Importing Finance Data with Python from Free Web Sources

Importing Finance Data with Python from Free Web Sources

Importing Finance Data with Python from Free Web Sources. Get Historical Prices, Fundamentals, Metrics/Ratios etc. for thousands of Stocks, Bonds, Indexes, (Crypto-) Currencies

What can be the most critical and most expensive part when working with financial data?

Pandas coding? Creating some advanced Algorithms to analyse and optimize portfolios? Building solutions for Algorithmic Trading and Robo Advising? Maybe! But very often it is … getting the Data!

Financial Data is scarce and Premium Data Providers typically charge $20,000 p.a. and more!

However, in 95% of all cases where Finance Professionals or Researchers require Financial Data, it can actually be obtained from Free or low-priced web sources. Some of them provide powerful APIs and Python wrapper packages, which makes it easy and comfortable to import the data with and into Python.

This course shows you how to get massive amounts of Financial Data from the web and provides downloadable Python coding templates (Jupyter Notebooks) for your convenience!

Importing Finance Data with Python from Free Web Sources Description

Requirements

  • Some Python Basics
  • A desktop computer (Windows, Mac, or Linux) capable of storing and running Anaconda. The course will walk you through installing the necessary free software.
  • An internet connection capable of streaming videos and downloading data
  • Ideally first experience with Pandas Library (not necessary, a Pandas crash course is included in the course)

Getting Started with Spring Boot 2

What you’ll learn

  • Importing free / low-priced Financial Data from the Web with Python
  • Installing the required Libraries and Packages
  • Working with powerful APIs and Python wrapper packages
  • Downloading Historical Prices and Fundamentals for thousands of Stocks, Indexes, Mutual Funds and ETF´s
  • Downloading Historical Prices for Currencies (FOREX), Cryptocurrencies, Bonds & more
  • Saving / Storing the Data locally
  • Pandas Coding Crash Course

Who this course is for:

  • Investment & Finance Professionals (and their Companies) spending thousands of USD p.a. on Financial Data.
  • (Finance) Students and Researchers who need to work with large financial datasets with only small budgets.
  • Everybody working occasionally with Financial Data.

Importing Finance Data with Python from Free Web Sources Free Download

Google Drive (Public)

Content From: https://www.udemy.com/course/importing-free-financial-data-with-python/

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