Though more complicated as it requires programming knowledge, Python allows you to perform any manipulation, transformation, and visualization of your data. It is ideal for data scientists.

This is a collection of my personal notes for Data Visualization in Python. Originally I had kept these in a collection of Jupyter notebooks, but it will be much more useful to just put them online so ...

where data visualization is often used for market analysis, technical charting, and other mission-critical business scenarios. In this project, we will create an interactive stock visualization ...

how we effectively represent data using channels like color, size, and position, and some ground rules for honest and effective visualization. You will also gain preliminary exposure to Altair, a ...

Employ data manipulation libraries like pandas in Python or dplyr in R to preprocess and clean large datasets before visualization. Consider using data streaming techniques for real-time data ...

Excel users can now use Python’s advanced capabilities for data manipulation, statistical analysis, and data visualization without leaving their familiar spreadsheet environment. This opens up new ...

Microsoft's Stefan Kinnestrand, writing about “the best of both worlds for data analysis and visualization,” writes that this public preview of Python in Excel will allow spreadsheet tinkerers ...