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Confusion matrix, precision, and recall
A model is only as trustworthy as your ability to judge it. Every prediction falls into one of four...
Handling missing data and validating input
In pandas the everyday moves are to detect, then deliberately decide: python...
Matrices: indexing, row and column sums
Real data is usually two-dimensional: a grid of rows and columns. A spreadsheet, a feature table, a...
Every metric is an estimate; confidence intervals
Every metric is an estimate from a finite sample, and real decisions hinge on whether a difference...
Why look first, and the figure/axes model
Exploratory data analysis (EDA) is the habit of plotting before modelling, because a picture...
Choosing charts and headless plotting
Four charts do most of the everyday work, and each answers a different question: - a histogram...
Print, input, and turning text into numbers
Python is the language most data scientists reach for first, and like any language you begin by...
Transpose and the ragged-row pitfalls
A close cousin of column iteration is the transpose , which turns rows into columns by swapping the...
Type hints and a numeric helper
As projects grow, functions become the way you organise them. A function with type hints states its...
Lazy evaluation and yield
Until now you've held whole datasets in memory. But some data doesn't fit — a file larger than your...
Measurement scales and your first function
Everything read from a CSV is a string, so before you can compute you must parse each value into...
A config class that validates itself
The highest-value use of a class in data work is a validated configuration object . A pipeline has...