rowid,event_id,name,clean_description,location_room,start_date_clean,start_time,end_time,pre_reg_flag,paid_flag,laptop_flag,speakers_cleaned,session_type,keywords,skill_level,session_title
6,4250,Advanced OpenRefine: Intro to GREL,"There is so much more to OpenRefine than the clustering and faceting feature. This session is a deep dive to GREL, OpenRefine expression language (the equivalent of Excel formulas). After a thorough introduction to GREL syntax, we will review the most common functions to explore and clean up your dataset. Functions covered in this session include replace, split, concatenate, string comparison, if, cell.cross (to join multiple projects together), and forEach. This session is good for: People who are familiar with OpenRefine or with at least some Excel experience. For an introduction to OpenRefine, check out the scheduled demo session. ",4,2019-03-08,2019-03-08 11:30:00,2019-03-08 12:30:00,0,0,0,"Martin Magdinier, OpenRefine Foundation ",3,,2,Advanced OpenRefine: Intro to GREL
14,4224,ArcGIS Online: Connect the where and the why with interactive demographic maps,"Demographic information can add critical context to any story. When paired with location, it can help explain why things happen where they do. Join us for a hands-on session where we’ll explore visualization- and analysis-ready datasets available to use in your stories. We’ll show you how to quickly find authoritative content in ArcGIS Online, run powerful spatial analyses, and create responsive web apps to support your reporting. You will get hands-on experience with the browser-based ArcGIS Online. Anyone who attends this session will also receive complimentary access to ArcGIS Pro, ArcGIS Online, and ArcGIS Maps for Office so you can continue your visualization journey long after you leave the conference. This session is good for: Anyone who’s wanted to dig into demographics but wasn’t sure where or how to start and those interesting in telling visual stories with that data. ",4,2019-03-08,2019-03-08 16:45:00,2019-03-08 17:45:00,0,0,0,"Robby Deming, Esri; Christopher Vaillancourt, Esri ",3,,2,ArcGIS Online: Connect the where and the why with interactive demographic maps
66,4261,Excel CARwash: Cleaning dirty data,"Dirty data lurk everywhere: in text files, spreadsheets, databases and PDFs. We'll walk you through some examples of the most common types of dirty data, point out telltale signs of data illness and explain how you can whip data into shape using some simple tools and methods. This session is good for: People with some experience working with data in columns and rows, in spreadsheets or database managers. ",4,2019-03-08,2019-03-08 15:30:00,2019-03-08 16:30:00,0,0,0,"Jennifer Smith Richards, Chicago Tribune",3,,4,Excel CARwash: Cleaning dirty data
69,4260,Excel: Importing data,"Not all data comes in ready-to-use, elegant spreadsheets. This session will teach you how to import data from text files and website tables. We will look at how to clean and organize data that may not come in the friendliest format. This session is good for: Anyone comfortable with working in Excel. ",4,2019-03-07,2019-03-07 16:45:00,2019-03-07 17:45:00,0,0,0,"Manuel Villa, The Marshall Project",3,,4,Excel: Importing data
70,4266,Excel: Using string functions to reformat data,Maybe you converted a PDF or imported a table into Excel -- or maybe an agency gave you a poorly formatted file. You can use string functions to reformat your data and get your spreadsheets working for you. This session is good for: Anyone comfortable with using formulas in Excel. ,4,2019-03-07,2019-03-07 15:30:00,2019-03-07 16:30:00,0,0,0,"Rachel Alexander, Salem Reporter",3,,4,Excel: Using string functions to reformat data
77,4268,Finding the story: Data-driven disaster coverage,"Natural disasters such as hurricanes, floods, wildfires and extreme temperature swings are causing historic damage. Together we’ll explore key data sets and learn how to use them to explain catastrophic events to audiences. This session is best for people who are already comfortable working with data in spreadsheets and have a basic familiarity with the capabilities of mapping tools such as QGIS or R. ",4,2019-03-08,2019-03-08 10:15:00,2019-03-08 11:15:00,0,0,0,"Matt Stiles, Los Angeles Times ",3,,4,Finding the story: Data-driven disaster coverage
79,4219,Finding the story: The state of immigration,"Accusations are flying in the immigration debate and you can be prepared to document the truth. How many are coming, where are they coming from and why? A hands-on look at how to use the data sources you need to follow the immigration debate nationally and in your town. This session is good for: those familiar with Excel. ",4,2019-03-07,2019-03-07 11:30:00,2019-03-07 12:30:00,0,0,0,"Tim Henderson, Pew Stateline ",3,,4,Finding the story: The state of immigration
91,4247,Geocoding and avoiding pitfalls,"If you've had to place many addresses on a map before, you know how problematic bulk geocoding can be — technical issues, terms of service, fun, fun, fun! If you've never had the pleasure, don't worry, we'll show you how to happily (and correctly) geocode large sets of addresses. Learn how to use Geocod.io to turn rows of addresses into points on a map. This session is good for: Anyone familiar with spreadsheets. No mapping experience necessary. ",4,2019-03-07,2019-03-07 10:15:00,2019-03-07 11:15:00,0,0,0,"Michael Corey, Reveal from the Center for Investigative Reporting",3,,2,Geocoding and avoiding pitfalls
