class MyBio:
def __init__(self):
self.name = "Gavin Qu"
self.role = ["Economics Research", "Analyst", "Curiosity-driven"]
self.location = ["Seattle"]
self.languages = ["Python", "R", "Java", "Bash", "SQL"]
self.interests = ["ML for Economics", "Causal Inference", "Open Source", "Blogging", "Linux"]
def current_project(self):
return "Learning Julia"
def contact(self):
return {
"LinkedIn": "linkedin.com/in/gavinqu/"
"email": "gavinqu dot dev at gmail"
}
def about_me(self):
return """
Outside of work, you'll often find me hiking, climbing, skiing, and reading Sci-fi.
"""
bio = MyBio()
print(bio.about_me())
print("Current Project:", bio.current_project())
print("Contact Info:", bio.contact())
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predoc-coding-sample
predoc-coding-sample PublicReproducible data pipeline (Python) for my thesis —health types and labor market outcomes.
Jupyter Notebook 1
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econ-phd-advice
econ-phd-advice PublicCommunity-maintained, open-source collection of resources and advice for Grad students in economics — and for undergrads considering a PhD.
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causal-inference-notes
causal-inference-notes PublicRefactored R code from my causal inference class to Python Notebooks.
Jupyter Notebook
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