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On November 04, 2019, RLadies-Philly presented a series of very informative lightning talks ranging from programming tips for reproducible research to full-blown applications of big data in delivering individualized care in medicine. One of the attendees correctly commented later that each of the five lightning talks was very enlightening and could each be extended to a full-length presentation. This blog post provides highlights from the lightning talks. I Can Code Clearly Now - 10 Tips for Formatting R Code Speaker: Jenine K.

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Networks, also referred to as graphs in mathematics, model multiple types of relations and processes in physical, social, biological, and information systems. R-Ladies Philly’s October 2019 meetup was a workshop focusing on how to implement network analyses using the R igraph object. The workshop was led by Chun Su, PhD, who is a bioinformatics scientist at the Children’s Hospital of Philadelphia and also a R-ladies Philly co-organizer. The workshop materials are available at rladiesPHL github.

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R-Ladies Philadelphia’s September 2019 meetup was on the topic of reporting research using R Markdown. Our speaker was Ramaa Nathan, PhD, a statistican and data scientist with a background in the healthcare and finance industries. Ramaa is a co-organizer of the Data Science Philadelphia (DataPhilly) meetup group. Ramaa’s materials are available here. Welcome #rladies to our meetup! So excited to see everyone and to have Ramaa leading our session on R markdown!

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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.

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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.

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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.

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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?

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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.

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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.

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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.

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