This project aims to conduct a comprehensive analysis and comparison of green and yellow taxis in New York City. The analysis includes factors such as trip distance, fare amounts, payment types, and customer preferences to provide insights for optimizing taxi services.
Sentiment Analysis: Zomato uses sentiment analysis to analyze customer reviews and feedback to get an understanding of their satisfaction levels. 3. Menu Optimization: Zomato uses data analysis to optimize the menus of restaurants based on the popularity of dishes and local tastes.
This is a repository that I have created to share my skills, projects and track my progress in Data Science related topics.
displays 2024 election news data from web scraping at detiknews.com
Project description. I developed a weekly credit card dashboard for real-time insights using Excel, SQL, and Power BI. The project included data cleaning, database creation, and visualization. Key insights included identifying top-performing cards and analyzing revenue factors. This demonstrates my proficiency in these tools for accurate analysis.
Projeto de análise de vendas de medicamentos controlados por um período de 12 meses e perfil dos consumidores com base nos dados disponibilizados pela Anvisa.
In-Depth Exploratory Data Analysis on Airbnb Listings NYC 2019 Dataset
Final result for Data Bootcamp 2024
we will delve into the comprehensive analysis of Amazon sales data, aiming to extract actionable insights that can drive business growth and optimization.
Data Analyst
This is a Analytics Project on Sales data of a Coffee Shop. Tool used for analytics is MS Excel, Power Query and Power BI desktop and Service.
For My Work As Senior Power Bi Developer I Face Many Challenges In Dax Functions I push It Here To Remember Them
Newyork Yellow Taxi Trips Record Data
Este repositorio contiene un proyecto de Machine Learning para predecir números de un juego utilizando árboles de decisión. Incluye un script principal (Lottery.py) para cargar datos, entrenar el modelo y hacer predicciones. Se proporciona un archivo de datos (num.csv) como entrada para el modelo.
El proyecto utiliza un modelo de Random Forest para predecir fenómenos utilizando datos proporcionados. El propósito principal es crear una herramienta útil para identificar posibles fenómenos basados en características específicas. Además, el archivo grafic_3d.py tiene como objetivo proporcionar una herramienta para la visualización en 3D.
Optimizing Online Sport Retail Revenue
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