utilsds 1.0.9

Solution for DS Team

utilsds

Utilsds is a library that includes classes and functions used in data science projects such as:

• ds_statistics:

  • test_kruskal_wallis: Perform the Kruskal-Wallis statistical test.

• transform_data:

  • DataTransformer: Transform data using various methods.

• data_processing:

  • encode_one_hot: Encode categorical features using one-hot encoding.
  • convert_numerical_to_categorized: Convert numerical features to categorized intervals.
  • scale_train_test: Scale training and testing datasets.
  • resample_X_y: Resample training data and target columns.

• data_split:

  • train_test_validation_split: Split data into training, testing, and validation sets.

• visualization:

  • MetricsPlot: Compare metrics for different parameter values.
  • Radar: Create radar plots for visualizing data.
  • cluster_characteristics: Analyze cluster characteristics.
  • comparison_density: Compare density distributions.
  • feature_distribution_box: Visualize feature distributions per cluster.
  • elbow_visualisation: Visualize the elbow method for clustering.
  • describe_clusters_metrics: Describe metrics for clusters.

• data_ops:

  • DataOperations: Handle data operations with Google Cloud services (BigQuery and Cloud Storage).

• confusion_matrix:

  • ConfusionMatrix: Generate and plot confusion matrices.

• modeling:

  • Modeling: Manage modeling, metrics, and logging with Vertex AI.

• hyperopt:

  • Hyperopt: Optimize hyperparameters using Hyperopt.

• classifier:

  • Classifier: Fit, train, and manage classification models.

• experiments:

  • VertexExperiments: Manage experiments with Vertex AI.