pandas.rst

Using BigQuery with Pandas

Retrieve BigQuery data as a Pandas DataFrame

As of version 0.29.0, you can use the ~google.cloud.bigquery.table.RowIterator.to_dataframe function to retrieve query results or table rows as a pandas.DataFrame.

First, ensure that the pandas library is installed by running:

pip install --upgrade pandas

Alternatively, you can install the BigQuery python client library with pandas by running:

pip install --upgrade google-cloud-bigquery[pandas]

To retrieve query results as a pandas.DataFrame:

../snippets.py

To retrieve table rows as a pandas.DataFrame:

../snippets.py

Retrieve BigQuery GEOGRAPHY data as a GeoPandas GeoDataFrame

GeoPandas adds geospatial analytics capabilities to Pandas. To retrieve query results containing GEOGRAPHY data as a geopandas.GeoDataFrame:

../samples/geography/to_geodataframe.py

Load a Pandas DataFrame to a BigQuery Table

As of version 1.3.0, you can use the ~google.cloud.bigquery.client.Client.load_table_from_dataframe function to load data from a pandas.DataFrame to a ~google.cloud.bigquery.table.Table. To use this function, in addition to pandas, you will need to install the pyarrow library. You can install the BigQuery python client library with pandas and pyarrow by running:

pip install --upgrade google-cloud-bigquery[pandas,pyarrow]

The following example demonstrates how to create a pandas.DataFrame and load it into a new table:

../samples/load_table_dataframe.py