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Project Description

In this project, I analyzed the pricing of various property listings in Melbourne. The aim of the analysis was to identify the factors that drive the pricing of properties.

The data was messy, therefore I performed data cleaning before I started the analysis.

I leveraged statistical tests like Pearson Product-Moment Correlation Coefficient, One-way ANOVA and Independent t test to validate some of my findings.

I conducted univariate, bivariate and multivariate analysis to understand the distribution of the variables and how they affected each other.

By the end of the analysis, I identified some variables that drive the pricing of property listings.

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Analysis of property pricing using Python

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