Nirmala Venkat at 11:03, 4 May 2018

2018-05-04T11:03:08Z

Priyacst: Created page with " {| style="border-spacing:0;" | style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"|
2018-05-03T07:30:29Z

Created page with " {| style="border-spacing:0;" | style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| <ce..."

New page

{| style="border-spacing:0;"
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| <center>'''Visual Cue'''</center>
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| <center>'''Narration'''</center>

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| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Show Slide
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Hello Friends. Welcome to the tutorial on "'''Statistics'''” using '''Python'''

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| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Show Slide

Objectives

| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| At the end of this tutorial, you will be able to -

* Do '''statistical''' operations in '''Python'''
* '''Sum''' a set of numbers
* Find their '''mean''', '''median''' and '''standard''' '''deviation'''

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| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Show Slide

System Specifications
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| To record this tutorial, I am using

* '''Ubuntu Linux 16.04''' operating system
* '''Python 3.4.3'''
* '''IPython 5.1.0'''

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| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Show Slide:

Pre-requisites

* Load data from files
* Use Lists
* Access parts of Arrays

| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| To practise this tutorial, you should know how to -

* load data from files
* use Lists and
* access parts of Arrays

If not, see the pre-requisite '''Python''' tutorials on this website.

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| <nowiki>[File Browser]</nowiki>

open and Show''' '''the''' '''file''' student_record.txt'''

'''1:08 - text box'''
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| For this tutorial, we will use the data file '''student_record.txt '''which we used in the earlier tutorial.

You can also find this file''' '''in the '''code files''' link of this tutorial.

Please download it in '''Home''' directory and use it.

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| <nowiki>[File Browser]</nowiki>

Show''' '''the''' '''file''' student_record.txt'''
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| We will use mathematical and logical operations on this array structured file.

For this, we need to install Numpy.

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| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Numpy(Numerical Python)

slide:

| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| NumPy, stands for Numerical Python

It is a library consisting of precompiled functions for mathematical and numerical routines

NumPy has to be installed separately.

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| <nowiki>Open terminal by pressing Ctrl+Alt+T keys simultaneously [Terminal]</nowiki>
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Let us first open the '''Terminal '''by pressing '''Ctrl+Alt+T '''keys simultaneously.

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| <nowiki>[Terminal] Install latest Python </nowiki>

type '''sudo apt-get install python3-pip'''
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Let us install latest '''pip'''.

'''pip''' command is used to install''' python libraries.'''

Type, '''sudo apt-get install python3 '''''hyphen '''''pip'''

You need to have root access for installation as it asks for admin password.

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| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Install '''numpy'''

'''type'''

'''sudo pip3 install numpy==1.13.3'''
| style="background-color:#ffffff;border:1pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.014cm;padding-right:0.191cm;"| Next, we need to install numpy library as we will be using numpy library throughout the tutorial.

Type, '''sudo pip3 install numpy equal to equalto 1.13.3'''

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Highlight prompt after installation
| style="background-color:#ffffff;border:1pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.014cm;padding-right:0.191cm;"| The installation is completed successfully.

We can see the terminal prompt without any error.

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| '''Slide:loadtxt()'''

| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Next we will learn about '''loadtxt'''() function.

To get the data as an array, we use the '''loadtxt()''' function.

For '''loadtxt() '''function''', '''we need to import '''numpy''' library first.

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| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| '''<nowiki>[Terminal] type ipython3</nowiki>'''
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Now, type '''ipython3''' and press '''Enter'''.

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| <nowiki>[IPython Terminal]</nowiki>

Type

'''import numpy as np'''
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Type, '''import numpy as np''' and press enter.

Where '''np''' is alias to numpy and it can be any name.

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| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Type

'''L=np.loadtxt('student_record.txt', usecols=(3,4,5,6,7), delimiter=';')'''

Type''' L '''and press''' enter'''
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Let us load the data from the file '''student_record.txt '''as an array.

Type,

'''L''' ''is equal to'' '''np '''''dot '''''loadtxt''' ''inside parentheses inside quotes'' '''student_record.txt''' ''comma'' usecols is equal to inside parentheses 3 comma 4 comma 5 comma 6 comma 7 comma delimiter is equal to inside quotes semicolon.

Press Enter.

Type''' L '''and press''' enter'''

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Highlight the output
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| We get the '''output''' in the form of an '''array'''.

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Highlight command one by one
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| '''loadtxt''' loads data from an external file.

'''Delimiter''' specifies the kind of character, that the fields of data is separated by.

'''usecols''' specifies the columns to be used.

loadtxt, delimiter and usecols are keywords.

