This is a data analytics report aimed at providing cross-cultural insights through the analysis of survey data from Northern and Southern Europe. The goal of this project is to understand cultural differences and preferences through comprehensive data analytics, focusing on key factors that impact life satisfaction.
The survey data used in this analysis was sourced from IKEA's Life at Home survey.
Python: For data processing and analysisPandas: For data manipulation and cleaningMatplotlibandSeaborn: For data visualizationNumPy: For numerical operation
This heatmap, created using Seaborn, illustrates the correlation between different factors influencing life satisfaction in Sweden and Spain. The plot was configured using Matplotlib. High positive correlations are represented by values close to 1, indicating a strong relationship between the factors.
This radar chart, created using Matplitlib, compares the average scores of key factors affecting life satisfaction between Sweden and Spain. NumPy was utilized for angle calculations. The factors analyzed include security, productivity, hope for the future, relaxation and contentment, and connectedness to others.