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If you work with data, you know that Excel is one of the most popular and powerful tools at your disposal. Depending on your industry or field, you may also use Python for data analysis, forecasting, running machine learning models, and more. For many people who deal with data, its common to use both tools in the same workflow, and moving your data between the two can be a hassle. Good news! In the new public preview of Excel, you can now use Python directly in Excel, eliminating the need to move your data between the tools. In this course, Scott Simpson explores the Python features launched in the public preview, showing you how to manage your entire data workflow directly inside an Excel worksheet. Join Scott to learn about exciting and powerful features—referencing Excel values in Python, using pandas to analyze data in an Excel worksheet, using Python plotting modules, and more—and see how you can leverage the power of Python in your Excel sheets to gain insights from your data.
If you work with data, you know that Excel is one of the most popular and powerful tools at your disposal. Depending on your industry or field, you may also use Python for data analysis, forecasting, running machine learning models, and more. For many people who deal with data, its common to use both tools in the same workflow, and moving your data between the two can be a hassle. Good news! In the new public preview of Excel, you can now use Python directly in Excel, eliminating the need to move your data between the tools. In this course, Scott Simpson explores the Python features launched in the public preview, showing you how to manage your entire data workflow directly inside an Excel worksheet. Join Scott to learn about exciting and powerful features—referencing Excel values in Python, using pandas to analyze data in an Excel worksheet, using Python plotting modules, and more—and see how you can leverage the power of Python in your Excel sheets to gain insights from your data.
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📖 100+ DSA Interview Questions for Cracking FAANG with Animated Examples for Deeper Understanding and Faster Learning
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01 - Introduction.zip
114.4 MB
01 - Introduction
02 - Recursion.zip
231.8 MB
02 - Recursion
03 - Cracking Recursion Interview Questions.zip
154 MB
03 - Cracking Recursion Interview Questions
04 - Bonus CHALLENGING Recursion Problems.zip
5.4 KB
04 - Bonus CHALLENGING Recursion Problems
05 - Big O Notation.zip
218.9 MB
05 - Big O Notation
06 - Top Big O Interview Questions.zip
85.1 MB
06 - Top Big O Interview Questions
07 - Arrays - Part 01.zip
367.3 MB
07 - Arrays - Part 01
07 - Arrays - Part 02.zip
212.5 MB
07 - Arrays - Part 02
08 - Python Lists.zip
321.1 MB
08 - Python Lists
09 - PROJECT - ArraysLists.zip
53.3 MB
09 - PROJECT - ArraysLists
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10 - Cracking ArrayList Interview Questions.zip
162.7 MB
10 - Cracking ArrayList Interview Questions
11 - Dictionaries.zip
316.1 MB
11 - Dictionaries
12 - Tuples.zip
154.4 MB
12 - Tuples
13 - Linked List - Part 01.zip
374.9 MB
13 - Linked List - Part 01
13 - Linked List - Part 02.zip
60.6 MB
13 - Linked List - Part 02
14 - Circular Singly Linked List.zip
325.7 MB
14 - Circular Singly Linked List
15 - Doubly Linked List.zip
341 MB
15 - Doubly Linked List
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16 - Circular Doubly Linked List - Part 01.zip
363.7 MB
16 - Circular Doubly Linked List - Part 01
16 - Circular Doubly Linked List - Part 02.zip
57.4 MB
16 - Circular Doubly Linked List - Part 02
17 - Cracking Linked List Interview Questions.zip
275.7 MB
17 - Cracking Linked List Interview Questions
18 - Stack.zip
212.7 MB
18 - Stack
19 - Queue - Part 01.zip
387.6 MB
19 - Queue - Part 01
19 - Queue - Part 02.zip
8.9 MB
19 - Queue - Part 02
20 - Cracking Stack and Queue Interview Questions.zip
219.2 MB
20 - Cracking Stack and Queue Interview Questions
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