| 7 |
4257 |
Advanced SQL: Working with dates, sub-queries and more |
If you feel comfortable with the Structured Query Language basics that IRE teaches in its boot camps — SELECT, FROM, WHERE, GROUP BY — but are ready to see what else SQL can do, this session is for you. We will cover more advanced ways of manipulating and questioning data, such as date functions, writing sub-queries and other neat tricks. We will use SQLite in the class. This session will be most helpful if: You are comfortable with counting and summing in SQL. |
5 |
2019-03-08 |
2019-03-08 10:15:00 |
2019-03-08 11:15:00 |
0 |
0 |
0 |
Jennifer Peebles, The Atlanta Constitution |
3 |
|
3 |
Advanced SQL: Working with dates, sub-queries and more |
| 16 |
4397 |
Avant garde data viz |
You know all the rules of data viz — north belongs at the top of maps, timelines read left to right, bar charts are used for comparison. Now it's time to break the rules. This panel will explore when and why to break with convention, and when not to. We'll look at the best examples of unconventional data viz and show how you can mix up your own work in new and interesting ways. |
1 |
2019-03-07 |
2019-03-07 11:30:00 |
2019-03-07 12:30:00 |
0 |
0 |
0 |
Scott Klein, ProPublica (moderator); Nonny de la Pena, Emblematic Group; Rachel Binx, Netflix |
1 |
|
3 |
Avant garde data viz |
| 48 |
4398 |
Cyberwar: Investigating hacking by advanced actors |
How to investigate warfare’s newest front: the cyber realm. We'll walk you through getting more information about this secretive world, including tracking down information about who owns what on the internet, disentangling server logs, studying IP addresses and analyzing malware and emails and more in this session. We’ll also talk about some of the tactics advanced hackers have used in the past to penetrate sensitive networks--and how those efforts can provide clues in future attacks. |
6 |
2019-03-09 |
2019-03-09 15:30:00 |
2019-03-09 16:30:00 |
0 |
0 |
0 |
Rob Barry, WSJ; Surya Mattu, The Markup |
1 |
|
3 |
Cyberwar: Investigating hacking by advanced actors |
| 49 |
4216 |
D3 in a reactive world |
In this session, we’ll introduce you to how we bridge the gap between visualization libraries like D3 and the latest component frameworks in JavaScript. We’ll show you how mixing the two can become a powerful way to build reusable chart components that will shortcut your dev time and extend the impact of your work. Students will get a reusable chart template they can take home. This session is good for: people with some background in D3. |
14 |
2019-03-09 |
2019-03-09 09:00:00 |
2019-03-09 10:00:00 |
0 |
0 |
0 |
Beatrice Jin & Jon McClure, POLITICO |
3 |
|
3 |
D3 in a reactive world |
| 78 |
4238 |
Finding the story: Open policing data |
Researchers at Stanford University have collected and examined the records from millions of local police stops in more than 50 cities. Using the programming language R, learn how to analyze this local policing data and find patterns for stories. This session is good for: People who have worked with data (or R) and want to learn how to analyze police data. |
17 |
2019-03-07 |
2019-03-07 09:00:00 |
2019-03-07 10:00:00 |
0 |
0 |
0 |
Daniel Jenson, Stanford University; Cheryl Phillips, Stanford University; Amy Shoemaker, Stanford University |
3 |
|
3 |
Finding the story: Open policing data |
| 84 |
4109 |
First Observable notebook: Prototyping with polish **pre-registered attendees only |
Skill level: Advanced Sahil Chinoy, Iris Lee, Ben Welsh and Aaron Williams teach you how to rapidly prototype a complex data visualization with JavaScript, D3.js and an interactive Observable notebook.?? This three-hour, hands-on course will show you how journalists are putting Observable’s powerful potential to work. Using nothing but your web browser, you will sketch, refine and publish an interactive graphic like one that appeared in The New York Times. Along the way, you’ll see how Observable’s groundbreaking approach to coding can help you be more creative, ambitious and efficient.?? Preregistration is required and seating is limited. Laptops will be provided. ?? Workshop prerequisites: If you’ve used JavaScript once or twice, have a good attitude and know how to take a few code crashes in stride, you are qualified for this class. If you’re suspicious and think we might be Internet hipsters, we welcome the challenge of winning you over. This stuff is cool. |
