016, 2013 or 2010 [b]Description[/b] For many years, and for good reason, Excel has been a staple for working professionals. It is essential in all facets of business, education, finance, and research due to its extensive capabilities and simplicity of use.Over the past few years, python programming language has become more popular. According to one study, the demand for Python expertise has grown by 27.6 % over the past year and shows no indications of slowing down. Python has been a pioneer in web development, data analysis, and infrastructure management since it was first developed as a tool to construct scripts that "automate the boring stuff."Why python is important for automation?Consider being required to create accounts on a website for 10,000 employees. What do you think? Performing this operation manually and frequently will eventually drive you crazy. It will also take too long, which is not a good idea.Try to consider what it's like for data entry workers. They take the data from tables (like those in Excel or Google Sheets) and insert it elsewhere.They read various magazines and websites, get the data there, and then enter it into the database. Additionally, they must perform the calculations for the entries.In general, this job's performance determines how much money is made. Greater entry volume, more pay (of course, everyone wants a higher salary in their job).However, don't you find doing the same thing over and over boring?The question is now, "How can I accomplish it quickly?"How to automate my work?Spend an hour coding and automating these kinds of chores to make your life simpler rather than performing these kinds of things by hand. By just writing fewer lines of Python code, you can automate your strenuous activity.The course covers following topics:1. Excel basics2. Excel Functions3. Excel Visualizations4. Excel Case study (Financial Statements)5. Python numpy and pandas6. Python Implementations of Excel functions7. Python matplotlib and pandas visualizationsThe evidence suggests that both Excel and Python have their place with certain applications. Excel is a great entry-level tool and is a quick-and-easy way to analyze a dataset.But for the modern era, with large datasets and more complex analytics and automation, Python provides the tools, techniques and processing power that Excel, in many instances, lacks. After all, Python is more powerful, faster, capable of better data analysis and it benefits from a more inclusive, collaborative support system.Python is a must-have skill for aspiring data analysts, data scientist and anyone in the field of science, and now is the time to learn. Overview Section 1: Introduction Lecture 1 Introduction Lecture 2 Python vs Excel Lecture 3 Limitation of Excel Lecture 4 Python Lecture 5 who can benefit from learning Python? Lecture 6 What makes Python a better option than Excel? Lecture 7 Excel vs Python: Who wins? Section 2: Download Resources for Excel[IMPORTANT] Lecture 8 Download Excel Lecture content! Section 3: Introduction to Basics of Excel Lecture 9 Structure of Excel sheets Lecture 10 The Ribbon Lecture 11 Rows and Columns Lecture 12 Enter, Edit, Delete in Excel Lecture 13 Excel basic formatting: border, font, color Lecture 14 Align Left, Right, Center Lecture 15 Arithmetic operations Lecture 16 Excel formulas introduction Lecture 17 Copy and Paste Lecture 18 Formatting cell Lecture 19 Formatting worksheet Lecture 20 Moving and selecting contents in Excel sheets Lecture 21[IMPORTANT] Fixing cell references Lecture 22 ALT+ENTER Lecture 23 Text to Column Lecture 24 Wrap Text Lecture 25 Select special Lecture 26 Dynamic Naming Lecture 27 Custom Formatting 1 Lecture 28 Custom Formatting 2 Lecture 29 Multiple Formats Section 4: Excel Tools and Tips Lecture 30 Macros Lecture 31 Data Validation Lecture 32 Sort and Filter Lecture 33 Hyperlinks Lecture 34 Freeze Panes Lecture 35 Tell me what you want to do Lecture 36 Keyboard Shortcuts Section 5: Excel Functions Lecture 37 Count, countif and countifs Lecture 38 Sum, sumif and sumifs Lecture 39 average and averageif Lecture 40 Text functions Lecture 41 max and min functions Lecture 42 round function Lecture 43 vlookup function[IMPORTANT} Lecture 44 hlookup function Lecture 45 index and match function Lecture 46 iferror function Lecture 47 pivot tables Lecture 48 data tables Section 6: Excel Visualizations Lecture 49 Excel charts Lecture 50 Basic formatting for charts Lecture 51 Designing charts Lecture 52 Bridge charts Lecture 53 Treemap Lecture 54 Spark Lines Section 7: Excel Case Study Lecture 55 Introduction to data Lecture 56 Preprocessing data Lecture 57 Create unique code (primary key) Lecture 58 Creating database Lecture 59 Populate database 1 Lecture 60 Populate database 2 Lecture 61 Mapping each row to category Lecture 62 Income statement Lecture 63 Format statement Lecture 64 Format statement more Lecture 65 Populate Income (P&L) statement Section 8: Excel Functions in Python Lecture 66 vlookup function in excel Lecture 67 Implement vlookup functionality in Python Lecture 68 Pivot tables in excel Lecture 69 Implement pivot tables functionality in Python Lecture 70 Pivot tables using pandas Lecture 71 IF function in Excel Lecture 72 IF functionalities in python Lecture 73 Text manipulation in Excel Lecture 74 Text manipulation in Python Lecture 75 count, countif, countifs, sum, sumif, sumifs Lecture 76 count, countif, countifs, sum, sumif, sumifs in Python Section 9: Python Visualizations Lecture 77 pivot charts in Excel Lecture 78 Python pandas visualization Lecture 79 Matplotlib Lecture 80 Formatting charts Lecture 81 More on matplotlib Lecture 82 matplotlib and pandas together Excel users curious about automating their work using python,Python Developer wanting career switch in Data Science Homepage Download From Rapidgator Download From FileRice Download From Nitroflare |