Book Image

Mastering Pandas for Finance

By : Michael Heydt
Book Image

Mastering Pandas for Finance

By: Michael Heydt

Overview of this book

Table of Contents (16 chapters)
Mastering pandas for Finance
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

The basics of the Series and DataFrame objects


Now let's examine using the Series and DataFrame objects, building up an understanding of their capabilities that will assist us in working with financial data.

Creating a Series and accessing elements

A Series can be created by passing a scalar value, a NumPy array, or a Python dictionary/list to the constructor of the Series object. The following command creates a Series from 100 normally distributed random numbers:

In [2]:
   np.random.seed(1)
   s = pd.Series(np.random.randn(100))
   s

Out[2]:
   0     1.624345
   1    -0.611756
   2    -0.528172
   3    -1.072969
           ...   
   96   -0.343854
   97    0.043597
   98   -0.620001
   99    0.698032
   Length: 100, dtype: float64

Individual elements of a Series can be retrieved using the [] operator of the Series object. The item with the index label 2 can be retrieved using the following code:

In [3]:
   s[2]

Out[3]:
   -0.528171752263

Multiple values can be retrieved using an array...