14 |
2019-03-07 |
2019-03-07 14:15:00 |
2019-03-07 17:45:00 |
1 |
1 |
0 |
Sahil Chinoy, The New York Times; Iris Lee, Los Angeles Times; Ben Welsh, Los Angeles Times; Aaron Williams, The Washington Post |
3 |
|
3 |
First Observable notebook: Prototyping with polish *pre-registered attendees only |
| 90 |
4214 |
Full-stack React |
In this session, we'll walk through how to connect a database-driven backend to a modern, React-driven static website frontend. We'll use Django as our backend of choice for this class, but the principles will apply to any news developer building databases and wanting to connect them to a modern frontend infrastructure. You'll come away knowing how to build the best of both worlds: a backend robust enough to handle huge datasets, and a frontend performant enough to handle your wildest traffic dreams. This session is good for: People who are comfortable writing JavaScript and have experience in a backend language. |
14 |
2019-03-09 |
2019-03-09 10:15:00 |
2019-03-09 11:15:00 |
0 |
0 |
0 |
Tyler Fisher, POLITICO |
3 |
|
3 |
Full-stack React |
| 96 |
4213 |
Graph databases 1: Building a database |
As data journalists, we're used to using relational databases — data organised in rows and columns such as a spreadsheet or SQL — to do our analysis and find stories. Graph databases are incredibly powerful for finding connections and patterns within our databases that would be difficult if not impossible to spot using traditional software. This session will provide a hands-on introduction to graph database Neo4j, showing examples of its use for investigative journalism including the Panama Papers, and teach you how to build your own graph database, importing public datasets to see at a glance the networks involved. This session is good for: beginners to graph databases. |
14 |
2019-03-07 |
2019-03-07 10:15:00 |
2019-03-07 11:15:00 |
0 |
0 |
0 |
William Lyon, Neo4j; Leila Haddou, The Times of London |
3 |
|
3 |
Graph databases 1: Building a database |
| 98 |
4155 |
Healthcare: Diagnose and treat a data dearth |
Learn to navigate healthcare's data minefield to challenge conventional wisdom, unleash hidden trends and expose industry lies. Our speakers found creative ways around bad or non-existent data to expose a global network of faulty medical devices, track the true danger of giving birth at home and show how private Medicaid contractors systematically deny treatments to boost profits. We'll explore the data and documents you'll need (and those you won't) for your next big investigation. |
1 |
2019-03-09 |
2019-03-09 16:45:00 |
2019-03-09 17:45:00 |
0 |
0 |
0 |
J. David McSwane, The Dallas Morning News (moderator); Marina Walker Guevara, International Consortium of Investigative Journalists; Emily Le Coz, GateHouse Media |
1 |
|
3 |
Healthcare: Diagnose and treat a data dearth |
| 100 |
4185 |
Holding algorithms accountable |
Algorithms are increasingly used throughout the public and private sectors, making decisions that impact people’s lives in myriad ways. Algorithmic accountability reporting is an emerging set of methods for investigating how algorithms exert influence and power in society. In this session, we’ll detail concrete investigations in this domain and discuss strategies, methods and techniques for pursuing algorithmic accountability reporting. |
3 |
2019-03-09 |
2019-03-09 10:15:00 |
2019-03-09 11:15:00 |
0 |
0 |
0 |
Nicholas Diakopoulos, Northwestern University (moderator); Heather Krause, Orb Media |
1 |
|
3 |
Holding algorithms accountable |
| 102 |
4158 |
How data can inform one of the hottest topics across the country: Housing |
How do local housing markets adapt when decimated by natural or man-made disasters? What’s the affordable housing strategy when Google comes to town? Want to unearth property tax inequities or fraud? This panel of experts will show you how to tackle the trends and complexities of the housing market, and how to make the most of ArcGIS, get help from Zillow Research and navigate property tax data. |
1 |
2019-03-09 |
2019-03-09 14:15:00 |
2019-03-09 15:15:00 |
0 |
0 |
0 |
Matt Clark, Newsday; Lorie Hearn, inewsource (moderator); Jon Schleuss, Los Angeles Times; Aaron Terrazas, Zillow |
1 |
|
3 |
How data can inform one of the hottest topics across the country: Housing |
| 105 |
4140 |
How it works: Blockchain |
