Edgar can be used to analyse the financials of a single company over time. However, we try to get an overall picture of the profits over all companies. For this we use the Python Data Analysis Library Pandas and my simple Edgar REST API. In [199]: import pandas import matplotlib.pyplot as plt Profits by Country¶ We can get a quick overview with the help of the follwing REST get request. We ask for countries by year Read more…
I was curious about the usefulness of the Edgar Database: Is is possible to predict the development of the stock price using the company filings? Can we predict the total yearly profits for the current year based on the filings of the current months? Is the overall profitability changing over time: e.g. are companies more profitable because of e.g. Trump? Which sectors are making money and which are loosing ? Is there a relationship between Read more…
Today, I was putting together and testing my Data Science Toolbox in Docker which consists of the following components: GUI/Environment – jupyter – python3 Core Libraries – NumPy – SciPy – Pandas Visualization – Matplotlib – Seaborn Machine Learning – SciKit-Learn – Keras – TensorFlow It is based on the lean Alpine Linux! Here is the version information of the installed components: In [12]: import sys print(sys.version) 3.6.2 (default, Aug 29 2017, 13:56:02) [GCC 6.4.0] In [11]: print(“Installed Read more…
I have fully Dockerized my infrastructure and I am currently running 44 containers. It is impressive to see that on a tiny 2 core i3 machine, this usually only takes 4% of the CPU. My images can be found on Docker-Hub