by Sarah Mason
Exploratory Data Analysis is an important type of analytics. This provides a summary of data to give understanding of contents. The summary includes counts of columns and rows, and statistics. Using an available dataset on world happiness from 2018, the data tools from excel can create a story of happiness by using exploratory data analysis to create a summary.
Excel is common and a great app for basic analysis. Using a public dataset on happiness, exploring the data about global analysis is covering the summation of the set for a first step to know about which places are happy.
Figure 1: Exploratory Analysis of Global Happiness 2018
The analysis shows that Finland has the highest happiness and Burundi has the lowest happiness. The summary chart shows a wide deviation for life expectancy and social support. Focusing analysis on healthy life expectance and social support may show insights into happiness due to finding patterns of deviation form the average value for all countries. Calculating and reviewing summary data to understand data is a way to form insight and hypotheses to test. This can lead to finding valuable relationships and patterns to apply for data-driven solutions to make happiness.
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Sarah Mason is a Healthcare Data Analyst and Founder Sarah Mason Consulting LLC.
Dataset found here: https://www.kaggle.com/datasets/cssouza91/hapiness?select=2018.csv
