Learn Python for Real Estate App Development

Learn Python for Real Estate App Development

Table of Contents

1. Introduction
2. Overview of the Web App
3. Getting Started with Google Colab
4. The Power of Streamlit
5. Creating the Home Page
6. Adding Property Metrics
   • Total Number of Properties
   • Average Price
   • Average Days on Market
   • Price per Square Foot
7. Creating Visual Charts
   • Days on Market Histogram
   • Price Box Plot
   • Price per Square Foot Histogram
8. Identifying Potential Opportunities
   • Additional Bedrooms
   • Accessory Dwelling Units
9. Exporting Features
   • Downloading the Data Frame
10. Conclusion

Introduction

In this article, we will guide You through the process of building your own web app that analyzes market deals from Redfin. With this web app, you will be able to import your downloaded file and automatically generate property metrics, including distribution charts and the identification of potential opportunities. We will walk you step by step through the creation of this web app using Google Colab and Streamlit, making it easy for even those with no front-end coding experience to develop a powerful web application.

Overview of the Web App

Before diving into the technical details, let's start with an overview of the web app we will be building. The main goal of this web app is to provide users with an easy way to analyze market deals from Redfin. By importing their downloaded file, users will be able to view property metrics such as the total number of properties, average price, average days on market, and price per square foot. Additionally, the web app will include visual charts to help users Visualize the data and identify potential opportunities. With these features, users will be able to make more informed investment decisions and find lucrative market deals.

Getting Started with Google Colab

To begin building our web app, we will be using Google Colab, a free tool provided by Google for coding in Python. This will allow us to collaborate on the project and run our Python code within our own space. In order to get started, you will need to Create a copy of the notebook in your own Google Drive. This will give you edit access and allow you to run the code. Once you have set up Google Colab, you can move on to the next steps of building the web app.

The Power of Streamlit

One of the key tools we will be using to build our web app is Streamlit. Streamlit is a powerful framework for building web applications in Python without any front-end coding experience. With Streamlit, we can quickly import the necessary libraries and write code to create our desired web app. This eliminates the need to know HTML or other front-end languages, making it accessible for data analysts, data scientists, and data engineers to create web applications for their teams or wider audiences. In the next sections, we will be exploring various Streamlit features and how to leverage them to build our web app.

Creating the Home Page

The first step in building our web app is to create the home page. This page will serve as the landing page for our web app and provide users with an overview of the app's functionalities. We will use Streamlit to create the home page by importing the necessary libraries and writing code to display the title, description, and main features of the app. By following the step-by-step instructions, you will be able to create an engaging and informative home page for your web app.

Adding Property Metrics

Once we have created the home page, we can move on to adding property metrics to our web app. These metrics will provide users with valuable insights into the market deals they are analyzing. In this section, we will cover four key property metrics: the total number of properties, average price, average days on market, and price per square foot. We will use the data from the imported file to calculate these metrics and display them in an easily understandable format. By incorporating these metrics, users will be able to assess property values and identify potential opportunities more effectively.

Creating Visual Charts

Visual charts are a powerful tool for presenting data in a clear and engaging way. In this section, we will leverage Plotly Express, a Python library for creating interactive visualizations, to add visual charts to our web app. We will create three charts: a histogram of days on market, a box plot of prices, and a histogram of price per square foot. These charts will allow users to visualize the distribution of key metrics and gain deeper insights into the market deals they are analyzing. By following the step-by-step instructions, you will be able to create visually appealing and informative charts for your web app.

Identifying Potential Opportunities

Identifying potential opportunities is crucial when analyzing market deals. In this section, we will focus on two specific opportunities: additional bedrooms and accessory dwelling units (ADUs). By analyzing the data from the imported file, we will identify properties that have the potential for adding additional bedrooms or ADUs. We will use specific ratios and criteria to determine if a property is suitable for these opportunities. By implementing this feature, users will be able to identify properties with Hidden potential and explore additional ways to increase cash flow and profitability.

Exporting Features

Once we have identified potential opportunities, we need to export our features so that users can further analyze the data or integrate it into other tools. In this section, we will export the features we have created as a CSV file, allowing users to download the data and work with it outside of the web app. By providing this functionality, users will have more flexibility in analyzing and utilizing the data for their investment decisions.

Conclusion

In conclusion, building a web app to analyze market deals from Redfin is a powerful tool for real estate professionals and investors. By leveraging tools such as Google Colab and Streamlit, we can create a user-friendly and informative web app that provides valuable insights and helps users make more informed investment decisions. By following the step-by-step instructions in this article, you will be able to build your own web app and unlock the potential of market deal analysis from Redfin.