An interactive dashboard to explore the Bacteria Biodiversity dataset, using Plotly.js to create visualizations

Full-Stack Data Analysis to Build an Interactive Dashboard Exploring the Belly Button Biodiversity DataSet Using Plotly.js, Flask and Heroku

Built an interactive dashboard using JavaScript, Plotly, D3.js, CSS, and Bootstrap.

O VisSE é ferramenta web – o VisSE, Visualization for Search Engine – que disponibiliza técnicas de visualização para a análise exploratória de resultados de pesquisas em motores de busca. Essas técnicas foram elaboradas usando a biblioteca d3.js, e tem como objetivo servir de apoio ao pesquisador o permitindo que utilize visualizações para apoi…

Python Pandas & Matplotlib Analysis of Ride Sharing Data and Pharmaceutical Data

A minimalistic bubble data visualization of Hans Florine's climbs on the Nose

Belly Button Biodiversity

udacity project

Belly Button Biodiversity

Web dashboard plotting data on belly button biodiversity

An interactive dashboard to explore the Belly Button Biodiversity dataset and to display individuals metadata using HTML, Javascript, json and D3.

A CSS time series bubble chart

Interactive Dashboard exploring the Belly-Button-Biodiversity Data | Live on Heroku

A demo application showcasing using LightningChart JS to display Bubble chart.

Dashboard visualizing bacterial population samples. HTML, JavaScript.

This project visualized bacteria data from volunteers' belly button with plotly, which included drop down menu, bar chart, gauge chart, and bubble chart show each volunteer's belly button biodiversity.

A Bubble plot with changing x and y axis using D3.js

Interactive dashboard using a dataset of Belly Button Biodiversity (http://robdunnlab.com/projects/belly-button-biodiversity/)

Engineered a dashboard about how many times people wash their belly button will impact how many germs they will have. Few washes on their belly button will result in a high number of germs they have.

The PyBer Analysis repo contains an analysis of ridesharing and city data using Python, NumPy, Matplotlib, and SciPy by creating line charts, bar charts, scatter plots, bubble charts, pie charts, and box-and-whisker plots. Using Pandas DataFrames and groupby, pivot, and resample functions, the data has been analyzed to determine total rides, tot…