Predictive Price modeling for AirBnb Listings
Budget: $30 – $250 USD
Prepare the data, including data cleaning, transformations, and aggregation.
Store the data in an SQL database.
Query the data to make initial discoveries: develop at least four SQL queries using different command, such as BETWEEN, IS NULL, LIKE, DISTINCT, MIN, MAX, COUNT, GROUP BY, HAVING, ORDER BY, etc.
Visualize the data based on the queries you’ve performed.
Use SPARK to perform an initial predictive model for your data. You may use the same dataset to train and test your model, and you may use a linear regression model.
I recommend using Google Colab to perform your project, as it allows easy installation of the PySpark module.
Title:
Clear and succinct title that describes your project.
Introduction:
Summarize the purpose of the report and summarize the data/subject.
Include important contextual information about the reason for the report.
Summarize your analysis questions, your conclusions, and briefly outline the report.
Body (four sections):
Data Section: Include written descriptions of data and follow with relevant spreadsheets.
Methods Section: Explain how you gathered and analyzed data.
Analysis Section: Explain what you analyzed. Include any charts and visualizations here.
Results: Describe the results of your analysis.
Conclusions:
Restate the questions from your introduction.
Restate important results.
Include any recommendations for additional data as needed.
Deliverables
Final report in word format
Code, including output, in ipynb and PDF format.
Store the data in an SQL database.
Query the data to make initial discoveries: develop at least four SQL queries using different command, such as BETWEEN, IS NULL, LIKE, DISTINCT, MIN, MAX, COUNT, GROUP BY, HAVING, ORDER BY, etc.
Visualize the data based on the queries you’ve performed.
Use SPARK to perform an initial predictive model for your data. You may use the same dataset to train and test your model, and you may use a linear regression model.
I recommend using Google Colab to perform your project, as it allows easy installation of the PySpark module.
Title:
Clear and succinct title that describes your project.
Introduction:
Summarize the purpose of the report and summarize the data/subject.
Include important contextual information about the reason for the report.
Summarize your analysis questions, your conclusions, and briefly outline the report.
Body (four sections):
Data Section: Include written descriptions of data and follow with relevant spreadsheets.
Methods Section: Explain how you gathered and analyzed data.
Analysis Section: Explain what you analyzed. Include any charts and visualizations here.
Results: Describe the results of your analysis.
Conclusions:
Restate the questions from your introduction.
Restate important results.
Include any recommendations for additional data as needed.
Deliverables
Final report in word format
Code, including output, in ipynb and PDF format.