Python fetches earthquake data from an API, storing it in both CSV and PostgreSQL (Docker). Jupyter Notebook will be used for future data visualization.

LinkedIn Job Scraper is a Jupyter notebook that scrapes job postings from LinkedIn, extracts key details, and saves them in a CSV file. It is designed to handle rate limiting also.

Este repositório está sendo utilizado pela equipe de analistas e cientistas de dados do projeto. As análises estão sendo conduzidas principalmente através de Jupyter Notebooks, com a geração de insights por meio de gráficos. Os arquivos CSV tratados estão disponíveis para referência.

Loan Eligibility Prediction Model: A machine learning application to predict loan approval based on applicant data. Includes a web interface for submitting loan applications and receiving predictions. Built with Python and Jupyter Notebook.

A CLI tool to convert CSV / Excel / HTML / JSON / Jupyter Notebook / LDJSON / LTSV / Markdown / SQLite / SSV / TSV / Google-Sheets to a SQLite database file.

Diferentes proyectos en Jupyter Notebook

This repository is a collection of Jupyter Notebooks featuring data analysis, cleaning, CSV exports, SQL files, and a database diagram image related to police datasets. Explore various data analysis and manipulation techniques used to handle police-related datasets.

The jupyter notebooks provided in this project while being based on IIIF repositories, extract metadata and images, creating a CSV file representing the dataset as a result. These are examples of exploitation that can serve as a basis for further development.

A trained ML model for prediction of house prices in IOWA using Random Forest Regression technique

Have you always wanted to make visuals of pokemon data? I found a csv file that has stats on most of the pokemon and I used python, seaborn and matplotlib to make some cool visualizations. This work was sampled from a cool tutorial on seaborn's great visualizations(https://elitedatascience.com/python-seaborn-tutorial#step-1). This covers a good …

This is an assignment for HHA 507 to familiarize yourself with Jupyter Notebook (Google Colab) and practice data acquisition techniques

Embarking on Mars data exploration! Using Jupyter Notebooks, I'll scrape Mars news and weather details. Firstly, I'll extract titles and preview text from the Mars News site using Beautiful Soup. Then, I'll dive into Mars weather data, analysing temperatures, atmospheric pressure, and more.

Contenido completo del curso

Jupyter Notebook demonstrating ETL (Extract, Transform, Load) pipeline for bank market capitalization data.

Perform the Extract, Transform and Load (ETL) process to create a data pipeline on Kickstarter datasets using Python, Pandas, Jupyter Notebook and PostgreSQL.

ESP8266 wardriving scripts & Jupyter Notebook data visualization tools

This notebook is in the area of People Analytics and includes the analysis of the IBM dataset to identify attrition. Besides attrition I also focus on diversity. I created strategies to reduce attrition.

Perform the Extract, Transform and Load (ETL) process to create a data pipeline on Crowdfunding datasets using Python, Pandas, Jupyter Notebook and PostgreSQL.

Executed an ETL process from an excel file using Python, Jupyter Notebook, and SQL.