Version 0.4.0

PyPI release, Conda Forge release

• Fix bug in read_gbq when building a dataframe with integer columns on Windows. Explicitly use 64bit integers when converting from BQ types. (#119)
• Fix bug in read_gbq when querying for an array of floats (#123)
• Fix bug in read_gbq with configuration argument. Updates read_gbq to account for breaking change in the way google-cloud-python version 0.32.0+ handles query configuration API representation. (#152)
• Fix bug in to_gbq where seconds were discarded in timestamp columns. (#148)
• Fix bug in to_gbq when supplying a user-defined schema (#150)
• Deprecate the verbose parameter in read_gbq and to_gbq. Messages use the logging module instead of printing progress directly to standard output. (#12)

Version 0.3.1

PyPI release, Conda Forge release

• Fix an issue where Unicode couldn't be uploaded in Python 2 (issue 106)
• Add support for a passed schema in :func:to_gbq instead inferring the schema from the passed DataFrame with DataFrame.dtypes (issue 46)
• Fix an issue where a dataframe containing both integer and floating point columns could not be uploaded with to_gbq (issue 116)
• to_gbq now uses to_csv to avoid manually looping over rows in a dataframe (should result in faster table uploads) (issue 96)

Version 0.3.0

PyPI release, Conda Forge release

• Use the google-cloud-bigquery library for API calls. The google-cloud-bigquery package is a new dependency, and dependencies on google-api-python-client and httplib2 are removed. See the installation guide for more details. (#93)
• Structs and arrays are now named properly (#23) and BigQuery functions like array_agg no longer run into errors during type conversion (#22 ).
• :func:to_gbq now uses a load job instead of the streaming API. Remove StreamingInsertError class, as it is no longer used by :func:to_gbq. (#7, #75 )