Python-bloggers

As an Excel analyst, you’ve probably had moments where your data seemed to show clear trends,profits rising, sales dropping, or costs climbing steadily. But sometimes, these apparent patterns might actually be random,tricking you into thinking there’s more control and predictability than there really is. That’s ...

Numbers don’t spread out evenly across digits. In many real datasets, the leading digit “1” shows up about 30% of the time while “9” hardly appears. That’s Benford’s Law. If your numbers don’t follow this pattern when they should, it could mean something odd or even fraudulent is going ...

... but it's nearly impossible. Could anybody guess why? Hint in the links below.

Understanding who your most influential customers are—those who consistently recommend your business—is essential for sustainable, cost-effective growth. This approach, called social influencer analysis, identifies customers who act as connectors and referral hubs within your customer base. Historically, performing this type of analysis required complex Excel formulas or specialized ...

Turning raw latitude and longitude coordinates into meaningful addresses is a foundational step in any geospatial analysis. This article evaluates the ten best reverse geocoding APIs designed for data science workflows, comparing them on accuracy, performance, Python integration, and pricing to help you find the perfect tool for enriching your ...

ARIMA (short for AutoRegressive Integrated Moving Average) is a classic statistical model for time series forecasting. It works by combining three elements: autoregression (using past values to predict future ones), integration (removing trends to make data stationary), and moving averages (capturing patterns in forecast errors). For analysts, it’s valuable ...