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
67,4212,Excel for business & economics,"Whether you just started using Excel or it's been your companion for years, chances are there's a lot it can do that you've never realized. We sometimes think of Excel as the stepping stone to database managers like Access or SQL Server, and overlook just how powerful its tools can be — especially if you're covering business and economics. Come find out why Excel is still so popular in the business world and we'll unlock some of its secrets. The people you're covering know these tricks — you should too. ",17,2019-03-07,2019-03-07 11:30:00,2019-03-07 12:30:00,0,0,0,"Aaron Kessler, CNN ",3,,4,Excel for business & economics
71,4092,Exploring the tidyverse in R *pre-registered attendees only,"Skill level: Intermediate Learn how to use the tidyverse, a collection of R packages will help you make your data journalism more efficient, stronger and fun. Learn how to import, clean, analyze and plot data for your stories. If you've used packages like dplyr, tidyr, readr, ggplot2, tibble and purr, or would like to learn more about how these work together, this class is for you. Preregistration is required and seating is limited. Laptops will be provided for the training.? ? Workshop prerequisites: You should be comfortable working with R and RStudio. You should also be familiar with basic data analysis. ",17,2019-03-09,2019-03-09 09:00:00,2019-03-09 17:45:00,1,1,0,"Aaron Kessler, CNN; Olga Pierce, University of Nebraska-Lincoln; Andrew Tran, The Washington Post",3,,2,Exploring the tidyverse in R *pre-registered attendees only
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
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
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
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
194,4242,R 1: Intro to R and RStudio,"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. ",17,2019-03-07,2019-03-07 14:15:00,2019-03-07 15:15:00,0,0,0,"Meghan Hoyer, Associated Press",3,,2,R 1: Intro to R and RStudio
196,4243,R 2: Data analysis and plotting in R,"We'll use the tidyverse packages dplyr and ggplot2, learning how to sort, filter, group, summarize, join 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. ",17,2019-03-07,2019-03-07 15:30:00,2019-03-07 16:30:00,0,0,0,"Ronald Campbell, NBC Owned Television Stations",3,,2,R 2: Data analysis and plotting in R
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
200,4291,R: Intro stats (repeat),"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. ",17,2019-03-08,2019-03-08 16:45:00,2019-03-08 17:45:00,0,0,0,"Steve Reilly, USA Today",3,,,R: Intro stats (repeat)
219,4228,Stats 1: An introduction using PSPP,"Statisticians need to really understand their data (and so do you!) before they begin running analyses. As a result, statistical software packages such as PSPP and SPSS have many powerful tools to summarize your data. You're going to love them. We'll take a look at the structure of data in PSPP, do data transformations and run some basic statistical tests. This session is good for: People who have familiarity with Excel and some database software. We've got a *lot* of ground to cover in this hour. ",17,2019-03-08,2019-03-08 09:00:00,2019-03-09 10:00:00,0,0,0,"Holly Hacker, The Dallas Morning News",3,,2,Stats 1: An introduction using PSPP
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