Nevada AirBnB data analysis

Following libraries were used for the analysis

matplotlib=3.3.4
seaborn=0.11.2
pandas=1.1.5
numpy=1.19.5

If you don't have above packages then you can use following commands to install them

conda install matplotlib
conda install seaborn
conda install pandas
conda install numpy

This project investigates the mean price distributions published by AirBnB for Clark County, Nevada. Following questions were investigated in this project.

a) What is the area that shows the lowest median price?

b) What area provides a higher number of rental properties?

c) How do prices change for each area of Clark County throughout the year?

In this project, a Jupyter notebook includes all the analysis, and the data used are stored in the 'data' subfolder.

Can use the notebook to run to regenerate the plots. You can use the following Medium post to see an overview of the things found in this study.

How to get the best rental price for your next stay in the silver state ?

1.0 The ‘City of Las Vegas’ area shows the lowest median rental price as shown in Figure 4 in the jupyter notebook included.

2.0 But if you look at available ‘Room types’ then ‘Unincorporated area’ provide provides the higher count of rental properties for each room type as shown in Figure 5 in the Jupyter notebook included.

3.0 In the Jupyter notebook Figure 6 shows the median price for a ‘Hotel room’ on Airbnb is slightly higher than August, September, and October months compared to a ‘Private room’. Therefore, pick a hotel in those months if you have an option between them. Also, Figure 6 shows it is a good idea to avoid ‘City of Mesquite’ if you are trying to find a lower rental price because the median rental is highest in the area throughout the year.

Airbnb

I want to thank Airbnb for sharing data and valuable comments from Udacity reviewers for the analysis.

MIT