the mean, median and standard deviation for a very large data set.

Let's start with calculating the mean acceleration due to gravity based on the data from pendulum.txt.

We first create an empty list `g_list' to which we shall append the values of `g'.

In []: g_list = []

For each pair of `L' and `t' values in the file `pendulum.txt' we calculate the 

value of `g' and append it to the list `g_list'

We proceed to calculate the mean of the value of `g' from the list `g_list'. 

Here we shall show three ways of calculating the mean. 

Firstly, we calculate the sum `total' of the values in `g_list'.

Once we have the total we calculate by dividing the `total' by the length of `g_list'

The second method is slightly simpler. Python provides a built-in function called "sum()" that computes the sum of all the elements in a list. 

The third method is the simplest. Python provides a built-in function `mean' that

calculates the mean of all the elements in a list.

Python provides support for dictionaries. Dictionaries are key value pairs. Lists are indexed by integers while dictionaries are indexed by strings. For example:

In []: d = {'png' : 'image',

      'txt' : 'text', 

      'py' : 'python'} 

is a dictionary. The first element in the pair is called the `key' and the second 

is called the `value'. The key always has to be a string while the value can be 

of any type.

Dictionaries are indexed using their keys as shown

In []: d['txt']

Out[]: 'text'

In []: d['png']

Out[]: 'image'

The dictionaries can be searched for the presence of a certain key by typing

Please note the values cannot be searched in a dictionaries.

Out[]: ['py', 'txt', 'png']

is used to obtain the list of all keys in a dictionary

Out[]: ['python', 'text', 'image']

is used to obtain the list of all values in a dictionary

In []: d

Out[]: {'png': 'image', 'py': 'python', 'txt': 'text'}

Please observe that dictionaries do not preserve the order in which the items

were entered. The order of the elements in a dictionary should not be relied upon.