Importing Finance Data with Python from Free Web Sources

Importing Finance Data with Python from Free Web Sources, available at $99.99, has an average rating of 4.25, with 93 lectures, based on 392 reviews, and has 6318 subscribers.

You will learn about 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 This course is ideal for individuals who are Investment & Finance Professionals (and their Companies) spending thousands of USD p.a. on Financial Data. or (Finance) Students and Researchers who need to work with large financial datasets with only small budgets. or Everybody working occasionally with Financial Data. It is particularly useful for Investment & Finance Professionals (and their Companies) spending thousands of USD p.a. on Financial Data. or (Finance) Students and Researchers who need to work with large financial datasets with only small budgets. or Everybody working occasionally with Financial Data.

Enroll now: Importing Finance Data with Python from Free Web Sources

Summary

Title: Importing Finance Data with Python from Free Web Sources

Price: $99.99

Average Rating: 4.25

Number of Lectures: 93

Number of Published Lectures: 93

Number of Curriculum Items: 93

Number of Published Curriculum Objects: 93

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will 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 Should Attend

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.

Target Audiences

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.

(Latest course update and full code review in April 2023!)

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! +++

This course covers four different data sources and explains in detail how to install required Libraries and how to download and import the data with few lines of Python Code. You will have access to

60+ Exchanges all around the world
120,000+ Symbols/Instruments
Historical Price and Volume Data for thousands of Stocks, Indexes, Mutual Funds and ETFs
Foreign Exchange (FOREX): 150+ Physical Currencies / Currency Pairs
500+ Digital- / Cryptocurrencies
Fundamentals, Ratings, Historical Prices and Yields for Corporate Bonds
Commodities(Crude Oil, Gold, Silver, etc.)
Stock Options for 4,500 US Stocks
Fundamentals, Metrics and Ratios for thousands of Stocks, Indexes, Mutual Funds and ETFs
Balance Sheets
Profit and Loss Statements (P&L)
Cashflow Statements
50+ Technical Indicators (e.g. SMA, Bollinger Bands)
Real-time and Historical Data (back to 1960s)
Streaming high-frequency real-time Data
Stock Splitsand Dividends and how these are reflected in Stock Prices
Learn how Stock Prices are adjusted for Stock Splits and Dividends…
… and use appropriately adjusted data for your tasks! (avoid the Pitfalls!)
Build your own Financial Databases…

… And save thousands of USDs!

What are you waiting for? As always, I provide a 30-Days-Money-Back Guarantee. So, there is no risk for you!

Looking forward to seeing you in the course!

Course Curriculum

Chapter 1: Getting Started

Lecture 1: Tips: How to get the most out of this Course

Lecture 2: Course Overview

Lecture 3: Hands-on: Downloading CSV-files and import to Python

Chapter 2: Importing Financial Data from Web Source 1

Lecture 1: Intro

Lecture 2: Installing the required Package

Lecture 3: Historical Price and Volume Data for one Stock

Lecture 4: Setting specific Time Periods

Lecture 5: Frequency Settings (Intraday)

Lecture 6: Stock Splits and Dividends

Lecture 7: Exporting to CSV / Excel

Lecture 8: Importing many Stocks

Lecture 9: Financial Indexes

Lecture 10: Currencies / FX

Lecture 11: Cryptocurrencies

Lecture 12: Mutual Funds & ETFs

Lecture 13: Treasury Yields

Lecture 14: The Ticker Object

Lecture 15: *** UPDATE March 2023*** the yahooquery alternative

Lecture 16: *** Updated Notebooks March 2023***

Lecture 17: Stock Fundamentals, Meta Info and Performance Metrics

Lecture 18: Financials (Balance Sheet, Cashflows, P&L)

Lecture 19: Put / Call Options

Lecture 20: Streaming Real-time Data

Chapter 3: Importing Financial Data from Web Source 2

Lecture 1: Intro / Get your API Key

Lecture 2: Installing the required Package

Lecture 3: Historical Price and Volume Data for one Stock

Lecture 4: Setting specific Time Periods

Lecture 5: Stock Splits and Dividends

Lecture 6: Converting to DatetimeIndex

Lecture 7: Frequency Settings (Intraday)

