Modules is one of the best feature of Python. Except some core modules, you can install what you need and keep your Python setup smooth.
Python’s datetime module handles date and time operations through five core classes. The datetime.datetime class represents a specific point in time with year, month, day, hour, minute, second, and microsecond precision. The date class stores calendar dates without time information.…
The pandas groupby method implements the split-apply-combine pattern, a fundamental data analysis technique that divides your dataset into groups, applies functions to each group independently, and merges the results into a unified output. This approach mirrors SQL’s GROUP BY functionality…
Syntax: Example: The np.arange() function generates arrays with evenly spaced values within a specified interval. This NumPy function returns a one-dimensional ndarray containing sequential values based on the parameters you provide. Understanding np.arange parameters The np.arange() method accepts up to…
The np.linspace function generates evenly spaced numbers across a defined interval. You specify where to start, where to stop, and how many values you want. NumPy calculates the spacing automatically. Basic syntax for np.linspace The function accepts several parameters that…
Large Language Models(LLMs) have been in the tech news for quite some time and every day, we learn about new advancements in this field. These models are being used in finance, management, content creation, and analysis. While these perform well…
That single line reads your CSV file and automatically detects the header row. Pandas assumes the first row contains column names by default, which is exactly what you want 99% of the time. But let me show you what’s actually…
Syntax: Quick example: That’s Python np where in action. You give it a condition, tell it what to return when True, what to return when False, and it runs that logic across your entire array without loops. What Python np…
Sklearn’s LogisticRegression is great for pure prediction tasks, but when I want p-values, confidence intervals, and detailed statistical tests, I reach for Statsmodels instead. The library gives you two main options for binary classification: Logit and Probit. Both model the…
Linear mixed effects models solve a specific problem we’ve all encountered repeatedly in data analysis: what happens when your observations aren’t truly independent? I’m talking about situations where you have grouped or clustered data. Students nested within schools. Patients are…
You’re running a regression on your sales data, and a few extreme values are throwing off your predictions. Maybe it’s a single huge order, or data entry errors, or legitimate edge cases you can’t just delete. Standard linear regression treats…