Hello welcome to the tutorial on statistics and dictionaries in Python.

Till now we have covered:
* How to create plots.
* How to read data from file and process it.

In this session, we will use them and some new concepts to solve a problem/exercise. 

We have a file named sslc1.txt.
It contains record of students and their performance in one of the State Secondary Board Examination.
We can see the content of file by opening with any text editor.
Please don't edit the data.
It is arranged in a particular format.
One particular line being:
A;015163;JOSEPH RAJ S;083;042;47;AA;72;244;;;
It has following fields:
* Region Code which is 'A'
* Roll Number 015163
* Name JOSEPH RAJ S
* Marks of 5 subjects: 
  ** English 083
  ** Hindi 042
  ** Maths 47
  ** Science AA (Absent)
  ** Social 72
* Total marks 244
* Pass/Fail Blank cause he was absent in one exam or else it will be(P/F)
* Withheld Blank in this case(W)

So problem we are going to solve is:
Draw a pie chart representing proportion of students who scored more than 90% in each region in Science.

The result would be something like this:
slide of result.

We would be using following machinery:
File Reading(done already)
parsing (done partly)
Dictionaries (new)
Arrays
Plot (done already)

Dictionaries

We earlier used lists, we just created them and appended items to list. 
x = [1, 4, 2, 7, 6]
to access the first element we use index number, and it starts from 0 so
x[0] will give
1 and
x[3] will
7

At times we don't have index to relate things. For example consider a telephone directory, we give it a name and it should return back corresponding number. List is not the best kind of data structure for such problems, and hence 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'} 
d 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
'py' in d
True

'jpg' in d
False
Please note the values cannot be searched in a dictionaries.

d.keys()
['py', 'txt', 'png']
is used to obtain the list of all keys in a dictionary

d.values()
['python', 'text', 'image']
is used to obtain the list of all values in a dictionary

d

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.

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Parsing and string processing

As we saw previously we will be dealing with lines with such content
A;015162;JENIL T P;081;060;77;41;74;333;P;;
so ';' is delimiter we have to look for.
We will create one string variable to see how can we process it get the desired output.

line = 'A;015162;JENIL T P;081;060;77;41;74;333;P;;'
a = line.split(';')
we have used split earlier to split on empty spaces.
a 

is list with all elements separated.
a[0] is the region we want.
and a[6] will give us the science marks of a particular region.
So we create a dictionary of all the regions with number of students having more then 90 marks.
Something like 
d = {'A': 729, 'C': 764, 'B': 1120,'E': 414, 'D': 603, 'F': 500}

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code

We first create an empty dictionary

science = {}
now we read the record data one by one

for record in open('sslc1.txt'):

    we split the record on ';' and store the list in 'fields'
    fields = record.split(';')

    now we strip this string for leading and trailing white spaces
    region_code = fields[0].strip()

    now we check if the region code is always there in dictionary by writing 'if' statement
    if region_code not in science:    
       when this statement is true, we add new entry to dictionary with 
       science[region_code] = 0

    we again strip(ing is good) the string
    score_str = fields[6].strip()

    we check if student was not absent
    if score_str != 'AA':
       then we check if his marks are above 90 or not
       if int(score_str) > 90:
       	  science[region_code] += 1

    Hit return twice

by end of this loop we will have our desired output in the dictionary 'science'
we can check the values by
science

now to create a pie chart we use

pie(science.values(),labels = science.keys())
title('Students scoring 90% and above in science by region')
savefig('science.png')