Name: Sebastian Sanchez Bernal
To solve this porblem I used postgreSQL in Heroku, with the python library sqlalchemy. In order to run my code I set a .env file with a link (heroku URI) that looks like:
DATABASE_URL=postgres://<username>:<password>@<hostname>:5432/<database_name>
The file that I ran in order to perform all the operations was main.py.
The other two python files (data_ingest.py and data_structure.py) contain the classes that perform all the operations in order to clean the data. All this file can be found in the src directory. Finally I prepared a .conf file to run PostgREST locally. The strucutre of this file is:
db-uri = "postgres://<username>:<password>@<hostname>:5432/<database_name>"
db-schema = "public"
db-anon-role = "<user>"
Both .env and .conf files are not in the repository.
In order to run postgREST we can call postgrest in our local environment:
postgrest <file_name>.conf
And we can call the REST api with
curl http://localhost:3000/<table_name>
My results for women in government are:
women_in_government
[{"date":"September 2020","valueInThousands":544.5},
{"date":"October 2020","valueInThousands":544.1},
{"date":"November 2020","valueInThousands":542.2},
{"date":"December 2020","valueInThousands":534.9},
{"date":"January 2021","valueInThousands":532.6},
{"date":"February 2021","valueInThousands":540.6},
{"date":"March 2021","valueInThousands":547.6},
{"date":"April 2021","valueInThousands":553.8}]
My results for the ratio between production employees and supervisor employees is:
ratio_table
[{"name":"production_employees","value":423866},
{"name":"supervisor_employees","value":42912},
{"name":"ratio","value":9.877563385533184}]
Note: All the data for this exercise comes from https://download.bls.gov/pub/time.series/ce