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chore: tweaks to eliminate broken docs links
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‎packages/pandas-gbq/docs/intro.rst‎

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@@ -27,11 +27,20 @@ Reading data from BigQuery
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Use the :func:`pandas_gbq.read_gbq` function to run a BigQuery query and
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download the results as a :class:`pandas.DataFrame` object.
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.. literalinclude:: ../samples/snippets/read_gbq_simple.py
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:language: python
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:dedent: 4
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:start-after: [START bigquery_pandas_gbq_read_gbq_simple]
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:end-before: [END bigquery_pandas_gbq_read_gbq_simple]
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.. code-block:: python
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import pandas_gbq
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# TODO: Set project_id to your Google Cloud Platform project ID.
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# project_id = "my-project"
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sql = """
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SELECT country_name, alpha_2_code
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FROM `bigquery-public-data.utility_us.country_code_iso`
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WHERE alpha_2_code LIKE 'A%'
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"""
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df = pandas_gbq.read_gbq(sql, project_id=project_id)
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print(df)
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By default, queries use standard SQL syntax. Visit the :doc:`reading tables
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guide <reading>` to learn about the available options.
@@ -57,11 +66,29 @@ Writing data to BigQuery
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Use the :func:`pandas_gbq.to_gbq` function to write a
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:class:`pandas.DataFrame` object to a BigQuery table.
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.. literalinclude:: ../samples/snippets/to_gbq_simple.py
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:language: python
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:dedent: 4
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:start-after: [START bigquery_pandas_gbq_to_gbq_simple]
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:end-before: [END bigquery_pandas_gbq_to_gbq_simple]
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.. code-block:: python
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import pandas
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import pandas_gbq
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# TODO: Set project_id to your Google Cloud Platform project ID.
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# project_id = "my-project"
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# TODO: Set table_id to the full destination table ID (including the
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# dataset ID).
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# table_id = 'my_dataset.my_table'
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df = pandas.DataFrame(
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{
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"my_string": ["a", "b", "c"],
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"my_int64": [1, 2, 3],
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"my_float64": [4.0, 5.0, 6.0],
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"my_bool1": [True, False, True],
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"my_bool2": [False, True, False],
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"my_dates": pandas.date_range("now", periods=3),
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}
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)
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pandas_gbq.to_gbq(df, table_id, project_id=project_id)
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The destination table and destination dataset will automatically be created.
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By default, writes to BigQuery fail if the table already exists. Visit the

‎packages/pandas-gbq/docs/reading.rst‎

Lines changed: 29 additions & 10 deletions
Original file line numberDiff line numberDiff line change
@@ -6,11 +6,20 @@ Reading Tables
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Use the :func:`pandas_gbq.read_gbq` function to run a BigQuery query and
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download the results as a :class:`pandas.DataFrame` object.
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.. literalinclude:: ../samples/snippets/read_gbq_simple.py
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:language: python
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:dedent: 4
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:start-after: [START bigquery_pandas_gbq_read_gbq_simple]
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:end-before: [END bigquery_pandas_gbq_read_gbq_simple]
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.. code-block:: python
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import pandas_gbq
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# TODO: Set project_id to your Google Cloud Platform project ID.
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# project_id = "my-project"
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sql = """
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SELECT country_name, alpha_2_code
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FROM `bigquery-public-data.utility_us.country_code_iso`
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WHERE alpha_2_code LIKE 'A%'
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"""
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df = pandas_gbq.read_gbq(sql, project_id=project_id)
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print(df)
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.. note::
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@@ -37,11 +46,21 @@ The ``dialect`` argument can be used to indicate whether to use
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BigQuery's ``'legacy'`` SQL or BigQuery's ``'standard'`` SQL. The
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default value is ``'standard'``.
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.. literalinclude:: ../samples/snippets/read_gbq_legacy.py
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:language: python
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:dedent: 4
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:start-after: [START bigquery_pandas_gbq_read_gbq_legacy]
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:end-before: [END bigquery_pandas_gbq_read_gbq_legacy]
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.. code-block:: python
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sql = """
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SELECT country_name, alpha_2_code
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FROM [bigquery-public-data:utility_us.country_code_iso]
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WHERE alpha_2_code LIKE 'Z%'
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"""
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df = pandas_gbq.read_gbq(
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sql,
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project_id=project_id,
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# Set the dialect to "legacy" to use legacy SQL syntax. As of
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# pandas-gbq version 0.10.0, the default dialect is "standard".
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dialect="legacy",
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)
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print(df)
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* `Standard SQL reference
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<https://cloud.google.com/bigquery/docs/reference/standard-sql/>`__

‎packages/pandas-gbq/docs/writing.rst‎

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Original file line numberDiff line numberDiff line change
@@ -6,11 +6,29 @@ Writing Tables
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Use the :func:`pandas_gbq.to_gbq` function to write a
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:class:`pandas.DataFrame` object to a BigQuery table.
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.. literalinclude:: ../samples/snippets/to_gbq_simple.py
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:language: python
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:dedent: 4
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:start-after: [START bigquery_pandas_gbq_to_gbq_simple]
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:end-before: [END bigquery_pandas_gbq_to_gbq_simple]
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.. code-block:: python
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import pandas
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import pandas_gbq
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# TODO: Set project_id to your Google Cloud Platform project ID.
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# project_id = "my-project"
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# TODO: Set table_id to the full destination table ID (including the
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# dataset ID).
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# table_id = 'my_dataset.my_table'
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df = pandas.DataFrame(
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{
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"my_string": ["a", "b", "c"],
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"my_int64": [1, 2, 3],
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"my_float64": [4.0, 5.0, 6.0],
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"my_bool1": [True, False, True],
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"my_bool2": [False, True, False],
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"my_dates": pandas.date_range("now", periods=3),
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}
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)
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pandas_gbq.to_gbq(df, table_id, project_id=project_id)
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The destination table and destination dataset will automatically be created
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if they do not already exist.

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