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Learning pandas

You're reading from   Learning pandas High performance data manipulation and analysis using Python

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Product type Paperback
Published in Jun 2017
Publisher
ISBN-13 9781787123137
Length 446 pages
Edition 2nd Edition
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Author (1):
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Michael Heydt Michael Heydt
Author Profile Icon Michael Heydt
Michael Heydt
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Table of Contents (16) Chapters Close

Preface 1. pandas and Data Analysis 2. Up and Running with pandas FREE CHAPTER 3. Representing Univariate Data with the Series 4. Representing Tabular and Multivariate Data with the DataFrame 5. Manipulating DataFrame Structure 6. Indexing Data 7. Categorical Data 8. Numerical and Statistical Methods 9. Accessing Data 10. Tidying Up Your Data 11. Combining, Relating, and Reshaping Data 12. Data Aggregation 13. Time-Series Modelling 14. Visualization 15. Historical Stock Price Analysis

Historical Stock Price Analysis

In this final chapter, we will use pandas to perform various financial analyses of stock data obtained from Google Finance. This will also cover several topics in financial analysis. The emphasis will be on using pandas to derive practical time-series stock data and not on details of the financial theory. However, we will cover many useful topics and learn how easy it is to apply pandas to this domain and to others.

Specifically, in this chapter, we will progress through the following tasks:

  • Fetching and organizing stock data from Google Finance
  • Plotting time-series prices
  • Plotting volume-series data
  • Calculating simple daily percentage change
  • Calculating simple daily cumulative returns
  • Resampling data from daily to monthly returns
  • Analyzing distribution of returns
  • Performing moving-average calculations
  • Comparing average daily returns across stocks...
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