no4_order_data.py

# import libraries
from google.cloud import bigquery

# create a client object
client = bigquery.Client()

# Construct a reference to the "nhtsa_traffic_fatalities" dataset
dataset_ref = client.dataset("nhtsa_traffic_fatalities", project="bigquery-public-data")

# API request - fetch the dataset
dataset = client.get_dataset(dataset_ref)

# construct a reference to the "accident_2015" table
table_ref = dataset_ref.table("accident_2015")

# API request - fetch the table
table = client.get_table(table_ref)

# Print information on all the columns in the "accident_2015" table in the "nhtsa_traffic_fatalities" dataset
table.schema

# Print information on all the columns in the "accident_2015" table in the "nhtsa_traffic_fatalities" dataset
client.list_rows(table, max_results = 5).to_dataframe()


# query
# Query to find out the number of accidents for each day of the week
query = """
        SELECT COUNT(consecutive_number) AS num_accidents,
               EXTRACT(DAYOFWEEK FROM timestamp_of_crash) AS day_of_week
        FROM `bigquery-public-data.nhtsa_traffic_fatalities.accident_2015`
        GROUP BY day_of_week
        ORDER BY num_accidents DESC
        """

# Set up the query (cancel the query if it would use too much of
# your quota, with the limit set to 1 GB)
safe_config = bigquery.QueryJobConfig(maximum_bytes_billed=10**9)
query_job = client.query(query, job_config=safe_config)

# API request - run the query, and convert the results to a pandas DataFrame
accidents_by_day = query_job.to_dataframe()

# Print the DataFrame
accidents_by_day