Analysis

I utilized SQL for all three Datasets in order to better understand the three neighborhoods I investigated.

within the Dataset for City of Pittsburgh Water features, I conducted a search of the named water features and queried 'Spray' features, and 'Decorative' water features, utilizing the following codes

ELECT * FROM ebellamy.table_513290a6_2bac_4e41_8029_354cbda6a7b7_2
WHERE feature_type ilike 'spray'

and

ELECT * FROM ebellamy.table_513290a6_2bac_4e41_8029_354cbda6a7b7_2
WHERE feature_type ilike 'decorative'

With City of Pittsburgh Pools, while isolated from the rest of the water features of the other dataset and not really needing to be queried, I still ran the following code

ELECT * FROM ebellamy .table_5cc254fe_2cbd_4912_9f44_2f95f0beea9a_1
WHERE feature_type ilike ‘pool’

Lastly, with the Pittsburgh Neighborhoods dataset, I queried the neighborhoods of East Liberty, on the Eastside; Observatory Hill, on the Northside; and Elliott, on the Southside, with the following code.

SELECT * FROM ebellamy.pittsburgh_neighborhoods

WHERE HOOD ILIKE 'OBSERVATORY HILL'

OR HOOD ILIKE 'EAST LIBERTY'

OR HOOD ILIKE 'ELLIOTT'