Tuesday, April 7 | 12 - 1:30 pm

Introducing Python

You’ve heard about how languages like Python and R can help extend the reach of your reporting, or maybe you’ve started working through a book or an online tutorial on your own and would like a more social learning experience. This hour and a half session will introduce yo the basics of Python — we’ll explore its syntax, its built-in objects and then tour some of the packages that make it so useful for journalism. We will leave you with some assignments to work on after the session that will help you refine your skills. The session will be led by and Mark Hansen, Professor and Director of the Brown Institute at Columbia Journalism School.

Tuesday, April 14 | 12 - 1:30 pm

Parsing Data and Creating Basic Graphs (Python, Pandas, Geopandas, Matplotlib)

We know subway usage in New York City has decreased dramatically during the current COVID-19 outbreak. But by how much exactly? And is it the same all over the city? This tutorial will guide you through the basic steps of parsing MTA turnstile data and giving it geographic attributes. Our final product will be a Jupyter Notebook with maps and graphs exploring the magnitude and extent of this decrease, as well as its correlation with income levels across the city. In this tutorial we will use Python through Jupyter Lab, along with the pandas, numpy, matplotlib and geopandas libraries. The session will be led by and Juan Francisco Saldarriaga, Senior Data & Design Researcher at the Brown Institute for Media Innovation.

Tuesday, April 21 | 12 - 1:30 pm

Working with Census Data and Creating a Map Highlighting Age in NYC

This tutorial will guide you through the process of downloading census data and joining it to its corresponding shapefile to create a map of New York City that highlights vulnerable populations (in an age of COVID-19). In the process you will learn how to join by attributes, how to perform field calculations within QGIS, and how to create categorical as well as quantitative maps. The session will be led by and Michael Krisch, Deputy Director of the Brown Institute for Media Innovation.

Tuesday, April 28 | 12 - 1:30 pm

Introduction to Web Scraping with Python

This tutorial covers the basics of “web scraping,” the act of extracting data from web pages. Whether it’s pulling COVID-19 case counts from state-level health departments or aggregating information about Obama-era commutations and pardons, web scraping is one of those skills that data journalists need to use frequently. Our tool of choice will be Python, as the language is nearly tailor-made for this activity. Our session will begin by reviewing the structure of HTML, the markup language that undergirds the web, and exploring how to use Python to retrieve and parse web pages, and extract data needed for your investigations. We will learn to use the Python library BeautifulSoup, and work a real world example, scraping data from the NYC Worker Adjustment and Retraining Notification website. Finally, we will switch Python libraries and look at how Selenium can be used for more advanced scraping projects that require site interactions such as filling out forms and clicking buttons. The session will be led by and Alex Calderwood, Staff Writer at the Brown Institute for Media Innovation.

Tuesday, May 5 | 12 - 1:30 pm

Intermediate Python

We will take some time and introduce Python as a tool for reporting, for finding stories. In previous sessions, we’ve tried to demonstrate how Python can be a useful “interpreter” — helping you gather data from the web, merge information from different sources, and produce insightful maps and graphics. In our next session, we will spend our time utilizing these various elements to look at a few stories surrounding COVID-19. The pace will be slow and deliberate, digging into powerful packages like pandas, Python’s version of a spreadsheet. We will collect data from APIs (Application Programming Interfaces), and contrast this form of access with our previous “web scraping” lesson. In short, we will pull a lot of concepts together in service of reporting. The COVID-19 data that we will be using include the mobility data sets from Apple, Google and Descartes Labs, tweets referring to the virus, and various tracking services like covidtracker.com and covidtracking.com. We hope that you’re able to join for this slower, deeper dive into Python. The session will be led by and Mark Hansen, Professor and Director of the Brown Institute at Columbia Journalism School.

Tuesday, May 12 | 12 - 1:30 pm

Intermediate GIS (Geocoding and Network Analysis)

This tutorial will guide you through the process of working with a CSV of addresses to generate point data that can be displayed on a map (geocoding). To begin, we will map food retailers that are greater than 6000SqFt in size. We will then perform network analysis, highlighting walking distance to food retailers, and in turn, food deserts. The session will be led by and Michael Krisch, Deputy Director of the Brown Institute for Media Innovation.

Tuesday, May 19 | 12 - 1:30 pm

3D reconstruction with Photogrammetry

In this tutorial we will learn the basics of Photogrammetry - a method used to take measurements and calculate depth using images captured with any camera, including the ones on your smartphone. Photogrammetry can be used to reconstruct objects large and small - from a plate of food to a terrain captured using a drone. We will cover guidelines for photographing an object, and then use the software Agisoft Metashape to process an example. The exported object can later be used for immersive experiences in AR/VR, or embedded into a written article on the web. We will assume no prior knowledge of 3D graphics. The session will be led by and Ziv Schneider, Creative Technologist at the Brown Institute for Media Innovation.

Tuesday, May 26 | 12 - 1:30 pm

Bots

Bots have been part of the information ecosystem for decades. Aside from well-known conversational news bots (“Alexa, give me the news”) or weather bots, there are plenty of other kinds of bots performing journalistic tasks — on Twitter we find @NYT_first_said repeating the first time a word is used in the New York Times, @earthquakeBot tweeting when earthquakes occur in realtime, @everytract methodically displaying satellite images of every Census tract in the US, and @thenexttodie from the Marshall Project reminding us when the next death row inmate is scheduled for execution. In this lesson, we’ll look at bots from two directions — as something to report on and as something to perform journalism with. We’ll focus mainly on Twitter and see how we might spot a bot. We’ll also build a bot that pulls data from a website or API. The session will be led by and Mark Hansen, Professor and Director of the Brown Institute at Columbia Journalism School.

