Release History

dabl 0.2.5

• Improved plotting of low cardinality integers, #326 by @amueller.

• Added engineering formatter to plots, #324 by @stefmolin.

• Share x and y axes when appropriate, #323 by @stefmolin.

dabl 0.2.4

• Added pruning of correlated features and detecting of interactions with categorical features to regression plots, #316 by @amueller.

• Add detection of lists and dicts in detect_type_series. #317 by @amueller.

• Use matplotlib’s stairs for faster histograms. #313 by @amueller.

• Add jitter to ordinal features in regression scatter plots. :issue:`` by @amueller.

dabl 0.2.2

• Added plot_sankey, #305 by @amueller for Sankey plots (or really alluvial flow diagrams).

• Drop outliers in univariate target plots in regression. #304 by @amueller.

dabl 0.2.1

• Plot missing values as separate category, #289 by @amueller.

• Don’t import dateutil.parser.ParserError for more version flexibility.

• Fix error in computation of max_int_cardinality, #288 by @amueller.

dabl 0.2.0

• Rely on the Successive Halving implementation from scikit-learn 0.24, removing the old implementation. Consequently the search module in dabl has been deprecated and the minimum version requirement of scikit-learn is now 0.24.

• The type detection has been completely rewritten and accomodates more edge cases, #270 by @amueller.

• A global configuration was introduced that can be set with set_config. For now, this allows users to turn off truncation of labels, by @amueller.

• Fix default value of alpha in plot_regression_continuous, #276 by @amueller.

• Fix a memory issue when calling bincount on really large integers in the type detection, #275 by @amueller.

dabl 0.1.9

• Fix bug in type detection when a column contained boolean data and missing values, #256 by @amueller.

• Bundle LICENSE file with project in release, #253 by @dhirschfeld.

• Make color usage consistent between scatter plots and mosaic plots, #249 by @h4pZ.

• Update the AnyClassifier portfolio to include several new optimized portfolios, #246 by @hp2500.

dabl 0.1.7

• Ensure target column is not dropped in ‘clean’ for highly imbalanced datasets #171.

• Scale histograms separately in class histograms #173.

• Shorten really long column names to fix figure layout #180.

• Add shuffling to cross-validation for simple models #185.

• Fix broken legend for class histograms for ordinal variables #189.

• Allow numpy arrays in SimpleRegressor and plot #187.

• Add actual vs predicted plot for regression to explain #186.

dabl 0.1.6

• More fixed to dirty floats with heterogeneous dtypes.

dabl 0.1.5

• More robust detection of dirty floats, more robust parsing of categorical variables.

• Ensure data is parsed consistently between predict and fit by not calling clean in fit.

• Allow passing columns with integer names as target in plot.