32. Features and Labels in Machine Learning

32.1 Features (X) and Labels (y) in Plain Words

By Ravindra Bagale · Last updated: 24 October 2026

Why. sklearn code writes X and y. If those letters feel scary, stop here and make them boring.

What.

• Features (X) — input columns the model is allowed to look at (items, distance, rain…).
• Label (y) — the answer column you want to guess (was_late, amount, churn…).

Memory trick: X = eXplanatory inputs. y = the why we care about (the target).

How.

import pandas as pd

df = pd.DataFrame({
 "items": [2, 5, 3],
 "distance_km": [1.2, 4.0, 2.5],
 "was_late": [0, 1, 0],
})
X = df[["items", "distance_km"]] # features
y = df["was_late"] # label
print("X columns:", list(X.columns))
print("y name:", y.name)