There are 2 repositories under scatter-plot topic.
Beautiful visualizations of how language differs among document types.
:chart_with_upwards_trend: :bar_chart: Introduces geom_pointdensity(): A Cross Between a Scatter Plot and a 2D Density Plot.
Interactive 2D scatter plot widget for Jupyter Lab and Notebook. Scales to millions of points!
Plot in the terminal using braille dots.
:full_moon_with_face: Lottery prediction besides of following "law of proability","Probability: Independent Events", there are still "Saying "a Tail is due", or "just one more go, my luck is due to change" is called The Gambler's Fallacy" existed.
Scalable WebGL-based scatter plot library build with Regl
Show plotly graph in grafana panel
Present your data as an effective and compelling story
Easy-to-Use Apple Vision wrapper for text extraction, scalar representation and clustering using K-means.
Data visualization is the visual presentation of data or information. The goal of data visualization is to communicate data or information clearly and effectively to readers. Typically, data is visualized in the form of a chart, infographic, diagram or map.
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 :bar_chart: :moneybag:
Simple responsive CSS scatter plot chart
Beyond Outlier Detection: LookOut for Pictorial Explanation
Sonification of multivariate datasets - SuperCollider, Electron, React-Redux
Routines for exploratory data analysis.
Jupyter Scatter Tutorial (that was first presented at SciPy '23)
Data preprocessing is a data mining technique that involves transforming raw data into an understandable format.
Different modeling techniques like multiple linear regression, decision tree, and random forest, etc. will be used for predicting the concrete compressive strength. A comparative analysis will be performed to identify the best model for our prediction in terms of accuracy. The best model will be helpful for civil engineers in choosing the appropriate concrete for bridges, houses construction.
This project implements a personalized apparel recommendation engine using content-based search with the Amazon API, NLTK, and Keras libraries.
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.
Spatial Data Analysis using different statistical methods
[MATLAB] An improved box plot that shows the data-points along with the median and the quartiles.
Google Charts Extension for Yii 2
Scripts for visualizing astronomy data using Blender.
CSBB - Computational Suite For Bioinformaticians and Biologists
Source code for UIST 2017 paper "AirCode: Unobtrusive Physical Tags for Digital Fabrication". C++ Computational Camera Imaging code, and MATLAB robust decoding implementation.
Graphs, plots and maps made using python.
A fully customizable ready to use scatter graph UI package for React.