The ORDER BY clause in SQL is used to sort query results based on one or more columns. In BigQuery, this clause works just like standard SQL, and using it with Python via the BigQuery client allows for powerful, customizable data sorting.

This tutorial covers:

• Syntax and usage of ORDER BY

• Sorting by one or more fields (ascending/descending)

• Using ORDER BY with Python and BigQuery

• Integration with Pandas

• Tips and common mistakes

✅ Prerequisites

Before running BigQuery queries in Python:

• Google Cloud account and project

• BigQuery dataset and table

• Service account with proper permissions

• BigQuery Python client library installed

Install BigQuery Python Client

pip install google-cloud-bigquery

Step 1: Set Up Authentication and Client

import os
from google.cloud import bigquery

# Set path to service account credentials
os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = "path/to/your-key.json"

# Initialize BigQuery client
client = bigquery.Client()

Step 2: Basic ORDER BY Query

Let’s say you have a table customers in your dataset. Here's a simple SQL query that sorts results by signup date in descending order:

SELECT id, name, signup_date
FROM `your-project.my_dataset.customers`
ORDER BY signup_date DESC

▶️ Step 3: Execute the ORDER BY Query in Python

query = """
    SELECT id, name, signup_date
    FROM `your-project.my_dataset.customers`
    ORDER BY signup_date DESC
"""

query_job = client.query(query)
results = query_job.result()

for row in results:
    print(row.id, row.name, row.signup_date)

⚙️ Sorting Options

Load Sorted Data into Pandas

Use Pandas for further data processing or visualization:

import pandas as pd

df = client.query(query).to_dataframe()
print(df.head())

Example: Multi-Column Sorting

Sort first by country (A–Z), then by signup_date (newest first):

SELECT id, name, country, signup_date
FROM `your-project.my_dataset.customers`
ORDER BY country ASC, signup_date DESC

Python:

query = """
    SELECT id, name, country, signup_date
    FROM `your-project.my_dataset.customers`
    ORDER BY country ASC, signup_date DESC
"""
df = client.query(query).to_dataframe()
print(df)

Example: Sorted and Filtered Query with Parameters

query = """
    SELECT id, name, signup_date
    FROM `your-project.my_dataset.customers`
    WHERE signup_date >= @start_date
    ORDER BY signup_date DESC
"""

job_config = bigquery.QueryJobConfig(
    query_parameters=[
        bigquery.ScalarQueryParameter("start_date", "DATE", "2023-01-01")
    ]
)

query_job = client.query(query, job_config=job_config)
df = query_job.to_dataframe()
print(df)

Tips for Using ORDER BY in BigQuery

⚠️ Common Pitfalls

Full Example: Python + BigQuery ORDER BY

import os
import pandas as pd
from google.cloud import bigquery

os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = "path/to/your-key.json"
client = bigquery.Client()

query = """
    SELECT id, name, email, signup_date, country
    FROM `your-project.my_dataset.customers`
    WHERE email IS NOT NULL
    ORDER BY signup_date DESC
    LIMIT 10
"""

query_job = client.query(query)
df = query_job.to_dataframe()

print(df)

Conclusion

The ORDER BY clause is essential when you want to:

• Sort results by date, name, or other fields

• Present data cleanly in dashboards or reports

• Combine with LIMIT to get top or recent entries

With Python and BigQuery, sorting data becomes simple and powerful—especially when paired with filtering and parameterized queries.Would you like to continue with a tutorial on how to DELETE rows using Python and BigQuery, or perhaps move into more advanced SQL with JOINs?