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Seaborn is one of the go-to tools for statistical data visualization in python. It has been actively developed since 2012 and in July 2018, the author released version 0.9. This version of Seaborn has several new plotting features, API changes and documentation updates which combine to enhance an already great library. This article will walk thr…
This project applies classical time series decomposition and forecasting methods to monthly airline passenger data for the United States in the 1950s. The objective is to analyze passenger trends and seasonality, build an appropriate forecasting model, and evaluate its predictive accuracy for the year 1960.
This is a wine dataset containing 1599 rows and 12 columns with factors like alcohol, color, PH, residual sugar, sulfur-dioxide was used to determine the quality of wine varying with color.
As a data analyst with strong attention to detail and curiosity, my goal for this project was to dive deep into the dataset and uncover meaningful insights into the factors influencing student performance.
An exploration of the relationship commitment to United Nations Drug Conventions to cocaine seizures (in kgs), economic indicators including GDP, military expenditure as a percentage of GDP and trade ratio as a percentage of GDP, as well as World Governance Indicators (WGI).