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AirBnB-Spatial-Data-Analysis

An applied spatial data analysis project for AirBnB dataset around Cape Town.

Spatial Point Pattern Analysis

In this part of the assignment, I analyse the locations of the listings in two wards and compare the ward-level information using methods such as quadrat counts, spatial point pattern models etc.

Examples of methods used:

Kernal density smoothing.

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G Function

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F Function

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Ripley's K Function

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Spatial Lattice Data Analysis

In this part of the assignment, I build spatial lag and error models that predict the average price of the listings within all 116 wards using some of the variables provided.

Observed Prices

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Ordinary Least-Squares

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Spatial Lag Model

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