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@ActurialCapital ActurialCapital released this 01 Jul 16:45
· 7 commits to main since this release
0.1.7
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Version 0.1.7 - Enhanced Data Preprocessing and Transformation

Summary

We are excited to announce the release of version 0.1.7 of the blocks package, which includes significant enhancements to data preprocessing and transformation capabilities. This release introduces new classes and transformers that simplify and extend the functionality of our data processing pipeline.

New Features

Preprocessing

  • ShiftFactor: Apply shifting to X while y remains unchanged.
  • BasisOperation: Perform elementary arithmetic operations between two DataFrames, including addition, subtraction, multiplication, division, and lagged operations.
  • Filter: Apply various filters to raw data based on specified thresholds, frequencies, and aggregation methods.

Transformers

  • ColumnAverage: Calculate various types of means within a DataFrame, including simple, weighted, expanding, rolling, EMA, and grouped means.
  • RateOfChange: Calculate the rate of change (ROC) for financial time series data over a specified window period.
  • Rolling: Compute rolling statistics for each column in the DataFrame, including sum, mean, median, variance, standard deviation, min, max, quantile, custom functions, correlation, covariance, skewness, kurtosis, count, and rank.
  • Zscore: Calculate the Z-score for each column in the DataFrame over a specified window period.
  • QuantileRanks: Transform predictions into quantile-based signals based on the specified number of quantiles.
  • Signal: Convert ranks or numbers into investment signals.

Tests

  • Added new tests using pytest to cover the newly introduced classes and methods.

Using poetry:

poetry run pytest

Structure

blocks
├── __init__.py
├── base.py
├── decorators.py
├── meta.py
├── pipeline.py
├── preprocessing.py
└── transformers.py
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