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Importing Finance Data with Python from Free Web Sources

Get Historical Prices, Fundamentals, Metrics/Ratios etc. for thousands of Stocks, Bonds, Indexes, (Crypto-) Currencies
Rating: 4.6 out of 54.6 (153 ratings)
2,305 students
Created by Alexander Hagmann
Last updated 2/2021
English
English [Auto]
30-Day Money-Back Guarantee

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
Curated for the Udemy for Business collection

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)

Description

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 Splits and 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!

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.

Course content

9 sections • 93 lectures • 7h 44m total length

  • Preview05:27
  • Preview03:32
  • Preview08:55

  • Intro
    03:05
  • Installing the required Package
    03:03
  • Preview04:01
  • Setting specific Time Periods
    06:06
  • Frequency Settings (Intraday)
    07:38
  • Stock Splits and Dividends
    11:51
  • Exporting to CSV / Excel
    05:36
  • Importing many Stocks
    04:17
  • Financial Indexes
    05:53
  • Currencies / FX
    03:14
  • Cryptocurrencies
    03:10
  • Mutual Funds & ETFs
    02:44
  • Treasury Yields
    03:38
  • The Ticker Object
    04:21
  • Stock Fundamentals, Meta Info and Performance Metrics
    04:22
  • +++IMPORTANT NOTICE & ACTION REQUIRED (before you start with next Lecture!) +++
    00:18
  • Financials (Balance Sheet, Cashflows, P&L)
    05:37
  • Put / Call Options
    04:04
  • Streaming Real-time Data
    04:01

  • Intro / Get your API Key
    05:26
  • Installing the required Package
    02:17
  • Historical Price and Volume Data for one Stock
    03:34
  • Setting specific Time Periods
    03:22
  • Stock Splits and Dividends
    06:47
  • Converting to DatetimeIndex
    03:39
  • Frequency Settings (Intraday)
    04:51
  • Real-time Data for many Stocks
    02:30
  • Technical Indicators
    08:57
  • Currencies / FX
    06:43
  • Cryptocurrencies
    05:21

  • Intro / Register and get your API Key
    06:13
  • Commands to install required packages
    00:23
  • Installing the required Package
    02:15
  • Connecting to the API/Server
    04:10
  • Currencies / FX (incl. Bid/Ask)
    05:45
  • Frequency Settings (Intraday)
    02:45
  • Setting specific Time Periods
    07:50
  • Stock Indexes (incl. Bid/Ask)
    04:01
  • Commodities (incl. Bid/Ask)
    04:15
  • Cryptocurrencies (incl. Bid/Ask)
    02:28
  • Streaming high-frequency real-time Data (Part 1)
    07:07
  • Streaming high-frequency real-time Data (Part 2)
    02:08

  • Intro / Register
    01:59
  • Commands to install required packages
    00:06
  • Installing the required Packages
    02:22
  • Get your API Key and connect to the Server
    05:21
  • Getting Historical Data
    04:36
  • Frequency Settings (high-frequency Intraday Data)
    02:53
  • Streaming high-frequency real-time Data
    02:43

  • Intro / Register and get your API Key
    06:17
  • Introduction to the API (hands-on)
    05:19
  • Getting Historical Stock Prices and Volume Data
    03:58
  • Stock Splits and Dividends
    08:02
  • Financial Indexes
    03:52
  • Currencies / FX
    04:24
  • Cryptocurrencies
    02:51
  • Commodities
    02:13
  • Mutual Funds & ETFs
    03:35
  • Treasury Yields
    02:37
  • Stock Fundamentals, Meta Info and Performance Metrics
    07:40
  • Financials (Balance Sheet, Cashflows, P&L)
    03:20
  • Fundamentals and Performance Metrics for Funds & ETFs
    05:04
  • Bond Data: Fundamentals
    03:15
  • Bonda Data: Ratings
    01:26
  • Bond Data: Historical Prices and Yields
    02:10
  • Bulk Download of Ticker Symbols for entire Exchanges
    06:05
  • Bulk Download of Stock Prices, Stock Splits and Dividends
    04:19

  • Installing Anaconda
    08:08
  • How to open a Jupyter Notebook
    09:29
  • Working with Jupyter Notebooks
    14:00
  • Downloading and Working with Templates
    04:17

  • Intro to Tabular Data / Pandas
    05:03
  • Tabular Data Cheat Sheets
    00:00
  • Download of Datasets (csv files)
    00:03
  • First Steps (Inspection of Data, Part 1)
    11:10
  • First Steps (Inspection of Data, Part 2)
    08:45
  • Built-in Functions, Attributes and Methods
    08:26
  • Make it easy: TAB Completion and Tooltip
    08:57
  • Selecting Columns
    08:01
  • Selecting Rows with iloc
    07:42
  • Selecting Rows with loc
    05:11
  • Pandas Series
    06:44
  • Importing Time Series Data from csv-files
    08:16
  • Converting strings to datetime objects with pd.to_datetime()
    08:53
  • Initial Analysis / Visualization of Time Series
    05:41
  • Indexing and Slicing Time Series
    07:25
  • Initial Inspection and Visualization of Financial Time Series
    05:32
  • Normalizing Time Series to a Base Value (100)
    06:31
  • Hands-on: Importing Excel-Files to Python
    09:47

  • Get your special BONUS here!
    01:58

Instructor

Alexander Hagmann
Data Scientist | Finance Professional | Entrepreneur
Alexander Hagmann
  • 4.7 Instructor Rating
  • 3,450 Reviews
  • 35,092 Students
  • 7 Courses

Alexander is a Data Scientist and Finance Professional with more than 10 years of experience in the Finance and Investment Industry.

He is also a Bestselling Udemy Instructor for

- Data Analysis/Manipulation with Pandas

- (Financial) Data Science

- Python for Business and Finance

- Algorithmic Trading

Alexander started his career in the traditional Finance sector and moved step-by-step into Data-driven and Artificial Intelligence-driven Finance roles. He is currently working on cutting-edge Fintech projects and creates solutions for Algorithmic Trading and Robo Investing. And Alexander is excited to share his knowledge with others here on Udemy. Students who completed his courses work in the largest and most popular tech and finance companies all over the world.

Alexander´s courses have one thing in common: Content and concepts are practical and real-world proven. The clear focus is on acquiring skills and understanding concepts rather than memorizing things.   

Alexander holds a Master´s degree in Finance and passed all three CFA Exams (he is currently no active member of the CFA Institute).   

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