Tuesday, June 2 | 12 - 1:30 pm

What To Do With All That Data

You’ve got data. Lots of data. But it’s often messy, obscure, redundant or simply locked inside obnoxious proprietary file formats. Getting it clean and into the right shape so you can use it for your reporting is often the most excruciating part of the process. In this session, you will learn some basic, yet very powerful tools and techniques for importing, cleaning, transforming and extracting data. You will explore how to import and merge data and tables with Google Sheets, how to clean, transform, and explore data with OpenRefine, and how to extract tables from PDFs with Tabula. So join us, and discover some fundamental key concepts in data structures and analysis that will inform and enhance your reporting in our data driven world! The session will be led by and Juan Francisco Saldarriaga, Senior Data & Design Researcher at the Brown Institute for Media Innovation.

Tuesday, June 9 | 12 - 1:30 pm

An Introduction to UNIX Tools (Why? for the love of Pete, why?)

In this session we step back to a simpler time when we interacted with computers through a handful of typed commands. Specifically, we'll deal in some pretty old magic — UNIX. While introduced in the late 1960s, the UNIX operating system lives underneath MacOS as well as the recent version of Windows. At one level, you can think of UNIX as a collection of tools to help you manipulate programmatically the basic stuff of a computer. We'll work with files and folders and running jobs. We will spend an hour and a half showing how UNIX commands can help you with your reporting — How do you find patterns of text in a file? How do you rummage though a dump of documents? Can you summarize the content of a file? UNIX tools slice and dice and tabulate, and do these things efficiently. Truly this session will offer you the keys to the kingdom! The session will be led by and Mark Hansen, Professor and Director of the Brown Institute at Columbia Journalism School.

Tuesday, June 16 | 12 - 1:30 pm

Introduction to Web Mapping

Old maps, new maps, red maps, blue maps! Interactive maps are everywhere - on our phones, our screens, open-source and easy to use. But, have you ever wanted to create your very own map? Now’s your chance to join the party, jump In the race, and build a presidential election map! We will use Mapbox, and its companion Mapbox GL JavaScript library, to explore how web maps are styled and embedded into a website. You will be amazed by their interactive capabilities, delighted by their popups, and experience how deep and engaging the world of map-making can be. So join us, and you will learn how to beautifully display your spatial data! The session will be led by and Juan Francisco Saldarriaga, Senior Data & Design Researcher at the Brown Institute for Media Innovation.

Tuesday, June 30 | 12 - 1:30 pm

Introduction to Data Visualization

Graphical (or pictorial) presentations of data have become an almost essential part of journalistic practice. Data visualization helps us see patterns in data, and is an important tool for finding stories. Also, outlets like The New York Times, The Washington Post, and FiveThirtyEight are publishing data visualizations that push the very idea of storytelling, creating new data-driven ways to inform and entertain. In this edition of At Home with the Brown Institute, we will discuss basic data visualizations — guiding you through the types of graphics popular among news outlets. We will then get practical, introducing you to a powerful tool for making graphics, ggplot. Again, our language of choice is Python. Along the way, we will also help you think critically about visualizations, making you a better consumer of data graphics. The session will be led by Mark Hansen, Professor and Director of the Brown Institute at Columbia Journalism School and Juan Francisco Saldarriaga, Senior Data & Design Researcher at the Brown Institute for Media Innovation.

Tuesday, July 21 | 12 - 1:30 pm

Reporting on Covid-19: How cities and states make decisions about the virus

So you want some public records — think government audits, memoranda, internal emails or data — for your journalism project. But how do you start? And once you get what you want — after waiting weeks or months and sometimes paying fees — how do you structure and present what you found? We'll show you how to think about local, state and federal open-records laws and the Freedom of Information Act from a journalists' perspective, starting from when you file the request, negotiate for records and then ultimately obtain the documents. In this edition of At Home with the Brown Institute, we'll walk through some best practices from newsroom and FOIA experts across the country, from classified national security records all the way to local government budgets and all documents in between. The session will be led by and Derek Kravitz, Professor at the Columbia Journalism School's Stabile Center for Investigative Journalism and a Brown Magic Grant awardee..

Tuesday, August 18 | 12 - 1:30 pm

How to Write a Tweetorial

Twitter threads have become a popular medium for explaining technical concepts, expounding on everything from dung beetle navigation to opposition research to why our fingertips get wrinkly in the bath. Twitter threads are incredibly popular among journalists as well, who use the medium to break or summarize a story, explain something they’ve learned while reporting, or build an audience for their beat. In this workshop, you'll learn how to engage a Twitter audience on a topic of your own expertise. We've been studying these Twitter tutorials, or "tweetorials", as an emerging communication genre with a set of strategies unique to the form. We will break down examples to show you what makes a tweetorial engaging and clear, and then do writing and revision exercises using strategies we have developed. If we have time, we'll test-run some automatic feedback tools we've been developing to help writers create an engaging and intriguing first tweet that draws readers in. The session will be led by Katy Ilonka Gero, PhD candidate in Computer Science, Columbia University Lydia Chilton, Assistant Professor of Computer Science, Columbia University and Tim Requarth, Journalist and Lecturer in Science & Writing at New York University.