Data Manipulation and Cleaning

Thomas Lai

Consulting Drop-In Hours: Fri 3pm-5pm

Consulting Areas: Python, Matlab, APIs, Data Manipulation and Cleaning, Data Science, Data Visualization, Machine Learning, Python Programming, Software Tools, Git or Github, Spotfire

Quick-tip: the fastest way to speak to a consultant is to first submit a...

Ini Umosen

Consulting Drop-In Hours: Tue 9am-11am

Consulting Areas: R, Stata, LaTeX, Data Manipulation and Cleaning, Data Science, Data Visualization, R Programming, Text Analysis, Web Scraping, Regression Analysis, RStudio, RStudio Cloud, Stata

Quick-tip: the fastest way to speak to a consultant is to first ...

Suraj Nair

Data Science Fellow
School of Information

I am a PhD Student at the School of Information. My research interests lie at the intersection of development economics and machine learning, with a focus on the use of large scale digital data and new computational tools to study pressing issues in global development.

Alex Ramiller

Data Science Fellow
City and Regional Planning

I am a PhD Candidate in City and Regional Planning. My research focuses on the use of large administrative datasets to study residential mobility, neighborhood change, and housing access. I received a Master in Geography from the University of Washington and a Bachelor's in Economics and Geography from Macalester College. I have also consulted on analytical projects for several organizations including the San Francisco Federal Reserve Bank, PolicyLink, and the City of Seattle.

Lauren Chambers

Consultant
School of Information

Lauren Chambers is a Ph.D. student at the Berkeley School of Information, where she studies the intersection of data, technology, and sociopolitical advocacy with Prof. Deirdre Mulligan. Previously Lauren was the staff technologist at the ACLU of Massachusetts, where she explored government data in order to inform citizens and lawmakers about the effects of legislation and political leadership on our civil liberties. Lauren received her Bachelor's from Yale in 2017, where she double-majored in astrophysics and African American studies, and she spent two years after graduation in...

Jane Angar

Consultant
Political Science

Mango Jane Angar is a Political Science Ph.D. student at the University of California, Berkeley. Her research focuses on Political Violence and Disability Politics. In particular, she examines how state institutions, society, and disabled persons organizations conceptualize and define disability.

Jailynne Estevez

Consultant
Info & Data Science MIDS

Jailynne Estevez is a Data Analyst and a prospective Masters in Information and Data Science candidate at UC Berkeley. With a bachelor's in Public Policy, she brings a diverse skill set to her pursuits, demonstrating aptitude in data analysis and programming.

Ini Umosen

Consultant
Economics

Ini is a PhD candidate in the Department of Economics. She studies topics in labor economics and the economics of education using applied econometrics methods. Current work in progress includes evaluating the impact of school choice systems and investigating gender and racial bias on gig platforms. She is a former Graduate Research Fellow at the California Policy Lab. She has also been a tutor for econometrics, labor economics, and macroeconomics.

Leah Lee

Data Science Fellow
Integrative Biology

I am a PhD candidate in the department of Integrative Biology. My research interest is at the intersection of biomechanics, entomology, and physiology. Currently I am studying how beetles use their shield-like forewings called elytra for flight, thermoregulation, and protection. Prior to UC Berkeley, I worked as a research assistant at Korea Institute of Ocean Science and Technology (KIOST), studying algae phylogenetics. I received my B.A. in Biology and Mathematics from Swarthmore College.

R Data Wrangling and Manipulation: Parts 1-2

September 25, 2023, 10:00am
It is said that 80% of data analysis is spent on the process of cleaning and preparing the data for exploration, visualization, and analysis. This R workshop will introduce the dplyr and tidyr packages to make data wrangling and manipulation easier. Participants will learn how to use these packages to subset and reshape data sets, do calculations across groups of data, clean data, and other useful tasks.