Use SQL to analyse incidents in Austin, Texas in 2016

In the past blog posts I have been studying SQL in order to enhance my skillset. I have selected a bigquery dataset that can be used on a Kaggle Jupyter Notebook. The dataset, which is a recording of incidents in Austin, Texas, can be found here:- https://www.kaggle.com/datasets/jboysen/austin-incidents/data

I created a Jupyter notebook in Kaggle and saved it to my account. The program is written in Python, and the SQL commands are written in Python remarks.

After I created a Jupyter Notebook to analyse this dataset, I imported the libraries that I would need to execute the program:-

1. bigquery to enable Python to work on bigquery datasets,
2. Bq_helper to enable Python to work on bigquery datasets,
3. Numpy to create numpy arrays and perform numeric computations,
4. Pandas to create dataframes and process data,
5. Matplotlib to visualise data, and
6. Seaborn to statistically visualise data.

Once the libraries were imported, I formatted the dataset to work with the bq_helper library.