99,4262,Hitchhiker's guide to APIs,"In this hands-on session, you will use Postman to interrogate a web API. We'll guide you through the process of constructing a magic URL that will tell you how Chicago’s violent crime in 2018 compares to other years. This session is good for: Beginners. If you’ve ever thought about what goes on in the location bar of your browser, have an eye for patterns, or want better ways to answer your reporting questions, you’ll have a blast. ",4,2019-03-09,2019-03-09 10:15:00,2019-03-09 11:15:00,0,0,0,"Roberto Rocha, CBC News",3,,4,Hitchhiker's guide to APIs
161,4259,MySQL,"Data often comes in large or relational tables that require a good database manager beyond what Excel can offer. MySQL is a free powerful and popular open-source tool and with it, you can transform and analyze almost any data set. In this class, we will introduce you to MySQL and how it works. This session is good for: People with some experience working with data in columns and rows and who are familiar with SQL. ",4,2019-03-08,2019-03-08 14:15:00,2019-03-08 15:15:00,0,0,0,"Jack Gillum, ProPublica ",3,,2,MySQL
189,4287,Python: Let's scrape a website (repeat),"This hands-on training will illustrate how Python can be used to grab a lot of data from a website at once, whether by pulling content from a page or interacting with forms. You’ll want to be comfortable writing loops in Python, though you won’t necessarily need to be able to write a function from scratch! This session is good for people who feel comfortable with Python’s data types and control flow (if/else, loops). Experience with HTML is a plus but not necessary. Note: It would be useful to attend the session ""How it Works: The Internet"" in advance if you’re not familiar with the topic already. ",4,2019-03-09,2019-03-09 09:00:00,2019-03-09 10:00:00,0,0,0,"Mike Stucka, The Palm Beach Post",3,,,Python: Let's scrape a website (repeat)
195,4288,R 1: Intro to R and RStudio (repeat),"Learn your way around the basics of RStudio. We’ll load basic packages to do data analysis, read in some data and explore it. This is a good class to learn the basic structure of writing R code. You’ll leave knowing how to get data into R, how to do some cleaning and formatting tasks and how to start doing basic analysis on a dataset. This will give you more confidence to take the next steps in your analyses. This session is good for: beginner to intermediate users. ",4,2019-03-09,2019-03-09 14:15:00,2019-03-09 15:15:00,0,0,0,"Sarah Ryley, The Trace",3,,,R 1: Intro to R and RStudio (repeat)
197,4289,R 2: Data analysis and plotting in R (repeat),"We'll use the tidyverse and sf packages, learning how to sort, filter, group, summarize, join, map and visualize to identify trends in your data. If you want to combine SQL-like analysis and charting in a single pipeline, this session is for you. This session is good for: People who have worked with data operations in SQL or Excel and would like to do the same in R. ",4,2019-03-09,2019-03-09 15:30:00,2019-03-09 16:30:00,0,0,0,"Sarah Ryley, The Trace",3,,,R 2: Data analysis and plotting in R (repeat)
199,4290,R 3: Gathering and cleaning data in R (repeat),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. ,4,2019-03-09,2019-03-09 16:45:00,2019-03-09 17:45:00,0,0,0,"David Montgomery, CityLab",3,,,R 3: Gathering and cleaning data in R (repeat)
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
203,4231,Regular expressions for the rest of us,"Regular expressions are a powerful way to slice, dice and clean up dirty data — a must-know skill for anyone who works with data. They may look intimidating, but they are really just pattern-matching puzzles. We'll learn the fundamentals of ""regex"" so you save time cleaning your next batch of data. This session is good for: People who have ever done more than two search/replace actions to clean a data set or had to split a ZIP code from an address or otherwise want to conquer their fears of regex. ",4,2019-03-07,2019-03-07 09:00:00,2019-03-07 10:00:00,0,0,0,"Christian McDonald, University of Texas ",3,,2,Regular expressions for the rest of us
222,4232,Stats in Excel,"You don't need a special statistics program to run simple statistical analysis. In this session, you'll learn how to compute some basic statistics in Excel and figure out what they mean. This session is good for: People who already are comfortable with using functions in Excel. ",4,2019-03-07,2019-03-07 14:15:00,2019-03-07 15:15:00,0,0,0,"Steve Doig, ASU Walter Cronkite School of Journalism",3,,2,Stats in Excel
227,4146,The data-driven escape room,"You're an investigative reporter in London, and you have one hour to help your colleague finish a story he's been digging into involving organized crime. We'll provide some real-life data files and some background reading, and you'll work in teams to scour the data, answer questions and do some internet sleuthing to put together the story, all in under an hour. This session is good for: Anyone familiar with spreadsheets. ",4,2019-03-09,2019-03-09 11:30:00,2019-03-09 12:30:00,0,0,0,"Jennifer LaFleur, Aron Pilhofer, Temple University; Jonathan Stoneman ",3,,1,The data-driven escape room