SF Crime Visualization - Kelsey C. Schuster. Web Application for Crime Data Visualization In most large U.S. cities, crime is an unfortunate reality.
The details of this criminal activity have become more readily accessible in recent years, as many cities have made their crime data publicly available through online data portals. San Francisco (SF) is one such city. Here, I use an R script to access SF crime data from 2003-present on SF OpenData via the Socrata Open Data API and SQL-like query language. Using Shiny --- a convenient web application framework for R --- I then create an interactive web app to visualize all crimes committed in SF at a specified date and time.Check out the web apphere. . # Load the RSocrata package for easy API access library(RSocrata) # Set the desired date and make query URL year = "2015" month = "01" day = "01" dateStr = sprintf("%s-%s-%sT00:00:00", year, month, day)
Mapping tweets: How to create your own web app. May 28, 2016 One of the reasons why Twitter has become so popular is because it is a great way to get data for web applications and projects.
Through its Search API, it is possible to find content by issuing a query to Twitter based on a supplied string. The results can then be parsed or displayed as preferred using ancillary tools. The purpose of this tutorial is that you learn how to create an interactive web app that retrieves geolocated tweets and shows them in a map. Sounds cool? Get access to Twitter API To get started, create a Twitter account. Notice that there are some rate limits for the Twitter Search API that you should take into account.
Prepare the code for your app First open an R session (preferably in RStudio) and install the following packages: twitteR, shiny and leaflet. Google News Lab – Mike Reilley. So You Wanna Be A Hack: Jupyter Journalism, Data “R” Viz & Setting Up Like A Python On AWS For Free. Carthago delenda est When Facebook, Uber and the rest of Silicon Valley convinced your mother to fall in love with the internet, they created a new grammar for journalism.
Scripting, storing and visualizing the flotsam is the new literacy. I call it Jupyter Journalism. It’s not difficult. Remember your first Word document? This document shows the steps to create a hack/hacking platform, in the same vein copy editors and writers share Google Docs. There will be three scrolls. These tools are already used in industries with better return on investment. It’s the connection between fielding a story’s lowest level sources, to aggregating from social media and forum sentiment. In college, Extended Parallel Process Model taught me that unfamiliarity can masquerade a carrot and stick. Carthage Must Fall. It’s the First Punic War (264–241 BC) 3 Free Data Visualization Tools for Non-Programmers - Simplified Web Scraping Tutorials! The data visualization trend is growing; however, not everyone is a skilled programmer, or proficient in data visualization.
That matters very little these days, as many programs have been developed to make data visualization more accessible and user-friendly to non-coders. There are at least 3 strong and free data visualization tools one should consider using, but first, consider the following: Real-world Python for data-crunching journalists. Reporters don’t interview human sources without a notebook, and they shouldn’t analyze data without one either.
In this walkthrough we’ll see how to use code instead of visual spreadsheet applications like Excel to keep an audit trail of our data analysis. Like we do for many of our stories and projects at Trend CT. In the hands-on portion, we’ll use the Python programming language to find the biggest recipients of vendor payments from the Connecticut Airport Authority in a format readable by anyone, not just people who know how to write code, called a “notebook.” The main drawback with visual tools is that, while they’re intuitive, they don’t provide a mechanism to show your work step-by-step. (See Appendix B for why we think this is important). The tools we’ll use are the Python programming language, a Python library for statistical analysis called Pandas, and a notebook program called Jupyter.
Difficulty level Challenging. Installing the software Setting up the environment 1. 2. 3. How Data Journalism Changed the University of Florida. Norm Lewis teaches data journalism in a new series of courses at the University of Florida.
Photo by Ryan Jones, University of Florida College of Journalism and Communications The University of Florida College of Journalism and Communications has always been on the leading edge of new technology. But we had been lagging in one important area: data journalism. When Dean Diane McFarlin joined the College in 2013, she was determined to change that. In the past three years, despite the usual snail’s pace of curriculum change, we’ve gone from zero courses to five. "In her first year of teaching both classes, she has lots of students (including many females and people of color) who brim with confidence in their programming skills. " How? Fortunately, we had Mindy McAdams, our Knight Chair for journalism technologies, who has been at the forefront of online journalism since 1200-baud modems were a thing.
Mindy McAdams developed Web Apps courses to teach students code.