Excel with Python: Performing Advanced Operations
Python 3.7
17 Videos | 1h 37m 3s - Includes Assessment
- Earns a Badge
Learners can explore complex operations in Microsoft Excel workbooks, including the use of conditional formatting, named ranges, and merged cells, in this 17-video course. Microsoft Excel is the best prototyping tool for data analysis, an interactive functional programming environment, and a forerunner of Python. Begin by exploring how Python and its ecosystem of libraries are fast emerging as a popular choice for easy spreadsheet automation. Then observe the formatting, alignment, and other aesthetics in Python. You will work with the Python library openpyxl; examine data analysis, the use of pivot tables, and the locking of cell references by using the $ operator; and learn how to perform complex data analysis operations using pivot tables, sorting and filtering, and formulae with both absolute and relative cell references to enable efficient copy paste. You will learn to control the workbook appearance using conditional formatting and styles. Finally, this course demonstrates how to leverage the Python Pandas library to read a spreadsheet, to group and analyze data.
WHAT YOU WILL LEARN
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discover the key concepts covered in this course
apply styling elements to control the display of data in cells
apply sophisticated styles and alignments to format cell contents
use number formats to represent currencies and add comma separators
apply formatting that varies based on the value contained in a cell
choose from different in-built icon sets and rules to control cell formatting at a granular level
insert images into Microsoft Excel files and control their size and location
insert formulae into Excel workbooks
use openpyxl to programmatically construct formulae in workbooks -
use the $ operator to convert relative cell references into absolute ones
use openpyxl to construct both absolute and relative cell references
use VLOOKUP to lookup specific values from a range in Excel
assign names to groups of cells and use those names in formulae to enhance readability
use Excel pivot tables to dynamically analyze and group data
use Pandas to read data from Microsoft Excel and perform pivoting operations
use Pandas to perform multi-level indexing and access individual row values as well as index values
summarize the key concepts in this course
IN THIS COURSE
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1.Course Overview2m 12sUP NEXT
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2.Working with Fonts and Styles6m 57s
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3.Working with Borders and Colors5m 9s
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4.Applying Number Formats8m 4s
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5.Applying Conditional Formatting4m 31s
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6.Using Advanced Conditional Formatting4m 49s
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7.Working with Images3m 5s
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8.Working with Formulae6m 56s
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9.More Operations Using Formulae3m 29s
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10.Using Absolute and Relative Cell References5m 52s
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11.Programmatically Constructing Absolute References5m 28s
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12.Using VLOOKUP6m 46s
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13.Working with Named Ranges6m 8s
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14.Working with Pivot Tables5m 42s
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15.Using Pandas for Pivoting7m 48s
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16.Leveraging Multi-level Indexing in Pandas5m 10s
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17.Course Summary1m 27s
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