Helpful messages & errors

moderndive is built for people learning statistics, so its messages and errors are written to teach, not just to report. They follow the same style as the R infer package: a short summary line, then one or more → hint bullets telling you what to do next.

There are two kinds:

• Errors (ValueError / TypeError) — something can’t proceed, raised with a fix-it hint.

• Informational notes — a heads-up that doesn’t stop your code, emitted as a suppressible ModernDiveMessage warning.

Errors that tell you how to fix them

Mistype a column name and you get the available columns back, not a cryptic KeyError:

import moderndive as md
from moderndive import get_correlation

houses = md.load_saratoga_houses()
try:
    get_correlation(houses, "price ~ livng_area")  # typo
except ValueError as e:
    print(e)

Column(s) not found in the data: livng_area.
  → Available columns: price, living_area, bathrooms, bedrooms, fireplaces, lot_size, age, fireplace.

Pass the wrong kind of object and the error names the fix:

from moderndive import get_regression_table

try:
    get_regression_table("not a fitted model")
except TypeError as e:
    print(e)

Expected a fitted statsmodels model, got str.
  → Fit one first, e.g. smf.ols("y ~ x", data).fit() or smf.glm(...).fit().

from moderndive import plot_3d_regression

# plot_3d_regression needs exactly two numeric predictors
try:
    plot_3d_regression(houses, "price ~ living_area")
except ValueError as e:
    print(e)

The right-hand side must name exactly two predictors (got 1).
  → Use a formula like 'z ~ x + y'.

Informational notes (and how to silence them)

Some functions point out something useful without stopping. For example, asking for correlations against several predictors notes that you’re getting predictor-vs-outcome correlations only (not a full pairwise matrix):

import warnings
from moderndive._messaging import ModernDiveMessage

with warnings.catch_warnings(record=True) as caught:
    warnings.simplefilter("always")
    get_correlation(houses, "price ~ living_area + bedrooms + bathrooms")

for w in caught:
    if issubclass(w.category, ModernDiveMessage):
        print(w.message)

Computing correlations of `price` against 3 predictors.
  → For a full pairwise matrix (incl. predictor–predictor correlations), use `df.to_pandas().corr()`.
  → Pass quiet=True to silence this message.

These notes are designed to be easy to turn off once you know what they mean. Many functions take a quiet=True flag:

with warnings.catch_warnings(record=True) as caught:
    warnings.simplefilter("always")
    get_correlation(houses, "price ~ living_area + bedrooms", quiet=True)

print("messages emitted:", sum(issubclass(w.category, ModernDiveMessage) for w in caught))

messages emitted: 0

Or silence every moderndive note globally with a standard warnings filter:

import warnings
from moderndive._messaging import ModernDiveMessage

warnings.filterwarnings("ignore", category=ModernDiveMessage)

Why this matters

For a newcomer, the difference between KeyError: 'livng_area' and “Column(s) not found in the data: livng_area. → Available columns: …” is the difference between getting stuck and fixing it in seconds. Because the informational notes are their own warning category, they’re equally easy to see while learning and to mute once you’re comfortable.