Advance data science and architecture
Working with Edgar datasets: Wrangling, Pre-processing and exploratory data analysis.
EDGAR, the Electronic Data Gathering, Analysis, and Retrieval system.performs automated collection, validation, indexing, acceptance, and forwarding of submissions by companies and others who are required by law to file forms with the U.S. Securities and Exchange Commission (the "SEC").
See documentation here
- config.ini --store CIK, acc_no data
- Dockerfile
--docker config for docker
-i stands for interactive mode and -t will allocate a pseudo terminal for us.
docker build -t parse_file . docker run -ti parse_file
In this way, you can input aws key and secret in docker via keyboard - parse_file.py --parse file python cource code
- Dockerfile --docker config for docker
-i stands for interactive mode and -t will allocate a pseudo terminal for us.
docker build -t missing_data . docker run -ti missing_data
In this way, you can input aws key and secret in docker via keyboard - missing_data.py --missing dat python source code
Conduct an exploratory data analysis using Python packages (seaborn, matplotlib) to understand the dataset.
AdaptiveAlgo Systems Inc. works on solutions to build algorithms and platforms to address energy modeling challenges.
With the knowledge of energy consumed by various equipment, seasonality and attributes like temperature and humidity, a machine learning model could be used to predict aggregate energy use.
See documentation here