Overview of this book

Python for Finance
Credits
Acknowledgments
www.PacktPub.com
Preface
Free Chapter
Introduction and Installation of Python
13 Lines of Python to Price a Call Option
Introduction to Modules
Statistical Analysis of Time Series
Index

The x.sum() dot function

After `x` is defined as a `NumPy` array, we could use `x.function()` to conduct related operations such as `x.sum()` as shown in the following lines of code:

```>>>import numpy as np
>>>x=np.array([1,2,3])
>>>x.sum()
6
>>>np.sum(x)
6
```

If `x` is a `NumPy` array, we could have other functions with the same dot format as well: `x.mean()`, `x.min()`, `x.max()`, `x.var()`, `x.argmin()`, `x.clip()`, `x.copy()`, `x.diagonal()`, `x.reshape()`, `x.tolist()`, `x.fill()`, `x.transpose()`, `x.flatten()`, and `x.argmax()`. Those dot functions are useful because of the convenience they offer. The following commands show two such examples:

```>>>cashFlows=np.array([-100,30,50,100,30,40])
>>>np.min(cashFlows)
-100
>>>np.argmax(cashFlows)
0
```

The `np.min()` function shows the minimum value, while the `np.argmin()` function gives the location (that is, index) of the minimum value.