Introduction May is here and it’s time to get back to our roots by revisiting the R for Data Science text as well as introduce materials to help you - yes you - get comfortable with GitHub.
Sure, we could do something similar to the first iteration of our online learning community and say we’re going to cover a specified amount of material each week, but instead we’re going to try something new!
Introduction This past March I had the distinct pleasure of participating in a panel about making the career transition to data science as part of Kaggle’s CareerCon 2018. As a result of this experience, I’ve gotten enough emails asking for more information about my data science journey that it warrants a blog post, per David Robinson’s advice:
When you’ve written the same code 3 times, write a function
When you’ve given the same in-person advice 3 times, write a blog post
(YMMV = your mileage may vary)
Introduction Feeling inspired by some recent data science collaborations, on Friday I released the following tweet into the wild:
want to build data science experience? reach out to a local non-profit you're interested in, and ask them if you can volunteer with data collection, cleaning, and basic analysis and reporting. you get experience, the NPO gets a product they desperately need, and everyone wins.
Introduction April is such a fantastic time of the year - the weather starts to warm up, trees and flowers start blooming, and many of us start in on some spring cleaning. So it’s only natural that we’d focus on the same thing in our R4DS Online Learning Community!
Finishing up March’s Viewing Parties Thank you to everyone who participated in our viewing party in early March, where member Chris B.
We’re going to walk through the basics of posting GIFs on your blogdown website using imgur and GIPHY.
Introduction Blogdown is an amazing tool for - wait for it - blogging. I recently made the jump to blogdown, and after working out all of my self-inflicted initial “OMG what happened now?!” issues, blogdown has become part of my daily workflow. I’m still playing with formatting issues (evidence below) but on the whole things are coming together nicely.
We’re so close to March, which for many of you involves a lot of college basketball.
But there’s another exciting challenge happening, once which also happens to involve your participation: R4DS is hosting its first series of community member talks!
The Challenge: Participate! Four of our community members have graciously stepped up to record a 20-30 minute talk on an R4DS-related topic, and they will be developing these over the next few weeks.
Introduction If you’ve found yourself here, you’ve probably been asked to create a reproducible example, or reprex, in response to a question you asked on the RStudio Community Site. This post provides a cursory overview of both creating a reprex as well as how to share your reprex on the RStudio Community site.
A brief reprex “how to” Install the development version of reprex from GitHub and then load the reprex package Highlight the code and associated packages, as indicated by library(package_name), like so: Copy the highlighted code by pressing Ctrl/Cmd + c In the console type reprex() and hit Enter/Return Everything that you need to post a reprex is now automatically stored on your clipboard!
It’s February–which most people associate with Valentine’s Day, and that’s fine–but for all of us in the R4DS Online Learning Community, we’re going to focus on winning!
The challenge: share your wins The challenge is short and sweet this month, and the same for both learners and mentors:
Once a week for the month of February, post a “win” that you’ve had in our #wins channel on Slack Engage with community members in the channel–emoji responses or starting a conversation by replying to someone’s win are both great ways to do this!
It always starts with a DM on Twitter, where someone shares with me their personal data science ambitions, where they currently are in their plans, and then they follow up with a request for me to help them figure out where to go next.
I love these messages—they’re an affirmation that the R community continues to grow and attract new members in part by creating a welcoming and supportive space for beginners, and that our community members are deemed approachable (enough) for someone brand new to R to reach out!
Happy New Year! I love the start of the New Year for so many reasons, but one of my favorites is the never-ending stream of motivational word art that populates a good 98% of every social media feed for 31 whole days, like so:
Another reason for loving the start of 2018 is that we’re kicking off the next iteration of the R for Data Science Online Learning Community! So if you’re joining us for January, consider participating in the January Challenge.