Peadar Coyle springcoil
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springcoil
/ report-runner.py
Last active
August 29, 2015 14:15
— forked from chris1610/report-runner.py
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| # -*- coding: utf-8 -*- | |
| """ | |
| Sample report generation script from pbpython.com | |
| This program takes an input Excel file, reads it and turns it into a | |
| pivot table. | |
| The output is saved in multiple tabs in a new Excel file. | |
| """ |
springcoil
/ Bayesian_Model.py
Last active
August 29, 2015 14:21
A Bayesian model for myself to debug - PyData Berlin
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| g = simuls.groupby('Team') | |
| season_hdis = pd.DataFrame({'points_lower': g.points.quantile(.05), | |
| 'points_upper': g.points.quantile(.95), | |
| 'goals_for_lower': g.gf.quantile(.05), | |
| 'goals_for_median': g.gf.median(), | |
| 'goals_for_upper': g.gf.quantile(.95), | |
| 'goals_against_lower': g.ga.quantile(.05), | |
| 'goals_against_upper': g.ga.quantile(.95), | |
| }) | |
| season_hdis = pd.merge(season_hdis, df_observed, left_index=True, right_on='Team') |
springcoil
/ Bayesian_Model_2.py
Last active
August 29, 2015 14:21
A Bayesian model for myself to debug - PyData Berlin
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| df_avg = pd.DataFrame({'avg_att': atts.stats()['mean'], | |
| 'avg_def': defs.stats()['mean']}, | |
| index=teams.team.values) | |
| df_avg = pd.merge(df_avg, df_observed, left_index=True, right_on='team', how='left') | |
| fig, ax = plt.subplots(figsize=(8,6)) | |
| for outcome in ['winner', 'triple_crown', 'wooden_spooon', '']: | |
| ax.plot(df_avg.avg_att[df_avg.QR == outcome], | |
| df_avg.avg_def[df_avg.QR == outcome], 'o', label=outcome) | |
springcoil
/ bayesian_model3.py
Created
May 15, 2015 12:38
Another Bayesian_Model which needs edited
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| df_hpd = pd.DataFrame(atts.stats()['95% HPD interval'], | |
| columns=['hpd_low', 'hpd_high'], | |
| index=teams.team.values) | |
| df_median = pd.DataFrame(atts.stats()['quantiles'][50], | |
| columns=['hpd_median'], | |
| index=teams.team.values) | |
| df_hpd = df_hpd.join(df_median) | |
| df_hpd['relative_lower'] = df_hpd.hpd_median - df_hpd.hpd_low | |
| df_hpd['relative_upper'] = df_hpd.hpd_high - df_hpd.hpd_median | |
| df_hpd = df_hpd.sort_index(by='hpd_median') |
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| { | |
| "cells": [ | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "slideshow": { | |
| "slide_type": "slide" | |
| } | |
| }, | |
| "source": [ |
springcoil
/ machine-create.sh
Last active
August 29, 2015 14:25
— forked from tshauck/machine-create.sh
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| docker-machine create \ | |
| --driver amazonec2 \ | |
| --amazonec2-access-key $ACCESS_KEY \ | |
| --amazonec2-secret-key $SECRET_KEY \ | |
| --amazonec2-vpc-id $VPC \ | |
| --amazonec2-security-group $SECURITY_GROUP \ | |
| --amazonec2-instance-type "m4.2xlarge" \ | |
| --amazonec2-root-size 20 \ | |
| --amazonec2-request-spot-instance \ | |
| --amazonec2-spot-price 0.20 \ |
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| LC_ALL=C docker-machine create \ | |
| --driver amazonec2 \ | |
| --amazonec2-access-key $AWS_ACCESS_KEY_ID \ | |
| --amazonec2-secret-key $AWS_SECRET_ACCESS_KEY \ | |
| --amazonec2-region "eu-west-1" \ | |
| --amazonec2-vpc-id $VPC \ | |
| --amazonec2-instance-type "m4.2xlarge" \ | |
| --amazonec2-root-size 20 \ | |
| --amazonec2-request-spot-instance \ | |
| --amazonec2-spot-price 0.20 \ |
springcoil
/ basic_income_monte_carlo.py
Last active
August 29, 2015 14:25
— forked from stucchio/basic_income_monte_carlo.py
Monte carlo simulation of basic income/basic job calculations, from blog.
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| from pylab import * | |
| from scipy.stats import * | |
| num_adults = 227e6 | |
| basic_income = 7.25*40*50 | |
| labor_force = 154e6 | |
| disabled_adults = 21e6 | |
| current_wealth_transfers = 3369e9 | |
| def jk_rowling(num_non_workers): |