Data Science Softuni 2019 course project

Project requirements - link

The purpose of this research is to find what are the top countries with ski resorts. Is there any statistically significant difference in ski pass prices for adults in this countries. The research is trying to find the features that are mostly affecting the ski pass prices in this datasets. The correlation coefficients of the dataset columns are compared to the whole dataset and separated by country. Maybe different countries have different pricing models for ski pass prices. Also interesting question is what is the best time in the year to visit a ski resort. For this question are used snowfall meteostation information in 4 different resorts: " the Jackson Hole resort,USA","the Snowbird, USA","the Telluride resort, USA" and "the Whistler-Blackcomb resort,Canada".

In this research we will try to find a country for a winter vacation. Maybe the top countries with ski resorts will be the countries that have The Apls in their territory - France, Switzerland, Monaco, Italy, Liechtenstein, Austria, Germany, and Slovenia. The research will try to find the cheapest countries with great ski slopes. Another point of view will be the overall rating for this countries. The prices could be very cheap somewhere, but this could be because the overall rating is low. The time when the customer is visiting the resort is also crucial, to enjoy the maximum fresh snow. The data from the meteostations combined to try to answer this question.

The following code shows the loading of the following datasets, gathered from "Kaggle" :

• dataset Ski Resorts Daily snowfall - snowfall in USA and Canada ski resorts (separated on 4 csv files) [1]. - the dataset is from "Kaggle", which is webcreaped from OnTheSnow.com
• dataset World Ski Resorts [2] - contains rating and prices of ski resorts all over the world; Downloaded from "kaggle", previously webscraped from http://www.skiresort.info