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Kaggle: Intro to SQL

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SQL, is a programming language used with databases.
BigQuery: A web service to apply SQL to huge datasets.
In BigQuery each dataset it contained in a corresponding project.

To access a dataset:
Construct a reference to the dataset with the dataset()method. Here's how:


               dataset_ref = client.dataset("hacker_news", project="bigquery-public-data")
dataset = client.get_dataset(dataset_ref)

Then we use get_dataset() method to fetch the dataset.
Every dataset is a collection of tables. Dataset is like spreadsheets.
list_tables method to list the tables in the dataset.
```
tables = list(client.list_tables(dataset))
```

Print names of all tables in the dataset

for table in tables:  
      print(table.table_id)

Fetch a table from reference:

# Construct a reference to the "full" table
table_ref = dataset_ref.table("full")

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

The structure of a table is called schema.
Each SchemaField tells us about a specific column(which is also referred to as field).
NULLABLE means the a column allows NULL values and is the default.

list_rows() can be used to test the first few lines to make sure it's correct, for example:

         # Preview the first five lines of the "full" table
            client.list_rows(table, max_results=5).to_dataframe()

Sometimes databases have outdated descriptions, so it's good to check.