General
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Xtest = Xtest.drop(columns=drop_cols
errors='ignore')
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Explore
Find agent skills by outcome
153,723 skills indexed with the new KISS metadata standard.
Showing 24 of 153,723
General
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STEP 12 — MICE / IterativeImputer (most powerful
use when needed)
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General
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Xtrain = Xtrain.drop(columns=drop_cols
errors='ignore')
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General
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X_train
X_test
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General
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X
y
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df.dropna(subset=[TARGET_COL]
axis=0
1
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DISGUISED_NULLS = [?
N/A
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General
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df.replace(DISGUISED_NULLS
np.nan
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Education
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from sklearn.impute import SimpleImputer
KNNImputer
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General
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│ Tree-based (XGBoost
LightGBM
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General
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│ SVM
KNN Classifier: │
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General
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│ Linear Models (LogReg
LinearReg
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→ df.dropna(subset=[TARGET_COL]
inplace=True)
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│ → Use max_iter=10
random_state=42 for reproducibility │
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│ → Creates: colwasmissing = 1 if NaN
else 0 │
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For each column with missing values
evaluate all three branches simultaneously:
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For each flagged column
fill in this analysis card:
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General
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│ │ Signs: Missingness correlates with OTHER columns
│
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missingreport = missingreport.sortvalues('Missing%'
ascending=False)
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General
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DISGUISED_NULLS = [?
N/A
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General
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df.replace(DISGUISED_NULLS
np.nan
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General
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- e.g.
CustomerID must be unique and non-null
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- e.g.
Age cannot be 0 or negative
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General
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- e.g.
Price is the target — rows missing it are unusable
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