Real Estate Data Analysis: Miami and Los Angeles

Project Overview

This project aims to analyze real estate data for Miami and Los Angeles to uncover investment insights. It involves data collection, cleaning, and descriptive analytics, using Excel and Tableau as the two main tools. We collected real estate listings from redfin.com, transforming raw data into actionable insights for potential real estate investors.

Motivation

The motivation behind this project is to provide concrete, data-driven advice to real estate investors looking to make informed decisions in the Los Angeles and Miami markets. By applying rigorous data cleaning methodologies and descriptive analytics, we aim to reveal patterns and trends that can guide investment strategies.

Project Structure

The project is divided into two parts:

Part A: Data Collection and Cleaning

• Data Source: Real estate listings from redfin.com for Miami and Los Angeles areas.
• Excel Workbook (real_estate_data.xlsx): Contains multiple sheets, each representing a step in the data cleaning process, from consolidating raw data to cleaning formats and addressing data quality issues.

Data Cleaning Process

• Consolidation: Merging data from various areas into a single, cohesive dataset.
• Standardization: Aligning column formats and data types across the dataset to ensure uniformity.
• Quality Control: Identifying and rectifying inconsistencies, missing values, and outliers to improve dataset reliability.
• Enrichment: Augmenting the dataset with calculated fields like $/SQFT for deeper analysis. These steps were critical in transforming the raw listings into an analytically valuable dataset, ready for further exploration and visualization.

Part B: Descriptive Analytics and Reporting

• Tableau Workbook (descriptive.twbx): Utilizes the cleaned data to create dashboards, tables, and charts. This part focuses on visualizing the behavior of the real estate market in the selected areas, providing a narrative that supports investment decision-making.
• Final Report (report.pdf): A comprehensive document summarizing the project's findings. It integrates the visualizations from Tableau with a narrative that outlines actionable insights for real estate investors.

Getting Started

To explore the project, start by opening the real_estate_data.xlsx in Microsoft Excel to review the data cleaning process. Then, use Tableau Desktop to interact with the descriptive.twbx for in-depth analysis and insights. Finally, read through the report.pdf for a comprehensive overview of the findings and recommendations.