Description:
This course explores how to use Python's openpyxl library to build visualizations such as line, bar, and bubble charts in Excel. In its 11 videos, you will examine how Python and its ecosystem of libraries are fast emerging as a popular choice for easy spreadsheet automation, before learning how to create line and bar charts in Excel, and learning how to use Python to control several properties of those charts, including line weights and style, data for the reference axes, formatting, and the position of ticks on those axes. Learners will observe how to construct data visualizations in Excel using Python. This course then demonstrates common types of visualizations that are supported in Excel, and how to programmatically replicate those visualizations from within Python. Finally, learners will observe demonstrations of the use of bubble charts to display three dimensions on a two-dimensional chart as well as stock charts to represent the opening, high, low, and closing prices of stocks in a single data visualization for the financial markets.
Target Audience:
Duration: 01:01
Description:
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.
Target Audience:
Duration: 01:30
Description:
This 13-video course explores how Microsoft Excel spreadsheets can be created, opened, and modified programmatically from within Python. Learners will review the Microsoft Excel object model, the attributes of the worksheet cell object which can be leveraged to create and modify workbooks programmatically. First, you will review VBA (Visual Basic for Applications) technology, before exploring how Python and its ecosystem of libraries are fast emerging as a popular choice for easy spreadsheet automation. Then you will learn how to use openpyxl (open pixel library) to manipulate Excel's object model programmatically from within Python. Continue by learning how to write spreadsheets by using openpyxl, and examining how existing Excel workbooks can be opened, as well as how new spreadsheet files can be created, and written out to disk. Finally, you will learn how Python iterators and indexing can be used to access and manipulate individual cells, ranges consisting of many cells, as well as entire rows and columns.
Target Audience:
Duration: 01:17