Data science uses mathematics to analyze data, distill information, and tell a story. The result of data science may be just to rigorously confirm a hypothesis, or to discover some useful property from the data. There are many tools you can use in data science, from basic statistics to sophisticated machine learning models. Even the […]
The path to uncovering meaningful insights often starts with a single step: looking at the data before asking questions. This journey through the Ames Housing dataset is more than an exploration; it’s a narrative about the hidden stories within numbers, waiting to be told. Through a “Data First Approach,” we invite you to dive deep […]
Data Science embodies a delicate balance between the art of visual storytelling, the precision of statistical analysis, and the foundational bedrock of data preparation, transformation, and analysis. The intersection of these domains is where true data alchemy happens – transforming and interpreting data to tell compelling stories that drive decision-making and knowledge discovery. Just as […]
The real estate industry is a vast network of stakeholders including agents, homeowners, investors, developers, municipal planners, and tech innovators, each bringing unique perspectives and objectives to the table. Within this intricate ecosystem, data emerges as the critical element that binds these diverse interests together, facilitating collaboration and innovation. PropTech, or Property Technology, illustrates this […]
Data transformations enable data scientists to refine, normalize, and standardize raw data into a format ripe for analysis. These transformations are not merely procedural steps; they are essential in mitigating biases, handling skewed distributions, and enhancing the robustness of statistical models. This chapter will primarily focus on how to address skewed data. By focusing on […]
In a data science project, the data you collect is often not in the shape that you want it to be. Often you will need to create derived features, aggregate subsets of data into a summarized form, or select a portion of the data according to some complex logic. This is not a hypothetical situation. […]
In data analysis, SQL stands as a mighty tool, renowned for its robust capabilities in managing and querying databases. The pandas library in Python brings SQL-like functionalities to data scientists, enabling sophisticated data manipulation and analysis without the need for a traditional SQL database. In the following, you will apply SQL-like functions in Python to […]
Outliers are unique in that they often don’t play by the rules. These data points, which significantly differ from the rest, can skew your analyses and make your predictive models less accurate. Although detecting outliers is critical, there is no universally agreed-upon method for doing so. While some advanced techniques like machine learning offer solutions, […]
In the world of real estate, numerous factors influence property prices. The economy, market demand, location, and even the year a property is sold can play significant roles. The years 2007 to 2009 marked a tumultuous time for the US housing market. This period, often referred to as the Great Recession, saw a drastic decline […]
The chi-squared test for independence is a statistical procedure employed to assess the relationship between two categorical variables—determining whether they are correlated or independent. The exploration of the visual appeal of a property and its impact on its valuation is intriguing. But how often do you associate the outlook of a house with functional features […]
