EDA Toolkit 0.0.24

Version 0.0.24

New Features

• detect_outliers(): New batch outlier detection function supporting
  IQR, Z-score, and Isolation Forest methods with groupby, flag_col,
  return_mask, return_bounds, and verbose parameters
• flex_corr_matrix(): Added corr_method (pearson/spearman/kendall),
  show_significance, significance_level, significance_method (stars/mask),
  significance_legend_x, filter_significance, and image_filename parameters

Enhancements

• read_csv_with_progress(): Added chunksize, low_memory, and **kwargs
  passthrough to pd.read_csv

Bug Fixes

• flex_corr_matrix(): Fixed title misalignment, -0.00 display artifact,
  diagonal now shows 1.00 in both stars and mask modes; fixed abs() stripping
  negative signs from significance annotations
• detect_outliers(): Added observed=True to groupby calls to silence
  pandas FutureWarning

Dependency Updates

• Removed upper caps on matplotlib, scikit-learn, and tqdm to prevent
  Colab downgrades

Infrastructure

• _data_manager_utils.py: Extracted _flag_iqr and _flag_zscore helpers
• new pytest tests added across detect_outliers, flex_corr_matrix,
  and read_csv_with_progress
• README stripped to lean landing page; full docs at
  datasciencedynamics.com/eda_toolkit_docs/