23rd June 2016, voters from United Kingdom (UK) voted in the Brexit referendum to leave European Union (EU) with a small majority vote of 51.9 %. The decision to leave EU since joining in 1973 has consequences that are both profound and catastrophic. The post analysis of the referendum found that the issues for Brexit can be categorized into socio-economic factors, geographic division,…
Recent economic recession and Brexit has raised doubts about the relationship with EU among member nations. This paper analyzes the public data from World Bank to determine the impact to the economic development of Ireland since joining the EU on 1st January 1973. The paper shows that EU membership has a positive relationship with the development of Ireland. Economy has transformed…
Living in Dublin, Ireland is amazingly expensive. Residential property prices in Dublin are growing. Yet we all think about buying a home while still wondering whether we might be better off continuing to rent. The data analyst in me wanted to dive deeper, to look back historically, to quantify, to visualize the trends, etc. to help me decide. With all…
The aim of this blog is to assess the quality and characteristics of the diamonds and gain insights about what makes a really good diamond. The data set is from ggplot2. The explanatory data analysis is done in Python and the notebooks are available on my Github. This blog address few important questions such as: What kind of diamonds are…
So much has been said about Proteins, Fat & Calories in recent years, that the single biggest challenge faced when trying to answer the question is how to “separate the wheat from the chaff.” Protein and fats are what our body uses and they all have calorie counts. Too many and we get fat, too few and we starve. In…
It is crucial to learn the methods of dealing with categorical variables as categorical variables are known to hide and mask lots of interesting information in a data set. A categorical variable identifies a group to which the thing belongs. You could categorise persons according to their race or ethnicity, cities according to their geographic location, or companies according to…
I recently took part in a challenge by Hostelworld. The challenge proposed by Hostelworld is to build a recommendation engine for users. Recommendations can save Recommendations can save travellers valuable time, improve their hostel experience, and increase user retention. This challenge will use user information, reviews, and hostel details. This is a link for Exploratory Data Analysis for Hostelworld Challenge.…