Work Share Session 1

First workshare session where R users at NN share project work.

This content was presented to Nelson\Nygaard Staff at a Lunch and Learn webinar on Wednesday, March 17th, 2021, and is available as a recording here and embedded below.

Announcements

• Schedule change: today we are doing a workshare instead of an interactive session on GitHub due to workload issues for Esther and I – this gives us a little more time to prepare, as well as some more time to make sure everyone has the appropriate software installed, and has made a GitHub account and shared their GitHub username with Bryan so that he can have you added to PW’s GitHub organization. Please give your username to Bryan ASAP if you have not. The most up to date webinar schedule is available here
• Software check in – does everyone have R, RStudio, RTools, and git installed? Have you made a GitHub account?
• Three NN R users – Paul Leitman, Ulises Hernandez, and Esther Needham contributing to workshare this week – I will let folks know when we are at the 15 minute mark for your workshare, so that you can wrap up in 1-2 minutes and transition to the next person. We have more than 15 but less than 20 minutes for each person.
• Our next workshare will be on Wednesday, May 26th, 2021 – I hope we will get some different volunteers to share work for that date, so please be thinking about what you might want to share on that date – I’ll be nudging folks as we get closer.

Paul Leitman: Transit Data Cleaning

Description: Clients often share data with us that requires a lot of manual clean up or reformatting to turn it into a useable dataset for summaries and visualization. I will share two examples of where two clients provided data in Excel that was not in a format that could be used for analysis, and were too large to manually clean up. I was able to quickly re-format the data sets in R so that they could be used.

Relevant Links:

• TransLink example: G:\Current\TRANSLINK_R6_RapidBus_920300_2020.0300\R\Dwell times\0.Save dwell time data.R
• StarMetro example: G:\Current\STARMETRO_2021_Update_2020.0099\R\Clean up ridership by stop file.R

Ulises Hernandez: Origin-Destination Trip Mapping

Description: Spider lines or OD lines are a common way to visualize travel patterns. We often need to produce spider line maps showing point-to-point trips or trips aggregated at a specific zone (e.g., block groups). A staple example of this is a paratransit spider line map or workers OD using LEHD data. I will go over how we can use R to produce these types of maps. I will walk through this script from the Norman City paratransit system. I might screen-share a couple of older scripts to show a few learning experiences/best practices.

Relevant Links:

• G:\Current\NORMAN_OK_LongRanceStrategicPlan_920529\R\Norman_OD_paratransit.R

Esther Needham: BDAT’s Project/Treatment Creation Feature

Description: The newest feature of our speed and reliability dashboard (BDAT) is the ability to code treatments on selected segments, implemented for the King County Metro and SDOT dashboard. The dashboard allows users to create custom lines based on segments by splitting segments up on the fly. Users are also able to drop points onto segments. I’ll walk through the code used to do this and explain the use of several different packages to work with geographic data for this purpose.

Relevant Links:

• Shiny Dashboard: https://nelsonnygaard.shinyapps.io/r_demo_treatments/
• Code

This content was presented to Nelson\Nygaard Staff at a Lunch and Learn webinar on Wednesday, March 17th, 2021, and is available as a recording here and embedded at the top of the page.