Learn what the blockchain is, the basic principles of a transaction and how money moves between wallets. We'll also suggest ways to analyze transactions for financial investigations and list some obvious obstacles. |
7 |
2019-03-09 |
2019-03-09 14:15:00 |
2019-03-09 15:15:00 |
0 |
0 |
0 |
Shane Shifflett, The Wall Street Journal |
1 |
|
3 |
How it works: Blockchain |
| 118 |
4145 |
How to verify that emails are authentic with DKIM and ARC |
Suppose someone leaks you an email -- maybe it's an email they received from a public official that's noteworthy. Maybe it's from a hacker. How do you make sure it's not a fake? In this hands-on session, we'll guide you through that process. How do you get what you need from the source? What the heck is a DKIM header? How do you interpret the results of the verification process? What hiccups might you run into? Some basic familiarity with the command line will be helpful, but no coding knowledge or experience necessary. |
14 |
2019-03-08 |
2019-03-08 15:30:00 |
2019-03-08 16:30:00 |
0 |
0 |
0 |
Jeremy Merrill, Quartz |
3 |
|
3 |
How to verify that emails are authentic with DKIM and ARC |
| 133 |
4209 |
Introduction to VisiData |
VisiData is a relatively new tool for quickly exploring datasets. It's fast, powerful and keyboard-driven. It's often the first piece of software I use to examine new data. In this hands-on session, you'll learn VisiData's essentials commands — including how to sort, filter, summarize and aggregate. This session is good for: People who have a basic familiarity with your computer's command line interface. No programming knowledge necessary, but some knowledge of Python is a plus. |
13 |
2019-03-09 |
2019-03-09 10:15:00 |
2019-03-09 11:15:00 |
0 |
0 |
0 |
Jeremy Singer-Vine, BuzzFeed News |
3 |
|
3 |
Introduction to VisiData |
| 139 |
4265 |
JavaScript 3: Building a map in D3 |
Learn how to create an easy D3 map by converting GIS data into nice, reusable TopoJSON, turning it into a map and connecting it to your data. You can then have these maps ready for future use by just switching out a few variables. This session is good for: People who have a basic grasp of JavaScript syntax and have been exposed to the D3 library at some point. |
14 |
2019-03-08 |
2019-03-08 11:30:00 |
2019-03-08 12:30:00 |
0 |
0 |
0 |
Emily Merwin, The Atlanta Journal-Constitution |
3 |
|
3 |
JavaScript 3: Building a map in D3 |
| 147 |
4206 |
Making graphics and maps with R |
Learn how to visualize data in R with this introductory graphics class. From scatter plots to bar charts to box plots, we'll cover the basics of what you need to get an idea of what your data is telling you using ggplot2 and base R. We will also cover labeling, faceting, legends, and some cosmetics (changing colors and line/dot patterns, and displaying multiple plots in one window). This session is good for: R beginners who want to know how to visualize data. |
17 |
2019-03-08 |
2019-03-08 14:15:00 |
2019-03-08 15:15:00 |
0 |
0 |
0 |
Mary Ryan, University of California, Irvine |
3 |
|
3 |
Making graphics and maps with R |
| 149 |
4164 |
Management: Leading the data reporting team |
Managing a data team or data story presents challenges for any editor. This session takes an editor's point of view on the ins and outs of managing data journalism. Topics include helping reporters find focus for their data stories; being skeptical of data and finding potential pitfalls; verifying analyses and bulletproofing data stories and apps; using data to find human sources and characters for stories; and planning the best data workflows for your newsroom. |
1 |
2019-03-09 |
2019-03-09 09:00:00 |
2019-03-09 10:00:00 |
0 |
0 |
0 |
Helena Bengtsson, Sveriges TV; John Kelly, USA TODAY Network; Janet Roberts, Reuters (moderator) |
1 |
|
3 |
Management: Leading the data reporting team |
| 151 |
4207 |
Mapping with R |
Learn how to create beautiful static or interactive maps and conduct geospatial analyses all within R. We'll map with sf and leaflet packages. We'll write scripts to pull data and shapefiles through packages that utilize APIs from the Census. We'll transform and analyze data and turn your exploratory map viz into maps nearly pretty enough to publish. This session is good for: People who already have some familiarity with R, mapping, Census data, and using ggplot2. |
17 |
2019-03-08 |
2019-03-08 15:30:00 |
