Overview

Chrono-Brush is a Python library I built to handle the dirty work of time-series analysis. It provides scikit-learn compatible transformers to build clean, reproducible preprocessing pipelines.

Features

  • Outlier Removal: Statistical methods (IQR, Z-score) to clean noise.
  • Imputation: Strategies for handling missing values (Forward fill, etc.).
  • Trend Removal: Prophet-based trend decomposition.
  • Composable: Fully compatible with sklearn.pipeline.Pipeline.
from chrono_brush import OutlierRemover, MissingValueImputer, Pipeline

pipe = Pipeline([
    ("impute", MissingValueImputer(strategy="ffill")),
    ("outliers", OutlierRemover(method="iqr")),
])
cleaned = pipe.fit_transform(series)

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