Skipper Seabold

538model. 538 Election Forecasting Model

pycon-ds-2018. Introduction to Python for Data Science for PyCon 2018

depy. DePy 2015 Talk

statsmodels-tutorial. Tutorial Created for SciPy 2012

odsc-west-python-2017. Introduction to Python for Data Science

pandas-selectable. A `select` accessor for easier subsetting of pandas DataFrames and Series

csc432-notebooks. These are the IPython notebook files for the CSC 432 Spring '13 course.

dask-pydata-chi-2016. Dask tutorial for PyData Chicago 2016

pydata-chi-docker. Jupyter Notebook

dask-pydata-dc-2016. Dask tutorial for PyData DC 2016

pydc. Introduction to Statsmodels Talk for Statistical Programming DC Meetup

odsc-east-python-2018. Introduction to Python for Data Science for ODSC East 2018

zorro. How to use IPython.parallel on AU's HPC Zorro

web-site. My home page

dotfiles. common config files

web-scraping. Web scraping demo and tutorial

jseabold.github.com. My Home page

jupyterlab-sql. SQL GUI for JupyterLab

pandas. NumPy-based labeled data structures and statistics library

statsmodels. Statsmodels: statistical modeling and econometrics in Python

data-science-science. Presentation and supporting materials for a talk about the science behind data science.

python-for-ds. Jupyter Notebook

sparkmagic. Jupyter magics and kernels for working with remote Spark clusters

pymc. Bayesian inference in Python

dockerfiles. Containerize all the things

pandas-intro. Pandas talk for PyData Boston 2013

lifelines. Survival analysis in Python

hyde. A Python Static Website Generator

numpy. Numpy main repository

scipy. Scipy main repository

xgboost. eXtreme Gradient Boosting (GBDT or GBRT) Library for large-scale (distributed) machine learning

ngcm_pandas_2017. Python data analysis course for 2017 NGCM Summer Academy

pelican-fresh. Fresh is a responsive Pelican theme. This theme uses HTML5 and its layout is responsive -- thanks to Smashing HTML5 and Twitter Bootstrap.