Our July Meetup sought to highlight work and lessons from our community members through a series of short and engaging lightning talks.
Important skills for women in data (Rajvi Mehta)
Rajvi, a Data Scientist at Vanguard and Philadelphia Chapter Lead of Women in Data, shared her story of becoming a data scientist, and the lessons she learned along the way. She highlighted the following advice:
Always seek to update your skill set, because job titles are varied in data science, and it’s a fast paced environment Seek to improve your communication skills, because there is often a need to explain complex statistics to colleagues and clients who have different areas of expertise but who, given the right explanation, could contribute tremendously to the data scientist’s work Seek diversity in teams, as people with diverse backgrounds can bring unique perspectives on solutions, risk, team dynamics, and problem solving approaches Remember that data is not just about the numbers, but it is also about the people behind the data (the end users, the developers implementing data collection systems, the business rules influencing the data being collected, etc.
Data visualization is paramount to both understanding and presenting your data, whatever your data may be. For our June Meetup, R-Ladies Philly member Jake Riley led an interactive workshop to elucidate aspects of the popular ggplot2 package and share helpful tips and best practices relevant to any R user.
The 2 g’s in ggplot2 - defined! Jake explained that the architecture of visualizing data using ggplot2 is based on the grammar of graphics: In ggplot2, just like every sentence has a subject, verb, and noun, every plot has a coordinate system, geom, and aesthetics.
How to communicate as (minority) data scientists? Being a minority in data science can be tough. It can be tough to get into the field, and sometimes even tougher to make yourself heard in the field. Marieke Jackson, a former epidemiologist turned data scientist, shared how basic rules from improv have helped her navigate day to day challenges.
Imagine you are working with an improv partner and you mention those pesky magical flying birds that poop jellybeans.
Our April meetup with Data Philly focused on the increasingly popular topic of Open Science. See below for the article that R Ladies Philly members Alice, Karla, and Amy co-wrote! This article originally appeared on Technical.ly Philly.
What is open science? It’s like open data, but for research. Organizers of the R-Ladies Philly meetup offer an explainer based on talks from their most recent meetup.
Many are familiar with the concept of open source in software development, but what is open science?
In February and March, R-Ladies Philly continued a longstanding community data project with the Philadelphia Animal Welfare Society (PAWS) - Philly’s largest no-kill shelter. Last year, we helped PAWS analyze data from volunteer engagement to identify patterns associated with continued volunteering. This year, we worked with PAWS to understand important facets of their sheltering system, including 1) animals’ trajectories at PAWS, 2) the adoption process, 3) geospatial patterns of adoptions, and 4) public engagement via social media.
Our January meetup marked an important event in R-Ladies Philly history - our first ‘birthday’! We honored this occasion by celebrating what our community has achieved over the past year, and planning for an exciting 2019.
Recap of our first year Alice and Karla started off by reiterating the founding principles of R-Ladies Philly: to create a welcoming, accepting, and representative community for R users in the Philadelphia area who espouse our values of diversity and gender equity.
We collaborated with Women in Kaggle Philly to provide an Introduction to Machine Learning (ML).
ML is the science of getting computers to learn from data without explicit programming. ML has led to advances in speech recognition, tumor identification, self-driving cars, and many other arenas. You probably interact with ML every day!
This meetup featured a lightning talk introducing some key concepts followed by a hands-on Kaggle competition tutorial.
A brief introduction to Machine Learning Tamera Lanham, a data scientist at Elsevier, gave a lightning talk introducing ML.
Geographic Information Systems or GIS are specialized technology used for spatial data that require mapping. In our November meetup, R-Ladies Philly member and GIS Specialist Mary Lennon introduced R-Ladies Philly to manipulating and plotting spatial data from our favorite city (Philly!) in our favorite language (R!)!
How can we access and store spatial data? First, Mary explained that GIS data can be stored in different formats including Shapefiles, GPX, and GeoJSON.
Shiny is an R Package that combines the computational power of R with the interactivity of the web to enable users to create interactive web apps (and dashboards!) in R. For our October meetup, Dr. Mine Çetinkaya-Rundel led a workshop introducing the basics of building dashboards using Shiny, and a demo on transitioning from dashboards to standalone apps. In case you missed the Meetup, all materials (code! slides! more!) can be found on the github repo Mine created.
In our September meetup hosted at the Penn Dental School, R-Ladies LA founder and recent Philadelphia transplant Dr. Katie Scranton led an interactive workshop on making websites (like this one!) using R and the blogdown package.
Overview Katie started off by providing a broad overview of how blogdown works. Blogdown generates websites using Rmarkdown documents, and each blogdown website consists of a single folder of static files. Once created, your blogdown website can then be hosted on any web server to make it ‘live.