Excel with Python: Constructing Data Visualizations

Excel with Python: Constructing Data Visualizations

• discover the key concepts covered in this course
• use Microsoft Excel to visualize data
• use openpyxl to construct visualizations in Excel workbooks
• tweak the title, formatting, and legend of a graph
• alter the data displayed on the axes of a graph
• alter the weight and line style of data series to customize the appearance of a visualization
• construct and modify bar chart visualizations in Excel
• use openpyxl to build different types of bar charts programmatically
• plot financial data containing open, high, low, close, and volume information about stock prices
• use bubble charts to represent three dimensions of data in a two dimensional visualization
• summarize the key concepts in this course

Discover how to use of the powerful openpyxl library in building visualizations such as line, bar, and bubble charts in Excel. Explore the use of stock charts to display financial information is covered as well.

Excel with Python: Performing Advanced Operations

Excel with Python: Performing Advanced Operations

• 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

Discover more complex operations on Excel workbooks including the use of conditional formatting, named ranges, and merged cells. Explore data analysis and the use of pivot tables, as well as the locking of cell references using the $ operator are covered as well.

Excel with Python: Working with Excel Spreadsheets from Python

Excel with Python: Working with Excel Spreadsheets from Python

• discover the key concepts covered in this course
• create a Microsoft Excel workbook by choosing from a list of templates
• create a Microsoft Excel workbook using the openpyxl library
• access individual cells programmatically using openpyxl
• access entire rows and columns and manipulate them programmatically
• save the contents of an in-memory representation to a Microsoft Excel file on disk
• use lists and other Python containers to read to and write from Excel files
• specify rows and columns that always ought to be on-screen as a user browses an Excel file
• filter data in a range based on various attributes
• sort data in a range using different columns and sort criteria
• customize the size of rows and columns to enhance readability
• merge and unmerge groups of cells
• summarize the key concepts covered in this course

Explore how Microsoft Excel spreadsheets can be created, opened, and modified programmatically from within Python. Discover how the powerful openpyxl library can be used to manipulate Excel's object model programmatically from within Python.