# Creating function

Function `<function name>` can be defined using following syntax:

```
def <function name>(arg1,arg2,...,argN):
  <body of function>
  return <output of function>
```

Where `arg1`,`arg2`,...,`argN` - arguments of function, `<body of function>` - actual block of code, `<output of function>` - return value, in fact - not necessary for some functions.

# Built-in functions

Also, additionally to function, that we could create, there are a variety of built-in functions, which we can use without importing any libraries beforehand.

Among them we can highlight next:

* `type(v)` - returns type of a variable/value `v`, which passed as argument;
* `map(f, c)` - returns iterable collection, in which function `f` applied to each element of iterable collection `c`;
* `filter(f, c)`- returns iterable collection, which contains those elements of iterable collection `c`, for which value of `f` is `True`;
* `zip(c1,c2)` - returns list of tuples with an item from each iterable collection `c1` and `c2`, by iterating them in parallel;
* `len(s)` - return number of items in object `s`(either can be sequence, like string, or collection);
* `max(c)` -  returns maximum value in iterable collection `c`;
* `max(arg1,arg2)` -  returns maximum value of elements `arg1` and `arg2`(can be used with larger number of arguments);
* `min()` - have two ways of usage, just like `max()`, however - finds minimum value;
* `sum()` - returns sum of elements into collection;
* `pow(base, power)` - returns number `base` raised to power `power`;
* `int()`, `float()`, `complex()`, `bool`,`list()`, `dict()`, `set()`, `str()`, `tuple()`, etc - convert variable/value to the corresponding datatype.

# Addition

For more detailed explanation and examples - dive into video: 

What is the value of the variable `d`?

```
f = lambda x: x ** 2 + 2 * x
a = [1, -1, 3]
b = ['a', 'c', 'd', 'g', 'b']
c = list(map(f, a))
d = dict(zip(b, c))
```

This course will help those who want to get some of Python’s basic knowledge, including features, which are useful for data manipulation, and also want to discover some of the financial concepts, including options trading and stock prices prediction using time series analysis.

First of all, we are going to discover some basic features of Python programming language, which will be helpful for us during the rest of the course, including data types, basic operators, functions, including some of the built-in, basics of NumPy and Pandas libraries, and also - how to upload financial data, in our case - from financial provider Yahoo Finance. 

Now, when we have already coped with basic aspects of Python programming language, it is time to dive into the first topic, directly related to finance - options trading. So, we will discuss such aspects as what is options, some basic strategies for trading and mathematical model for estimating option's price.

Now, we are going to show several methods that will be useful for a specific task - which is forecasting of stock prices.  

Introduction to Finance with Python

Functions

What is a function?

Creating function

Built-in functions

Addition