Vibe codingMediumvc-g260

Subject Ai code reviewLevel Mid–Senior~16 minCommon in Algorithms & data structures interviewsIndustries Software development

Question

An AI produced this data-cleaning step before training. It runs without error and the model trains, but the loss curve is oddly noisy. Find the silent NaN bug.

python

1import numpy as np2 3# 'sensor' has missing readings encoded as -9994df['sensor'] = df['sensor'].replace(-999, np.nan)5df['sensor_norm'] = (df['sensor'] - df['sensor'].mean()) / df['sensor'].std()6features = df[['sensor_norm', 'temp', 'pressure']].values.astype(np.float32)7labels = df['target'].values8model.fit(features, labels)   # no error raised

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