Lecture 8: Technical Indicators

Lecture 9: Currencies / FX

Lecture 10: Cryptocurrencies

Chapter 4: Importing Financial Data from Web Source 3

Lecture 1: Intro / Register and get your API Key

Lecture 2: Commands to install required packages

Lecture 3: Installing the required Package

Lecture 4: Connecting to the API/Server

Lecture 5: Currencies / FX (incl. Bid/Ask)

Lecture 6: Frequency Settings (Intraday)

Lecture 7: Setting specific Time Periods

Lecture 8: Stock Indexes (incl. Bid/Ask)

Lecture 9: Commodities (incl. Bid/Ask)

Lecture 10: Cryptocurrencies (incl. Bid/Ask)

Lecture 11: Streaming high-frequency real-time Data (Part 1)

Lecture 12: Streaming high-frequency real-time Data (Part 2)

Chapter 5: Web Source 3b (for US and Canadian Residents)

Lecture 1: Intro / Register

Lecture 2: Commands to install required packages

Lecture 3: Installing the required Packages

Lecture 4: Get your API Key and connect to the Server

Lecture 5: Getting Historical Data

Lecture 6: Frequency Settings (high-frequency Intraday Data)

Lecture 7: Streaming high-frequency real-time Data

Chapter 6: Importing Financial Data from Web Source 4

Lecture 1: Intro / Register and get your API Key

Lecture 2: Introduction to the API (hands-on)

Lecture 3: Getting Historical Stock Prices and Volume Data

Lecture 4: Stock Splits and Dividends

Lecture 5: Financial Indexes

Lecture 6: Currencies / FX

Lecture 7: Cryptocurrencies

Lecture 8: Commodities

Lecture 9: Mutual Funds & ETFs

Lecture 10: Treasury Yields

Lecture 11: Stock Fundamentals, Meta Info and Performance Metrics

Lecture 12: Financials (Balance Sheet, Cashflows, P&L)

Lecture 13: Fundamentals and Performance Metrics for Funds & ETFs

Lecture 14: Bond Data: Fundamentals

Lecture 15: Bonda Data: Ratings

Lecture 16: Bond Data: Historical Prices and Yields

Lecture 17: Bulk Download of Ticker Symbols for entire Exchanges

Lecture 18: Bulk Download of Stock Prices, Stock Splits and Dividends

Chapter 7: Installing Python and Download/Working with Templates

Lecture 1: Installing Anaconda

Lecture 2: How to open a Jupyter Notebook

Lecture 3: Working with Jupyter Notebooks

Lecture 4: Downloading and Working with Templates (***Updated August 2023***)

Chapter 8: Appendix 1: Pandas Crash Course

Lecture 1: Intro to Tabular Data / Pandas

Lecture 2: Tabular Data Cheat Sheets

Lecture 3: Download of Datasets (csv files)

Lecture 4: First Steps (Inspection of Data, Part 1)

Lecture 5: First Steps (Inspection of Data, Part 2)

Lecture 6: Built-in Functions, Attributes and Methods

Lecture 7: Make it easy: TAB Completion and Tooltip

Lecture 8: Selecting Columns

Lecture 9: Selecting Rows with iloc

Lecture 10: Selecting Rows with loc

Lecture 11: Pandas Series

Lecture 12: Importing Time Series Data from csv-files

Lecture 13: Converting strings to datetime objects with pd.to_datetime()

Lecture 14: Initial Analysis / Visualization of Time Series

Lecture 15: Indexing and Slicing Time Series

Lecture 16: Initial Inspection and Visualization of Financial Time Series

Lecture 17: Normalizing Time Series to a Base Value (100)

Lecture 18: Hands-on: Importing Excel-Files to Python

Instructors

Alexander Hagmann
Data Scientist | Finance Professional | Entrepreneur

Rating Distribution

1 stars: 2 votes
2 stars: 7 votes
3 stars: 32 votes
4 stars: 126 votes
5 stars: 225 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

Menu