janegao2019 Goto Github PK

assignment-2

Materials for the second homework assignment

barefoot

Java library for integrating the map into software and services with state-of-the-art online and offline map matching that can be used stand-alone and in the cloud.

cactuslemonade.github.io

cpln692-week1

Introduction to Javascript and the tools of the trade

cpln692-week2

Introduction to Javascript: Programming with Functions

data-viz-template

A template for including data visualizations in a Jekyll-powered blog with Github Pages.

ds-class-intro

hello-world

My first practice project on Github!

jane.github.com

FridayGithubWorkshop

janegao2019.github.io

Use this template if you need a quick developer / data science portfolio! Based on a Minimal Jekyll theme for GitHub Pages.

masterclass2018

meyersoniurworkshop

FridayGithubWorkshop

mobility-data-specification

A data standard for Mobility as a Service Providers who work within in the City of Los Angeles

paasbaan-crime-prediction

Crime classification, analysis & prediction in Indore city

philadelphia-shootings-app

A Panel-based dashboard showing recent shootings in Philadelphia using Altair, Folium, and Holoviews

phl-open-geodata

Providing geospatial data in alternate formats

rides-python-sdk

Uber Rides Python SDK (beta)

rmarkdowns_to_github

search-script-scrape

101 real world web scraping exercises in Python 3 for data journalists

sf-crime-analysis

Spatial and Time Series Analysis of San Francisco Crimes

spatial-temporal-analysis-of-crime

Crimes occur everywhere around us, affecting the quality of life and growth of the economy of a society. Although crimes occur everywhere, criminals target familiar areas for them whenever they get the opportunity. Thus, given a data mining approach, it is possible to process data such as the crime type, date, area and so on to find a pattern among these crimes. This could help us predict whether the area is safe or unsafe, for a given time, day and area. By this, we hope to raise the awareness among people about their surroundings and help them be aware and undertake safety measures at the dangerous time periods. This could also be useful to the police department of the area so they can send suitable police force and maintain tight security in crime prone areas and times. Our Data Mining assignment aims at performing Tactical Crime analysis on real-world crimes dataset of Los Angeles in California from 2010 to 2015. To extract frequent patterns of crime on the dataset, we used several techniques and algorithms to generate various graphs to help us analyze the data and be able to predict the crime rates in specific locations at a particular time. We have provided statistical analysis of different crime types with their demographic information.

spatialml_package

This repository stores the spatial ml code

tncstoday

Tool for visualizing the estimate of number of TNC (Uber and Lyft) pickups and dropoffs in San Francisco—by location and by time of day.

week-1

Materials for week 1 of MUSA 620 for Spring 2019

week-10

Web Maps, Observable, and Javascript

week-2

Data Visualization Fundamentals

week-3

Geospatial Data Analysis and GeoPandas

week-4

More Interactive Data Viz (hvplot), Getting Started with APIs

week-5

Getting Data Part 1: the Census and Twitter APIs

week-6

Getting Data Part 2: Web Scraping