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38 public repositories
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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…
Chart.js Box Plots and Violin Plot Charts
👁 vioplot
Development version of vioplot R package (CRAN maintainer)
The project aims to perform various visualizations and provide various insights from the considered Indian automobile dataset by performing data analysis that utilizing machine learning algorithms in R programming language.
In this data set we have perform classification or clustering and predict the intention of the Online Customers Purchasing Intention. The data set was formed so that each session would belong to a different user in a 1-year period to avoid any tendency to a specific campaign, special day, user profile, or period.
A simple workaround to produce violin plot with highcharts.js
👁 surgery-PROMs-score-and-weather-conditions-data-visualizations
Two Data Visualization about the relationship between PROMs scores after surgery and weather conditions on the day of compilation. Made with the matplotlib library.
Comprehensive Machine Learning Techniques: Metrics, Classifiers, and Evaluation
A development version of the vioplot R package. This has been migrated to "vioplot" as version 0.3.
The objective of this work is to investigate factors affecting borrower rate and loan amount.
A simple example on creating violin plots using Seaborn library in Python
📓 Visualization and training a basic ML model on the Iris dataset
Employed hyper-parameter tuning (Gridsearch CV) and ensemble methods (Voting Classifier) to combine the results of the best models. Data Cleaning and Exploration using Pandas. Stratified Cross Validation to model and validate the training data
📊 Upload CSV/Excel files to generate boxplots, run ANOVA, and auto-calculate Tukey HSD — no coding needed.
Python EDA and Visualization Using , Matplotlib, Seaborn,Plotly and Bokeh. Map visualization using Folium
Visualization using Matplotlib and Seaborn
Strip Plot, Grouping with Strip Plot, Swarm Plot, Box and Violin Plot, placing plots together, Combining the plots, Joint Plot, Density Plot, Pair Plot
EDA - Pre processing | Feature Engineering
R package to allow the storage of several datasets of RNAseq data and the generation of graphical representations of genes in those datasets (violinplots or heatmaps) with a shiny app
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