v0.3.0

0.3.0 (2023-09-02)

Features

• Add bigframes.get_global_session() and bigframes.reset_session() aliases (a32b747)
• Add bigframes.pandas.read_pickle function (a32b747)
• Add components_, explained_variance_, and explained_variance_ratio_ properties to bigframes.ml.decomposition.PCA (89b9503)
• Add fit_transform to bigquery.ml transformers (a32b747)
• Add Series.dropna and DataFrame.fillna (8fab755)
• Add Series.str methods isalpha, isdigit, isdecimal, isalnum, isspace, islower, isupper, zfill, center (a32b747)
• Support bigframes.pandas.merge() (8fab755)
• Support DataFrame.isin with list and dict inputs (8fab755)
• Support DataFrame.pivot (a32b747)
• Support DataFrame.stack (89b9503)
• Support DataFrame-DataFrame binary operations (8fab755)
• Support df[my_column] = [a python list] (89b9503)
• Support Index.is_monotonic (8fab755)
• Support np.arcsin, np.arccos, np.arctan, np.sinh, np.cosh, np.tanh, np.arcsinh, np.arccosh, np.arctanh, np.exp with Series argument (89b9503)
• Support np.sin, np.cos, np.tan, np.log, np.log10, np.sqrt, np.abs with Series argument (89b9503)
• Support pow() and power operator in DataFrame and Series (8fab755)
• Support read_json with engine=bigquery for newline-delimited JSON files (89b9503)
• Support Series.corr (89b9503)
• Support Series.map (8fab755)
• Support for np.add, np.subtract, np.multiply, np.divide, np.power (8fab755)
• Support MultiIndex for DataFrame columns (a32b747)
• Use pandas.Index for column labels (a32b747)
• Use default session and connection in ml.llm and ml.imported (8fab755)

Bug Fixes

• Add error message to set_index (a32b747)
• Align column names with pandas in DataFrame.agg results (89b9503)
• Allow (but still not recommended) ORDER BY in read_gbq input when an index_col is defined (89b9503)
• Check for IAM role on the BigQuery connection when initializing a remote_function (89b9503)
• Check that types are specified in read_gbq_function (a32b747)
• Don't use query cache for Session construction (a32b747)
• Include survey link in abstract NotImplementedError exception messages (89b9503)
• Label temp table creation jobs with source=bigquery-dataframes-temp label (89b9503)
• Make X_train argument names consistent across methods (8fab755)
• Raise AttributeError for unimplemented pandas methods (89b9503)
• Raise exception for invalid function in read_gbq_function (a32b747)
• Support spaces in column names in DataFrame initializater (89b9503)

Performance Improvements

• Add local cache for __repr_*__ methods (a32b747)
• Lazily instantiate client library objects (89b9503)
• Use row_number() filter for head / tail (8fab755)

Documentation

• Add ML section under Overview (a32b747)
• Add release status to table of contents (a32b747)
• Add samples and best practices to read_gbq docs (a32b747)
• Correct the return types of Dataframe and Series (a32b747)
• Create subfolders for notebooks (a32b747)
• Fix link to GitHub (89b9503)
• Highlight bigframes is open-source (a32b747)
• Sample ML Drug Name Generation notebook (a32b747)
• Set options.bigquery.project in sample code (89b9503)
• Transform remote function user guide into sample code (a32b747)
• Update remote function notebook with read_gbq_function usage (8fab755)

Version 0.2.0

0.2.0 (2023-08-17)

Features

• Add KMeans.cluster_centers_.
• Allow column labels to be any type handled by bq df, column labels can be integers now.
• Add dataframegroupby.agg().
• Add Series Property is_monotonic_increasing and is_monotonic_decreasing.
• Add match, fullmatch, get, pad str methods.
• Add series isin function.

Bug Fixes

• Update ML package to use sessions for queries.
• Optimize read_gbq with index_col set to cluster by index_col.
• Raise ValueError if the location mismatched.
• read_gbq no longer uses 'time travel' with query inputs.

Documentation

• Add docstring to _uniform_sampling to avoid user using it.

Version 0.1.1

Documentation

• Correct link to code repository in setup.py and use correct terminology for
  console.cloud.google.com links.

Version 0.1.0

0.1.0 (2023-08-11)

Features

• Add bigframes.pandas package with an API compatible with
  pandas. Supported data sources include:
  BigQuery SQL queries, BigQuery tables, CSV (local and GCS), Parquet (local
  and Cloud Storage), and more.
• Add bigframes.ml package with an API inspired by
  scikit-learn. Train machine learning
  models and run batch predicition, powered by BigQuery
  ML.