v0.17.0

0.17.0 (2022-01-19)

⚠ BREAKING CHANGES

• use nullable Int64 and boolean dtypes if available (#445)

Features

• accepts a table ID, which downloads the table without a query (#443) (bf0e863)
• use nullable Int64 and boolean dtypes if available (#445) (89078f8)

Bug Fixes

• read_gbq supports extreme DATETIME values such as 0001-01-01 00:00:00 (#444) (d120f8f)
• to_gbq allows strings for DATE and floats for NUMERIC with api_method="load_parquet" (#423) (2180836)
• allow extreme DATE values such as datetime.date(1, 1, 1) in load_gbq (#442) (e13abaf)
• avoid iteritems deprecation in pandas prerelease (#469) (7379cdc)
• use data project for destination in to_gbq (#455) (891a00c)

Miscellaneous Chores

• release 0.17.0 (#470) (29ac8c3)

v0.16.0

Features

• to_gbq uses Parquet by default, use api_method="load_csv" for old behavior (#413) (9a65383)
• allow Python 3.10 (#417) (faba940)

Miscellaneous Chores

• release 0.16.0 (#415) (ea0f4e9)

Documentation

• clarify table_schema (#383) (326e674)

Version 0.15.0

Features

• Load DataFrame with to_gbq to a table in a project different from
  the API client project. Specify the target table ID as
  project.dataset.table to use this feature. (#321, #347)
• Allow billing project to be separate from destination table project
  in to_gbq. (#321)

Bug fixes

• Avoid 403 error from to_gbq when table has policyTags. (#354)
• Avoid client.dataset deprecation warnings. (#312)

Dependencies

• Drop support for Python 3.5 and 3.6. (#337)
• Drop support for google-cloud-bigquery==2.4.* due to query
  hanging bug. (#343)

Version 0.14.1

• Use object dtype for TIME columns. (#328)
• Encode floating point values with greater precision. (#326)
• Support INT64 and other standard SQL aliases in
  pandas_gbq.to_gbq table_schema argument. (#322)

https://pypi.org/project/pandas-gbq/0.14.1/

Version 0.14.0

0.14.0 / 2020-10-05

• Add dtypes argument to read_gbq. Use this argument to override
  the default dtype for a particular column in the query results.
  For example, this can be used to select nullable integer columns as
  the Int64 nullable integer pandas extension type. (#242, #332)

df = pandas_gbq.read_gbq(
    "SELECT CAST(NULL AS INT64) AS null_integer",
    dtypes={"null_integer": "Int64"},
)

Dependency updates

• Support google-cloud-bigquery-storage 2.0 and higher. (#329)
• Update the minimum version of pandas to 0.20.1. (#331)

Internal changes

• Update tests to run against Python 3.8. (#331)

Version 0.13.3

• Include needed "extras" from google-cloud-bigquery package as
  dependencies. Exclude incompatible 2.0 version. (#324, #329)

PyPI

Version 0.13.1

• Fix AttributeError with BQ Storage API to download empty results. (#299)

PyPI

Version 0.13.0

• Raise NotImplementedError when the deprecated private_key argument is used. (#301)

Version 0.12.0

New features

• Add max_results argument to pandas_gbq.read_gbq(). Use this
  argument to limit the number of rows in the results DataFrame. Set
  max_results to 0 to ignore query outputs, such as for DML or DDL
  queries. (#102)
• Add progress_bar_type argument to pandas_gbq.read_gbq(). Use
  this argument to display a progress bar when downloading data.
  (#182)

Dependency updates

• Update the minimum version of google-cloud-bigquery to 1.11.1.
  (#296)

Documentation

• Add code samples to introduction and refactor how-to guides. (#239)

Bug fixes

• Fix resource leak with use_bqstorage_api by closing BigQuery Storage API client after use. (#294)

Release on PyPI

Version 0.11.0

• Breaking Change: Python 2 support has been dropped. This is to align
  with the pandas package which dropped Python 2 support at the end of 2019.
  (#268)

Enhancements

• Ensure table_schema argument is not modified inplace. (:issue:278)

Implementation changes

• Use object dtype for STRING, ARRAY, and STRUCT columns when
  there are zero rows. (#285)

Internal changes

• Populate user-agent with pandas version information. (#281)
• Fix pytest.raises usage for latest pytest. Fix warnings in tests.
  (#282 )
• Update CI to install nightly packages in the conda tests. (#254)