RBD212

PythonDataScienceHandbook

Python Data Science Handbook: full text in Jupyter Notebooks

seaborn

Statistical data visualization in Python

DataSciencePython

common data analysis and machine learning tasks using python

ggpy

ggplot port for python

flask_jsondash

:snake: :bar_chart: :chart_with_upwards_trend: Build complex dashboards without any front-end code. Use your own endpoints. JSON config only. Ready to go.

data-visualization

Misc data visualization projects, examples, and demos: mostly Python (pandas + matplotlib) and JavaScript (leaflet).

dash-cytoscape

Interactive network visualization in Python and Dash, powered by Cytoscape.js

data_visualization

A collection of my data visualizations, mostly in Python.

squarify

Pure Python implementation of the squarify treemap layout algorithm

DataVisualization

Tutorials on visualizing data using python packages like bokeh, plotly, seaborn and igraph

ggnet

Network visualization with ggplot2

chorogrid

A python script to produce choropleths and colored square- and hex-grid maps

statebins

Alternative to choropleths of US States ala http://bit.ly/statebins

interactive-and-responsive-svg-map-of-us-states-capitals

SVG map of the United States that allows you to hover each state to see its capital

A-Deep-Learning-Based-Illegal-Insider-Trading-Detection-and-Prediction-Technique-in-Stock-Market

Illegal insider trading of stocks is based on releasing non-public information (e.g., new product launch, quarterly financial report, acquisition or merger plan) before the information is made public. Detecting illegal insider trading is difficult due to the complex, nonlinear, and non-stationary nature of the stock market. In this work, we present an approach that detects and predicts illegal insider trading proactively from large heterogeneous sources of structured and unstructured data using a deep-learning based approach combined with discrete signal processing on the time series data. In addition, we use a tree-based approach that visualizes events and actions to aid analysts in their understanding of large amounts of unstructured data. Using existing data, we have discovered that our approach has a good success rate in detecting illegal insider trading patterns. My research paper (IEEE Big Data 2018) on this can be found here: https://arxiv.org/pdf/1807.00939.pdf

ColorHistogram

Simple demos of Color Histogram (Python).

Python-Data-Analytics-and-Visualization

Code repository for Python Data Analytics and Visualization by Packt

rworldmap

R package for mapping country data

PDFNLT-1.0

Tools for Natural Language Text aware PDF structure analysis

pynetviz

Python Network(Graph) Visualization

PDF-Report-to-Excel

Python code to crawl data from PDF report (Argus FMB) into a structured excel file for data analysis

utl_convert_pdf_tables_to_sas_tables

Converting tables in a pdf document to database tables. Data analytics. Machine learning. R, Python, Perl and SAS. Keywords: sas sql join merge big data analytics macros oracle teradata mysql sas communities stackoverflow statistics artificial inteligence AI Python R Java Javascript WPS Matlab SPSS Scala Perl C C# Excel MS Access JSON graphics maps NLP natural language processing.

GISfinal

R code for formatting/manipulating US Census Bureau Business Patterns Data by Zip Code (1998-2012).

Law_Text_Segmentaion

Structured data extraction from unstructured text based on law documents

USFederalBudget

Python and Processing code to animate US Federal Budget over time as growing and shrinking pie charts

EnergyMarketHeatmap

R heat maps for regional energy markets

ThinkfulAssignments

Forms-in-Django

Basic drop down menu form in Django.

pieCharts

Sales-Data-Analysis

We have sales data which is unstructured, so, we first make it structured and do analysis.