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HR / People Analytics · how-to

Flight Risk — predict which employees will resign — in Python

A turnover-prediction analysis. Every step below is the same analysis rendered for Python — grounded in the source, honest where Python can't do a step cleanly.

Same analysis, your tool

DERIVE

logistic regression needs numeric inputs; encode categoricals

df["derived"] = expr

CORRELATE

screen which variables actually track turnover before modeling

df["driver_j"].corr(df["outcome"])

FIT-CLASSIFIER

estimate the equation linking predictors to probability of resigning

LogisticRegression().fit(X, y)

VALIDITY · mechanical

confirm each predictor contributes reliably

df["measure"].corr(df["criterion"])

PREDICT

score each employee's likelihood of leaving to prioritize retention

model.predict(df)

Grounded in

Predictive HR Analytics with Excel, Sec 19.8 Logistic Regression: Predict Staff Resignation (also 12.4, 17.9)

Doing HR / People Analytics work?

The full HR / People Analytics guide covers this and the whole workflow around it — reconciled from the field’s best books.

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