2019-03-08 16:30:00 |
0 |
0 |
0 |
Andrew Tran, The Washington Post |
3 |
|
3 |
Mapping with R |
| 164 |
4308 |
Observable notebooks: Your interactive data journal |
In this gentle introduction, we'll show you how to analyze and visualize data in an Observable notebook, whip up a series of rough prototypes, and export the bones to finish as a news graphic. There's nothing to install, no way to get yourself into a bad state with reactive cells, and no problem loading almost any JavaScript library you can think of. We’ll finish by walking through a series of published Washington Post pieces that started their life as Observable notebooks. |
7 |
2019-03-09 |
2019-03-09 11:30:00 |
2019-03-09 12:30:00 |
0 |
0 |
0 |
Jeremy Ashkenas, ObservableHQ; Aaron Williams, The Washington Post |
2 |
|
3 |
Observable notebooks: Your interactive data journal |
| 171 |
4227 |
PDF 3: Batch pdf processing |
This class will cover advanced tools for working with PDF, particularly the Python library pdfplumber. Learn how you can use programming skills to unlock information from PDF files that tools like Tabula or CometDocs just won't deal with. This session is good for: People who are familiar with Python notebooks, or if you've taken the first two PDF classes in the track. |
13 |
2019-03-08 |
2019-03-08 16:45:00 |
2019-03-08 17:45:00 |
0 |
0 |
0 |
Dan Nguyen, independent journalist |
3 |
|
3 |
PDF 3: Batch pdf processing |
| 174 |
4258 |
PostgreSQL |
This session will introduce you to PostgreSQL, a free, open source relational database system similar to MySQL and Microsoft SQL Server. We’ll cover the PostgreSQL ecosystem, from the database itself to management tools such as pgAdmin and psql. We’ll also dig into some of PostgreSQL’s unique and super-handy features, including the PostGIS spatial database extension, full-text search, and statistical functions. This session is good for: People who have some database experience, but beginners are welcome too! |
17 |
2019-03-07 |
2019-03-07 10:15:00 |
2019-03-07 11:15:00 |
0 |
0 |
0 |
Anthony DeBarros, The Wall Street Journal |
3 |
|
3 |
PostgreSQL |
| 175 |
4159 |
Preparing for the future of disinformation and deep fakes |
Recent advances in artificial intelligence make it easy to generate believable video and audio. It seems likely that these techniques will see usage in the political arena, where the ability to cheaply generate high fidelity hoaxes might be an attractive option for state and nonstate actors seeking to manipulate discourse and voter behavior. Journalists, tasked with evaluating the quality of information, will be on the front lines confronting these new threats as they emerge. Learn what tools exist to detect potential fakes, what machine learning can and can’t do, who is fighting the potential spread of synthetic videos and what we can do about it. This session was sponsored by Knight Foundation. IRE retains control of content, including the topic and speaker selection, for all conference sessions. |
10 |
2019-03-07 |
2019-03-07 16:45:00 |
2019-03-07 17:45:00 |
0 |
0 |
0 |
Paul Cheung, Knight Foundation (moderator); Christine Glancey, The Wall Street Journal; Sam Gregory, Witness; Tim Hwang, Harvard University; |
1 |
disinformation; fakes |
3 |
Preparing for the future of disinformation and deep fakes |
| 184 |
4241 |
Python 3: Data cleaning and visualization |
Now that you’ve got a handle on pandas, it’s time to jump into some advanced topics. You know how to import a dataset, but what happens when you load the data and nothing looks right? We’ll walk through cleaning up a dirty dataset with pandas. Then we’ll jump into the fun part: visualizing the data you’ve analyzed with matplotlib. This session is good for: People who can load and perform basic summary and grouping functions in pandas. |
13 |
2019-03-07 |
2019-03-07 16:45:00 |
2019-03-07 17:45:00 |
0 |
0 |
0 |
Karrie Kehoe, International Consortium of Investigative Journalists |
3 |
|
3 |
Python 3: Data cleaning and visualization |
| 186 |
4248 |
Python: Basic mapping and GIS |
Learn how to use GeoPandas, a lovely little Python library that will simplify your geospatial life. Manage projections, filter shapefiles, and even create publication-ready maps all from the safe haven of a Jupyter Notebook. This session is good for people who use Python in the newsroom. Some familiarity with the Pandas library is ideal, but not required. |
