R tool for automated creation of ggplots. Examines one, two, or three variables and creates, based on their characteristics, a scatter, violin, box, bar, density, hex or spine plot, or a heat map. Also automates handling of observation weights, log-scaling of axes, reordering of factor levels, and overlays of smoothing curves and median lines.

Salary report visualization with D3.js 📊 💰

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.

For easy metric logging and visualization

A bunch of scripts and files that describe topology creation, the topologies, the testing data, real-time graph rendering, table creation and chart creation.

Graphs, plots and maps made using python.

Relational Plot, Two Dimensional Plot, Scatter Plot, Pair Plot, Faceted Plot, Box Plot, Bar Graph, and Density Plot

This is a Data Visualization App that allows the user to upload their dataset in clean format and then perform various Data Visualization like - Line Plots, Scatter Plots, Bar Plots, Box Plots, Violin Plots, Histogram Plots

Data Mining Project: Classification of the Car Evaluation Dataset.

Statistics and probability engineering with python

A Data Science Portfolio for potentially interested employers and recruiters.

This project focusing on statistical analysis to understand and prepare data for potential machine learning applications. The dataset house_price.csv includes property prices in Bangalore. The analysis aims to perform exploratory data analysis (EDA), detect and handle outliers, check data distribution and normality, and analyze correlations.

Beginner-friendly Matplotlib notes with theory, syntax, parameters, examples, and visualizations using Python.

The following table shows changes in bad loans and in provisions for bad loans, from 2005 to 2006, for 19 lending institutions. Verify the reported averages, and find the medians. Which measure is more meaningful, in your opinion? Also find the standard deviation and identify outliers for change in bad loans and change in provision for bad loans

Data Mining: Iris Data Exploration

Creates (scatter, contour, regression, etc.) main plot with upper and right marginal distributions (histogram, boxplot, violin, rug, etc.).

Exploring the Data Cosmos: Journey Through Analytical Insights 📊🔍

This is Glass Type prediction web app

Various small programs: barnsley fern, game of life, christmas tree, langton's ant, bean machine, etc.