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analyze_fracfocus_data

This repo contains Python script that is used to pull and analyze FracFocus data for completions and vendor insights.

automated_decline_curve_analysis_oil_and_gas_wells

This Python script uses webscraped Bakken data to generate automated exponential and hyperbolic decline curves for production forecasting for individual wells.

automated_fracfocus_data_pull

This script automates pulls from the online FracFocus database into a Python pandas dataframes, and writes to a csv.

automl_examples

batch_mode_script_automation

This repo shows how to automate both Python and SQL scripts in batch mode

change_point_detection

Examples of online and offline changepoint detection using the ruptures and changefinder packages

daily_peak_electricity_demand_analysis

This script uses hourly electricity demand data to build a machine learning model that estimates peak hourly demand on a daily basis.

electricity_price_time_series_analysis

This project pulls electricity price data from the EIA API, and then performs time series analysis on it, including time series decomposition and vector autoregression for forecasting.

financial-time-series-api-tutorial

This tutorial provides a background on pulling different financial time series using the Quandl and Alpha Vantage API's.

foreclosure_webscraper

Webscrapes a the Jefferson County CO foreclosures ASP.NET form using Selenium.

mann_whitney_comparison

This code provides an example where two distributions are compared using the Mann-Whitney U Test.

pull_data_from_epa_envirofacts_api

This script is an example script for pulling data from the EPA's Envirofacts database. In it, data from the greenhouse gas emissions database is pulled via the API and assembled into a master pandas dataframe.

pull_eia_carbon_dioxide_emissions_data_nat_gas_tx

This script is an example script for pulling data via the EIA API

seasonal_arima_model_forecasting

This code covers the seasonal ARIMA model, where a SARIMA model is generated, tuned, and forecast using test data.

unsupervised_anomaly_detection_time_series

This script pulls the gasoline price time series (from the EIA), and performs unsupervised time series anomaly detection using a variety of techniques. Techniques include SESD algorithm, One Class SVM, Isolation Forests, and low pass filter.

webscrape_monthly_og_data_bakken

This script automates web scraping the North Dakota Oil & Gas Division website, collecting monthly oil and gas data and pulling into a master dataframe that can be used for data analysis.