14 |
2019-03-10 |
2019-03-10 10:15:00 |
2019-03-10 11:15:00 |
0 |
0 |
0 |
Scott Pham, Buzzfeed News |
3 |
|
3 |
Python: Basic mapping and GIS |
| 187 |
4204 |
Python: Data visualization with Altair |
Move over, matplotlib -- a Python library called Altair is promising to make it even easier to create charts and maps for exploratory data analysis. Come learn how to use this library to bring your analysis to life with charts and maps. This session is good for: People who already have some familiarity with Python, Jupyter notebooks and using pandas for data analysis. |
14 |
2019-03-09 |
2019-03-09 15:30:00 |
2019-03-09 16:30:00 |
0 |
0 |
0 |
Andrea Suozzo, Seven Days |
3 |
|
3 |
Python: Data visualization with Altair |
| 190 |
4221 |
Python: Machine learning and natural language processing |
How to use off-the-shelf unsupervised machine learning, natural language processing, and outlier detection algorithms to find and visualize patterns in data. Sample data includes the Internet Research Agency Facebook Ads released by the Democrats on the House Intelligence Committee. This session is good for: People who have intermediate Python knowledge. |
14 |
2019-03-07 |
2019-03-07 09:00:00 |
2019-03-07 10:00:00 |
0 |
0 |
0 |
Jeff Kao, ProPublica |
3 |
|
3 |
Python: Machine learning and natural language processing |
| 191 |
4234 |
Python: Writing tests for your code |
Every programmer makes mistakes. Writing good tests can help you avoid making them in production. In this session, you will learn how to use Python's built-in tools to automate testing so you can sleep better at night. This session is good for: People who use Python regularly and want to improve their workflow. |
14 |
2019-03-09 |
2019-03-09 16:45:00 |
2019-03-09 17:45:00 |
0 |
0 |
0 |
Andrew Chavez, The Dallas Morning News |
3 |
|
3 |
Python: Writing tests for your code |
| 198 |
4244 |
R 3: Gathering and cleaning data in R |
Learn how to use R to collect information from web pages and transform the results into usable data. This session will also teach you how to clean and structure data for analysis using the tidyverse and other packages. This session is good for: People who have used R and database software. |
17 |
2019-03-07 |
2019-03-07 16:45:00 |
2019-03-07 17:45:00 |
0 |
0 |
0 |
Ronald Campbell, NBC Owned Television Stations |
3 |
|
3 |
R 3: Gathering and cleaning data in R |
| 201 |
4245 |
R: Intro stats in R |
Learn how to use R to spot trends and identify relationships in data using social science theories and methods. In this session, we will use R for statistical significance tests, cross-tabulations and linear regression. This session is good for: Anyone who is comfortable working with spreadsheets and database managers and wants to learn how to do basic statistical analysis. Some experience with R will be helpful. |
16 |
2019-03-07 |
2019-03-07 15:30:00 |
2019-03-07 16:30:00 |
0 |
0 |
0 |
Olga Pierce, ProPublica |
3 |
|
3 |
R: Intro stats in R |
| 202 |
4141 |
R: Models for clustered and correlated data |
Basic linear regression is great, but what happens when not all of your observations are independent or you have multiple observations per subject? Take your statistical analysis skills to the next level when you learn how to measure the relationships within correlated and clustered data in R using the gee package. This session is good for: Intermediate R users who are comfortable with linear and logistic regression and want to learn more complex modeling methods. |
4 |
2019-03-08 |
2019-03-08 09:00:00 |
2019-03-08 10:00:00 |
0 |
0 |
0 |
Mary Ryan, University of California, Irvine |
3 |
|
3 |
R: Models for clustered and correlated data |
| 210 |
4211 |
Spatial queries in PostGIS |
In this session, you will learn how to write spatial queries in PostGIS in order to make powerful conclusions with your geodata. We’ll go over examples and tricks, while also covering importing and exporting data. This class is good for: those comfortable writing their own SQL queries, including how to write “WHERE” and “GROUP BY” statements. Familiarity with writing spatial queries isn’t required, but students should have some basic GIS understanding. |
14 |
2019-03-09 |
2019-03-09 11:30:00 |
2019-03-09 12:30:00 |
0 |
0 |
0 |
Andrew Chavez & Ariana Giorgi, The Dallas Morning News |
3 |
|
3 |
Spatial queries in PostGIS |
| 220 |
4229 |
Stats 2: Linear regression using PSPP |
