从 DataFrame 加载数据

将 pandas DataFrame 的内容加载到表中。

代码示例

Python

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import datetime
from zoneinfo import ZoneInfo

import bigframes.pandas as bpd
import pandas as pd
import pandas_gbq

# Set partial ordering mode for BigQuery DataFrames.
bpd.options.bigquery.ordering_mode = "partial"


def load_table_dataframe_bigframes(
    table_id: str = "your-project.your_dataset.your_table_name",
) -> None:
    """Loads a pandas DataFrame into a BigQuery table using BigQuery DataFrames."""
    records = [
        {
            "title": "The Meaning of Life",
            "release_year": 1983,
            "length_minutes": 112.5,
            "release_date": datetime.datetime(
                1983, 5, 9, 13, 0, 0, tzinfo=ZoneInfo("Europe/Paris")
            ).astimezone(datetime.timezone.utc),
            # Assume UTC timezone when a datetime object contains no timezone.
            "dvd_release": datetime.datetime(2002, 1, 22, 7, 0, 0),
        },
        {
            "title": "Monty Python and the Holy Grail",
            "release_year": 1975,
            "length_minutes": 91.5,
            "release_date": datetime.datetime(
                1975, 4, 9, 23, 59, 2, tzinfo=ZoneInfo("Europe/London")
            ).astimezone(datetime.timezone.utc),
            "dvd_release": datetime.datetime(2002, 7, 16, 9, 0, 0),
        },
        {
            "title": "Life of Brian",
            "release_year": 1979,
            "length_minutes": 94.25,
            "release_date": datetime.datetime(
                1979, 8, 17, 23, 59, 5, tzinfo=ZoneInfo("America/New_York")
            ).astimezone(datetime.timezone.utc),
            "dvd_release": datetime.datetime(2008, 1, 14, 8, 0, 0),
        },
        {
            "title": "And Now for Something Completely Different",
            "release_year": 1971,
            "length_minutes": 88.0,
            "release_date": datetime.datetime(
                1971, 9, 28, 23, 59, 7, tzinfo=ZoneInfo("Europe/London")
            ).astimezone(datetime.timezone.utc),
            "dvd_release": datetime.datetime(2003, 10, 22, 10, 0, 0),
        },
    ]
    dataframe = pd.DataFrame(
        records,
        # In the loaded table, the column order reflects the order of the
        # columns in the DataFrame.
        columns=[
            "title",
            "release_year",
            "length_minutes",
            "release_date",
            "dvd_release",
        ],
        # Optionally, set a named index, which can also be written to the
        # BigQuery table.
        index=pd.Index(["Q24980", "Q25043", "Q24953", "Q16403"], name="wikidata_id"),
    )

    bq_df = bpd.read_pandas(dataframe)
    bq_df.to_gbq(table_id, if_exists="replace", index=True)
    print(f"Loaded DataFrame to {table_id} using BigQuery DataFrames.")


def load_table_dataframe_pandas_gbq(
    table_id: str = "your-project.your_dataset.your_table_name",
) -> None:
    """Loads a pandas DataFrame into a BigQuery table using pandas-gbq."""
    records = [
        {
            "title": "The Meaning of Life",
            "release_year": 1983,
            "length_minutes": 112.5,
            "release_date": datetime.datetime(
                1983, 5, 9, 13, 0, 0, tzinfo=ZoneInfo("Europe/Paris")
            ).astimezone(datetime.timezone.utc),
            # Assume UTC timezone when a datetime object contains no timezone.
            "dvd_release": datetime.datetime(2002, 1, 22, 7, 0, 0),
        },
        {
            "title": "Monty Python and the Holy Grail",
            "release_year": 1975,
            "length_minutes": 91.5,
            "release_date": datetime.datetime(
                1975, 4, 9, 23, 59, 2, tzinfo=ZoneInfo("Europe/London")
            ).astimezone(datetime.timezone.utc),
            "dvd_release": datetime.datetime(2002, 7, 16, 9, 0, 0),
        },
        {
            "title": "Life of Brian",
            "release_year": 1979,
            "length_minutes": 94.25,
            "release_date": datetime.datetime(
                1979, 8, 17, 23, 59, 5, tzinfo=ZoneInfo("America/New_York")
            ).astimezone(datetime.timezone.utc),
            "dvd_release": datetime.datetime(2008, 1, 14, 8, 0, 0),
        },
        {
            "title": "And Now for Something Completely Different",
            "release_year": 1971,
            "length_minutes": 88.0,
            "release_date": datetime.datetime(
                1971, 9, 28, 23, 59, 7, tzinfo=ZoneInfo("Europe/London")
            ).astimezone(datetime.timezone.utc),
            "dvd_release": datetime.datetime(2003, 10, 22, 10, 0, 0),
        },
    ]
    dataframe = pd.DataFrame(
        records,
        # In the loaded table, the column order reflects the order of the
        # columns in the DataFrame.
        columns=[
            "title",
            "release_year",
            "length_minutes",
            "release_date",
            "dvd_release",
        ],
        # Optionally, set a named index, which can also be written to the
        # BigQuery table.
        index=pd.Index(["Q24980", "Q25043", "Q24953", "Q16403"], name="wikidata_id"),
    )

    pandas_gbq.to_gbq(dataframe, table_id, if_exists="replace")
    print(f"Loaded DataFrame to {table_id} using pandas-gbq.")


# [Preferred] Run using BigQuery DataFrames:
# load_table_dataframe_bigframes("your-project.your_dataset.your_table_name")

# Alternatively, run using pandas-gbq:
# load_table_dataframe_pandas_gbq("your-project.your_dataset.your_table_name")

后续步骤

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