docs: fix reading dtypes

[yokomotod]

Hello. I faced the same confusion as #579, so have tried to update the docs.

Not only the BQ DATE type but also the TIME, TIMESTAMP, and FLOAT64 types seems to be wrong.

It seems to be due to a breaking change in google-cloud-bigquery v3.
https://cloud.google.com/python/docs/reference/bigquery/latest/upgrading#changes-to-data-types-loading-a-pandas-dataframe

I have confirmed the correct dtypes as:

>>> import pandas

>>> sql1 = """
SELECT
  TRUE AS BOOL,
  123 AS INT64,
  123.456 AS FLOAT64,

  TIME '12:30:00.45' AS TIME,
  DATE "2023-01-01" AS DATE,
  DATETIME "2023-01-01 12:30:00.45" AS DATETIME,
  TIMESTAMP "2023-01-01 12:30:00.45" AS TIMESTAMP
"""

>>> pandas.read_gbq(sql).dtypes
BOOL                        boolean
INT64                         Int64
FLOAT64                     float64
TIME                         dbtime
DATE                         dbdate
DATETIME             datetime64[ns]
TIMESTAMP       datetime64[ns, UTC]
dtype: object

>>> sql2 = """
SELECT
  DATE "2023-01-01" AS DATE,
  DATETIME "2023-01-01 12:30:00.45" AS DATETIME,
  TIMESTAMP "2023-01-01 12:30:00.45" AS TIMESTAMP,
UNION ALL
SELECT
  DATE "2263-04-12" AS DATE,
  DATETIME "2263-04-12 12:30:00.45" AS DATETIME,
  TIMESTAMP "2263-04-12 12:30:00.45" AS TIMESTAMP
"""

>>> pandas.read_gbq(sql2).dtypes
DATE         object
DATETIME     object
TIMESTAMP    object
dtype: object

Fixes #579 🦕

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[yokomotod]

Some tests failed with

google.auth.exceptions.DefaultCredentialsError: Could not automatically determine credentials. Please set GOOGLE_APPLICATION_CREDENTIALS or explicitly create credentials and re-run the application. For more information, please see https://cloud.google.com/docs/authentication/getting-started

Can anyone help me with this for review and merge?

[tswast]

Thanks for the contribution!

As an aside, in future I'd like pandas-gbq to align our dtypes handling with the latest dtype_backend parameter #621 which is in other pandas I/O methods like read_csv.