Hidden Python libraries can make data analysis faster and easier for large datasets. Tools like Polars, Dask, and Sweetviz simplify data cleaning, modeling, and visualization. Learning new Python ...

Abstract: With the flourishment of 3D content, stereoscopic image quality assessment (SIQA) becomes an urgent issue in image processing field. In this paper, a new blind SIQA method is proposed based ...

In today’s data-rich environment, business are always looking for a way to capitalize on available data for new insights and increased efficiencies. Given the escalating volumes of data and the ...

If you’re new to Python, one of the first things you’ll encounter is variables and data types. Understanding how Python handles data is essential for writing clean, efficient, and bug-free programs.

What if the tools you already use could do more than you ever imagined? Picture this: you’re working on a massive dataset in Excel, trying to make sense of endless rows and columns. It’s slow, ...

ABSTRACT: This paper proposes a universal framework for constructing bivariate stochastic processes, going beyond the limitations of copulas and offering a potentially simpler alternative. The ...

If you’ve ever found yourself staring at a messy spreadsheet of survey data, wondering how to make sense of it all, you’re not alone. From split headers to inconsistent blanks, the challenges of ...

Microsoft's integration of Python into Excel, slated for release in Q3 2024, is a major advance for financial data professionals using Excel as their core analysis tool. This powerful combination ...