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Mastering Pandas for Finance

Mastering Pandas for Finance

By : Michael Heydt
3.7 (6)
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Mastering Pandas for Finance

Mastering Pandas for Finance

3.7 (6)
By: Michael Heydt

Overview of this book

If you are interested in quantitative finance, financial modeling, and trading, or simply want to learn how Python and pandas can be applied to finance, then this book is ideal for you. Some knowledge of Python and pandas is assumed. Interest in financial concepts is helpful, but no prior knowledge is expected.
Table of Contents (11 chapters)
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10
Index

Chapter 4. Time-series

A time-series is a sequence of data points, typically consisting of successive measurements made at a regular frequency and over a specific time interval. Time-series analysis is composed of various methods for making decisions based upon the data in a time-series by extracting meaningful statistics. Time-series forecasting is the process of developing a model based upon data in a time-series, and using it to predict future values based upon previously observed values. Regression analysis is the process of testing whether one or more independent time-series affect the current value of another time-series.

There is extensive support for working with time-series data in pandas. In this chapter, we will examine representing time-series data with the pandas Series and DataFrame as well as several common techniques for manipulating this data. The techniques learned in this chapter will set the basis for the remaining chapters, where we will examine several financial...

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