Go beyond counting and sorting. Learn how (and when) to measure relationships, level playing fields and make predictions. This session is good for: People who took “Stats 1: An introduction” and want to know how to apply what they learned, or are comfortable with summary statistics and PSPP or SPSS and new to stats. Familiarity with spreadsheets and database managers is recommended. |
17 |
2019-03-08 |
2019-03-08 10:15:00 |
2019-03-08 11:15:00 |
0 |
0 |
0 |
Ryan McNeill, Reuters |
3 |
|
3 |
Stats 2: Linear regression using PSPP |
| 221 |
4230 |
Stats 3: Logistic regression using PSPP |
Linear regression helps you find relationships between two or more variables, but when an outcome has only two possibilities, you need a different tool. That, my friends, is where logistic regression comes in. This session will be taught in PSPP and is good for people who took “Stats: An introduction” or are comfortable with summary statistics and PSPP or SPSS. Familiarity with spreadsheets and database managers is recommended. |
17 |
2019-03-08 |
2019-03-08 11:30:00 |
2019-03-08 12:30:00 |
0 |
0 |
0 |
John Perry, The Atlanta Journal Constitution |
3 |
|
3 |
Stats 3: Logistic regression using PSPP |
| 225 |
4210 |
Text mining in R with tidytext |
Do you want to analyze the themes, sentiment, and complexity of every State of the Union address, or analyze how Members of congress responded on Twitter to @realDonaldTrump? This session will introduce you to the tools needed to tackle these and other challenges in text analysis in R, using the tidytext package. This class is good for: those who are familiar with the basics of the tidyverse. |
16 |
2019-03-07 |
2019-03-07 11:30:00 |
2019-03-07 12:30:00 |
0 |
0 |
0 |
Peter Aldhous, Buzzfeed News |
3 |
|
3 |
Text mining in R with tidytext |
| 226 |
4147 |
The data sleuth's guide to the social web |
Whether you're spotting bots by plotting their activity levels or you're analyzing the spread of hate speech or misinformation in quantitative ways — there are many ways for journalists to investigate stories on the social web. This demo will walk through various approaches to leverage social media data for different kinds of stories and talk about the kinds of tools needed to report them out. |
1 |
2019-03-08 |
2019-03-08 09:00:00 |
2019-03-08 10:00:00 |
0 |
0 |
0 |
Jane Lytvynenko, BuzzFeed News; Lam Thuy Vo, Buzzfeed News |
2 |
|
3 |
The data sleuth's guide to the social web |
| 235 |
4152 |
Three open-source workflow tools that your newsroom could use today |
In this session, you will learn about three recently released open-source workflow tools and how they could be immediately useful to your newsroom: - gspan.js, a JavaScript library for transcribing and annotating CSPAN captions - Vizier, a GUI for ai2HTML projects. This app makes it easy to use the New York Times' ai2HTML plugin for turning Adobe Illustrator projects into responsive web graphics - socrata2sql, a Python library for quickly slurping data out of a Socrata portal into your database of choice |
10 |
2019-03-09 |
2019-03-09 10:15:00 |
2019-03-09 11:15:00 |
0 |
0 |
0 |
Andrew Briz, POLITICO (moderator); Kavya Sukumar, Hearken; Allan James Vestal, Dallas Morning News |
2 |
|
3 |
Three open-source workflow tools that your newsroom could use today |
| 254 |
4087 |
Write better Python code *pre-registered attendees only |
Skill level: Intermediate/advanced You’ve written a few Python scripts that get the job done, but the initial euphoria has worn off. Your code is hard to read. Bugs are cropping up. And you can’t always explain your process or results to an editor — or yourself. There must be a better way, but the path forward is not clear. If you’ve had that itchy feeling, this three-hour, hands-on workshop is for you. This class will explore Python language features that will help you write readable, reliable and reusable code. Preregistration is required and seating is limited.*Attendees must bring a laptop and charger to the training. Workshop prerequisites: Experience with basic Python language features like variables, data types, conditionals and functions are required. |
11 |
2019-03-09 |
2019-03-09 09:00:00 |
2019-03-09 12:30:00 |
1 |
1 |
0 |
Eric Sagara, Reveal from The Center for Investigative Reporting; Serdar Tumgoren, The Associated Press |
3 |
|
3 |
Write better Python code *pre-registered attendees only |