A project showcasing various techniques for visualizing datasets (UCI, KDD, Kaggle, DELVE, StatLib).
-
Updated
Mar 31, 2024 - Jupyter Notebook
A project showcasing various techniques for visualizing datasets (UCI, KDD, Kaggle, DELVE, StatLib).
Generalized Estimating Equations (GEE), Quasi-likelihood under the Independence Model Criterion (QIC), Longitudinal data, Embedded box plots within violin plots with hypertension risk categories, spaghetti plots, aggregate line plots, histograms, faceted-area plots, box and jitter plots. Investigating the impact of lifestyle on health.
evaluate the performance among various algorithmic, hedge, and mutual fund portfolios and compare them against the S&P 500 Index.
Using R, performed statistical analysis and data visualization of life expectancies of United States, Canada, and Mexico, using custom plots and data analysis.
Perform EDA on an air quality dataset. Identify relationships in the data and discover trends in pollutant levels over time
In this project, we will visualize time series data using a line chart, bar chart, and box plots. We will use Pandas, Matplotlib, and Seaborn to visualize a dataset.
Add a description, image, and links to the box-plots topic page so that developers can more easily learn about it.
To associate your repository with the box-plots topic, visit your repo's landing page and select "manage topics."