/Data_Science_Code_Challenge

Primary LanguageJupyter Notebook

Exploratory Data Analysis and Pricing Model Challenge

Welcome to this data science challenge focused on exploratory data analysis (EDA) and pricing model development for short-term rentals in New York City! The goal of this challenge is to test your skills in solving real-world business problems, applying statistical concepts, and utilizing machine learning for predictive analysis.

Dataset: teste_indicium_precificacao.csv

Objectives:

The primary objectives of this challenge encompass:

  1. Exploratory Data Analysis (EDA):

    • Uncover key insights and relationships within the dataset through exploratory data analysis.
    • Formulate business hypotheses based on the data's main characteristics.

  2. Specific Questions:

    • Address specific questions related to real estate investment and rental pricing.
      • Identify suitable locations for property investment.
      • Explore the impact of minimum nights and annual availability on pricing.
      • Investigate patterns in the textual names of locations.

  3. Pricing Model Development:

    • Develop a predictive pricing model using machine learning techniques.
    • Evaluate the model's performance using relevant metrics.

Configuring the Python Development Environment to run the application

python -m venv venv
# activate your venv if your system is Windows
venv\Scripts\activate
# activate your venv if your system is Unix or MacOS
source venv/bin/activate
pip install -r requirements.txt
python app.py
venv\Scripts\activate