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-Hello friends and welcome to the tutorial on statistics using Python
-
-{{{ Show the slide containing title }}}
-
-{{{ Show the slide containing the outline slide }}}
-
-In this tutorial, we shall learn
- * Doing simple statistical operations in Python
- * Applying these to real world problems
-
-You will need Ipython with pylab running on your computer
-to use this tutorial.
-
-Also you will need to know about loading data using loadtxt to be
-able to follow the real world application.
-
-We will first start with the most necessary statistical
-operation i.e finding mean.
-
-We have a list of ages of a random group of people ::
-
- age_list=[4,45,23,34,34,38,65,42,32,7]
-
-One way of getting the mean could be getting sum of
-all the elements and dividing by length of the list.::
-
- sum_age_list =sum(age_list)
-
-sum function gives us the sum of the elements.::
-
- mean_using_sum=sum_age_list/len(age_list)
-
-This obviously gives the mean age but python has another
-method for getting the mean. This is the mean function::
-
- mean(age_list)
-
-Mean can be used in more ways in case of 2 dimensional lists.
-Take a two dimensional list ::
-
- two_dimension=[[1,5,6,8],[1,3,4,5]]
-
-the mean function used in default manner will give the mean of the
-flattened sequence. Flattened sequence means the two lists taken
-as if it was a single list of elements ::
-
- mean(two_dimension)
- flattened_seq=[1,5,6,8,1,3,4,5]
- mean(flattened_seq)
-
-As you can see both the results are same. The other is mean
-of each column.::
-
- mean(two_dimension,0)
- array([ 1. , 4. , 5. , 6.5])
-
-or along the two rows seperately.::
-
- mean(two_dimension,1)
- array([ 5. , 3.25])
-
-We can see more option of mean using ::
-
- mean?
-
-Similarly we can calculate median and stanard deviation of a list
-using the functions median and std::
-
- median(age_list)
- std(age_list)
-
-
-
-Now lets apply this to a real world example ::
-
-We will a data file that is at the a path
-``/home/fossee/sslc2.txt``.It contains record of students and their
-performance in one of the State Secondary Board Examination. It has
-180, 000 lines of record. We are going to read it and process this
-data. We can see the content of file by double clicking on it. It
-might take some time to open since it is quite a large file. Please
-don't edit the data. This file has a particular structure.
-
-We can do ::
-
- cat /home/fossee/sslc2.txt
-
-to check the contents of the file.
-
-Each line in the file is a set of 11 fields separated
-by semi-colons Consider a sample line from this file.
-A;015163;JOSEPH RAJ S;083;042;47;00;72;244;;;
-
-The following are the fields in any given line.
-* 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
-*
-
-Now lets try and find the mean of English marks of all students.
-
-For this we do. ::
-
- L=loadtxt('/home/fossee/sslc2.txt',usecols=(3,),delimiter=';')
- L
- mean(L)
-
-loadtxt function loads data from an external file.Delimiter specifies
-the kind of character are the fields of data seperated by.
-usecols specifies the columns to be used so (3,). The 'comma' is added
-because usecols is a sequence.
-
-To get the median marks. ::
-
- median(L)
-
-Standard deviation. ::
-
- std(L)
-
-
-Now lets try and and get the mean for all the subjects ::
-
- L=loadtxt('sslc2.txt',usecols=(3,4,5,6,7),delimiter=';')
- mean(L,0)
- array([ 73.55452504, 53.79828941, 62.83342759, 50.69806158, 63.17056881])
-
-As we can see from the result mean(L,0). The resultant sequence
-is the mean marks of all students that gave the exam for the five subjects.
-
-and ::
-
- mean(L,1)
-
-
-is the average accumalative marks of individual students. Clearly, mean(L,0)
-was a row wise calcultaion while mean(L,1) was a column wise calculation.
-
-
-{{{ Show summary slide }}}
-
-This brings us to the end of the tutorial.
-we have learnt
-
- * How to do the standard statistical operations sum , mean
- median and standard deviation in Python.
- * Combine text loading and the statistical operation to solve
- real world problems.
-
-{{{ Show the "sponsored by FOSSEE" slide }}}
-
-
-This tutorial was created as a part of FOSSEE project, NME ICT, MHRD India
-
-Hope you have enjoyed and found it useful.
-Thankyou
-
-.. Author : Amit Sethi
- Internal Reviewer 1 :
- Internal Reviewer 2 :
- External Reviewer :
-