[News] : Explore VerticaPy v0.6.0, a Python library for data science projects
What’s New in VerticaPy v0.6.0 ?
New features: Python API for Vertica Data Science at Scale
- AutoDataPrep is now available. AutoDataPrep automatically finds relations between the different features to preprocess the data according to each column type.
- Improved AutoML is now available. AutoML is a powerful machine learning technique that automatically tests several models and returns the one with the highest input score.
- AutoClustering is now available. AutoClustering creates k groups and for generalizing the data.
- New method: Model.contour draws the contour plot of your model.
- New method: Model.to_sql exports your model as regular SQL.
- New method: Model.to_python eports your model as an independent Python function.
- New functions for evaluating models and tuning hyperparameters: bayesian_search_cv, enet_search_cv, randomized_features_search_cv and stepwise.
- New Functions: coordinate_converter converts bertween latitude and longitude and Euclidean coordinates (x,y) and to split any polygon to n identical smaller ones.
- New Functions: split_polygon_n splits any polygon to n identical smaller polygons.
- New method: vDataFrame.cut allows you to discretize numerical features.
- New method: vDataFrame.add_duplicates allows you to add duplicates when it is needed. An example could be creating a weighted KMeans.
- Additional parameter ‘ncols_block’ for the vDataFrame.describe and vDataFrame.agg methods: this parameter lets you control the number of columns specified in the generated SQL code and can make queries “lighter” according to your use case.
Graphics and Data Visualization
- A loading bar is available for many functions. It uses ‘tqdm’ API.
- New method: vDataFrame.animated draws animated charts.
- New method: vDataFrame.contour draws contour plots.
- New time series datasets: load_gapminder and load_pop_growth.
- You can now generate your own datasets with gen_dataset and gen_meshgrid.
Deprecated, Replaced, or Moved
- The package verticapy.connections.connect has been moved to verticapy.connect
- The package verticapy.learn.datasets has been moved to verticapy.datasets
- The package verticapy.learn.tsa.tools has been moved to verticapy.stats
- The package verticapy.learn.tsa.models has been moved to verticapy.learn.tsa
- The functions drop_table, drop_text_index, drop_view, and drop_model have been replaced by the drop function.
GitHub and Unit Tests
- More unit tests are available.
To know more about Vertica or request a demo, visit our page HERE