Solution for Alkemy Challenge - Data Analytics - Python

Introduction

This repository consists in a solution for the challenge required for applying to Alkemy Data Analytics - Python acceleration program.

The project consumes 3 datasets from datos.gob.ar CKAN API with information of libraries, museums and cinemas from Argentina, saves them into csv files, and after normalizing them, populates a PostgreSQL database with 3 different tables:

• Sitios: A merge of the 3 datasets with selected columns formerly normalized.
• Totales: A table with unique value counts of selected columns from the original data: category, source, and province and category merged.
• Cines: A table with the sum of cinemas, screen, seats and registered INCAA spaces, aggregated by province.

Requirements

• Python 3 (tested on Python 3.8.5)
• Git (tested on Git 2.31.1.windows.1)
• PostgreSQL (tested on PostgreSQL 14.1)
• PgAdmin 4 (optional)

Installation (Windows 10)

Open CMD and execute the following commands:

1. Clone this repository into desired directory

   git clone https://github.com/facundofacio/alkemy-python-challenge-solution
   

2. Go to project directory

   cd alkemy-python-challenge-solution
   

3. Create virtual environment

   python -m venv env
   

4. Activate virtual environment

   env\Scripts\activate
   

5. Install dependencies

   pip install -r requirements.txt
   

6. Configure SQLalchemy database settings

   Edit lines 17-21 in \components\settings.ini file as needed:

   USER = postgres
   PASS = admin
   DB_HOST = localhost
   PORT = 5432
   DB_NAME = cultura
   

   • USER: PostgreSQL user
   • PASS: PostgreSQL password
   • DB_HOST: Database host ip (Default localhost)
   • PORT: Database port (Default 5432)
   • DB_NAME: Database name to be created and populated with downloaded data.

Running

In CMD, go to project directory and execute script.py

python script.py