[Machine Learning for Trading] {ud501} Lesson 1: 00-00 Introduction | Lesson 2: 01-01 Reading and plotting stock data

 

 

 

 

 

 

 

 

 

 

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Python  vs  R and  Matlab

 

 

 

You will be using the Python data analysis library pandas extensively.

You will also occasionally need to dabble in NumPy, SciPy and matplotlib. But don't worry, these libraries work very well together.

 

 

 

Lesson outline

In this lesson you will learn how to read data, select subsets of it and generate useful plots, using pandas and matplotlib. The documentation links below are for your reference.

• Read stock data from CSV files:
  • pandas.DataFrame
  • pandas.read_csv
• Select desired rows and columns:
  • Indexing and Slicing Data
  • Gotchas: Label-based slicing conventions
• Visualize data by generating plots:
  • Plotting
  • pandas.DataFrame.plot
  • matplotlib.pyplot.plot

Hit Next to continue with the lesson.

 

 

 

 

Note: CSV = Comma-Separated-Values

Keep an eye out for notes and documentation links in this area throughout the course.

 

 

 

 

 

 

 HCP stock data on Yahoo Finance: [summary | table | chart]

Open: first price

Close: final price

Volume: how many shares of the stock traded

Adj Close: close price adjusted by splits, dividend payments, etc. => last day, close = adj close => longer ago, more difference

 

 

Python data analysis library: pandas

Documentation: pandas.DataFrame

 

 pandas is createed by Wes McKinney at a hedge fund called AQR, used at many hedge funds and by many people in the finance industry

 

 

 

 

 

 

Select rows

 

 

 

 

 

Compute max closing price 

 

 

 

 

 

 

 

 

 

 

Plotting stock price data

 

 

 

 

Plot High prices for IBM 

 

 

 

 

 Plot two columns

 

Note: 'Adj Close' stands for 'Adjusted Close' or 'Adjusted Closing Price' which is a historically-adjusted value of the stock that takes into account corporate actions (such as stock splits) and distributions (such as dividends issued).