Collection of Databricks and Jupyter Notebooks

Tutoriales de cursos de Platzi hechos en Jupyter Notebooks.

This project focuses on scraping data related to books by their genre from the "Books To Scrape" website; performing necessary transformations on the scraped data and then analyzing & visualizing it using Jupyter Notebook and Power BI.

This project automates the Python ETL process through GitHub Actions. The updated data is then analyzed and visualized with Jupyter Notebook and Power BI, respectively, to generate powerful insights

This project focuses on scraping data related to Japanese Whiskey from the Whiskey Exchange website; performing necessary transformations on the scraped data and then analyzing & visualizing it using Jupyter Notebook and Power BI.

This project focuses on scraping all the service locations across Australia and their associated attributes from "Cleanaway" website; performing necessary transformations on the scraped data and then analyzing & visualizing it using Jupyter Notebook and Power BI.

This project focuses on scraping data related to Pokémons from a complete Pokédex; performing necessary transformations on the scraped data and then analyzing & visualizing it using Jupyter Notebook and Power BI.

The project focuses on analyzing salaries and various other in-game metrics of top NBA basketball players from 2005-14 by performing exploratory data analysis with Python and Jupyter Notebook and by visualizing the data in an insightful dashboard made with Power BI

This project focuses on scraping data related to video games from the GameRevolution website; performing necessary transformations on the scraped data and then analyzing & visualizing it using Jupyter Notebook and Power BI.

This project focuses on scraping student properties related data from the UK Student Accommodation website; performing necessary transformations on the scraped data and then analyzing & visualizing it using Jupyter Notebook and Power BI.

Análise de Crédito de Cliente usando ferramentas de análise e visualização de dados como: Power Bi, Excel, Power Point, Python, Jupyter Notebook, análise feita no período de 12 meses entre homens e mulheres de diferentes idades e escolaridades.

This project focuses on scraping all the beers related information available on the BeerWulf website by using its backend private API; making necessary data transformations on the scraped data and then, analyzing & visualizing the data with Jupyter Notebook and Power BI.

This project focuses on scraping famous quotes and their related data from the GoodReads website; performing necessary transformations on the scraped data and then analyzing & visualizing it using Jupyter Notebook and Power BI.

This project focuses on scraping all the quotes and their related data from the "Quotes To Scrape" website; performing necessary transformations on the scraped data and then analyzing & visualizing it using Jupyter Notebook and Power BI.

This project focuses on scraping all the products and their related info from the "There You Go" website; performing necessary transformations on the scraped data and then analyzing & visualizing it using Jupyter Notebook and Power BI.

This project focuses on scraping all the service locations across Australia & New Zealand and their associated attributes from "Suez" website; performing necessary transformations on the scraped data and then analyzing & visualizing it using Jupyter Notebook and Power BI.

This project focuses on scraping data related to cafes and coffee shops in London, England from the Yellow Pages (Yell.com) website; performing necessary transformations on the scraped data and then analyzing & visualizing it using Jupyter Notebook and Power BI.

Databricks ETL Pipeline for retrieving and processing NI TestStand test results, featuring a well-documented notebook for ETL operations, Data Lake for storage, Spark SQL+Python for transformations, and Power BI as the final visualization of factory metrics.

World Health Organization (WHO) crude suicide rates per 100,000 by demographics. Data profiling and statistical tests contained in the Jupyter Lab notebook. Data visualization using Power BI. Data taken from the WHO (https://www.who.int/data/gho/data/themes/mental-health/suicide-rates)