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Highlight command one by one
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| So columns 3,4,5,6,7 from '''student_record.txt '''are loaded here.

The 'comma' between column numbers is added because '''usecols''' is a '''sequence'''.

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| <nowiki>[IPython Terminal]</nowiki>

Type '''L.shape'''
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| As we can see '''L''' is an '''array'''.

We can get the shape of this '''array''' using '''shape'''

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Type

'''L.shape'''
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Type,

'''L '''''dot''''' shape '''and press enter.

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| <nowiki>[IPython Terminal]</nowiki>

4:45

Highlight '''(185667, 5)'''
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| We get a '''tuple''' giving the numbers of '''rows''' and '''columns''' respectively.

In this example, the array '''L '''has 185667 rows and 5 columns.

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"|
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Let us switch back to the '''student_record.tx'''t file.

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Highlight record
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Let us start applying statistical operations on these.

How do you find the '''sum''' of marks of all subjects for the first student?

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| <nowiki>[IPython Terminal]</nowiki>

Type

'''<nowiki>L[0]</nowiki>'''
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Switch back to the terminal.

To access the first row in an array, we will type '''L '''''inside square brackets '''''0 '''and press enter.

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| <nowiki>[IPython Terminal]</nowiki>

Type

'''<nowiki>totalmarks=sum(L[0])</nowiki>'''
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Now to '''sum''' this, type,

'''totalmarks '''''is equal to '''''sum '''''inside parentheses '''''L '''''inside square brackets 0 ''

Press Enter

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Type '''totalmarks'''

Highlight 177.0
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Type, '''totalmarks'''

Press Enter

We got '''sum''' of marks of all subjects of the first student.

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| <nowiki>[IPython Terminal]</nowiki>

Type

'''<nowiki>totalmarks/len(L[0])</nowiki>'''

Highlight 35.399999999999999
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Now to get the '''mean''' we can divide the '''totalmarks''' by the length of the '''array.'''

Type,

'''totalmarks '''divided by '''len''' ''inside parentheses '''''L'' '''inside square brackets '''''0.'''

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| <nowiki>[IPython Terminal]</nowiki>

Type

'''np.<nowiki>mean(L[0])</nowiki>'''
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Or simply use the '''function mean'''.Type '''np '''''dot '''''mean '''''inside parentheses '''''L'' '''inside square brackets '''''0.'''

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| <nowiki>[IPython Terminal]</nowiki>

Type

'''np.mean?'''
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| But we have such a large '''data''' '''set'''.

And calculating the '''mean''' for each student one by one is time consuming.

Is there a way to reduce the work?

<nowiki><pause></nowiki>

For this we will look into the '''documentation''' of '''mean.'''

Type, '''np '''''dot '''''mean '''''questionmark''

Read the text for more information.

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Type '''q '''and press '''enter'''
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Type '''q '''and press '''enter '''to exit the documentation.

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| show slide

Two-Dimensional array
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| In the above example, '''L''' is a '''two dimensional array '''like matrix.

We can calculate the '''mean''' across each of the '''axis''' of the '''array'''.

The '''axis''' of '''rows''' is referred by 0 and '''columns''' by 1.

To calculate '''mean''' across all columns, we have to pass extra parameter, 1 for the '''axis'''.

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| <nowiki>[IPython Terminal]</nowiki>

Type

'''np.mean(L,0)'''
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Switch back to the terminal.

Let us calculate, '''mean''' of the marks scored by all the students for each subject.

Type '''np''' ''dot''' ''mean '''''inside parentheses '''''L '''''comma '''0''' ''

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| <nowiki>[IPython Terminal]</nowiki>

Type

'''<nowiki>L[:,0]</nowiki>'''

Highlight output '''<nowiki>array([ 53., </nowiki>58., 72., ..., 49., 33., 17.])'''
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Next, we will calculate the '''median''' of English marks for all the students.

Type '''L '''''inside square brackets '''''colon''''' comma '''0'''''

Note :, displays first '''column''' in the '''array''' i.e (that is) English Mark.

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| <nowiki>[IPython Terminal]</nowiki>

Type

'''np.<nowiki>median(L[:,0])</nowiki>'''
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| To get the '''median''' we will simply use the '''function median'''.

Type '''np '''''dot '''''median '''''inside parentheses '''''L '''''inside square brackets '''''colon''''' comma '''0'''''

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| <nowiki>[IPython Terminal]</nowiki>

Type

'''np.median(L,0)'''
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| For all the subjects, we can calculate '''median''' across all '''rows''' using '''median function''' as shown here.

Type '''np '''''dot '''''median '''''inside parentheses '''''L '''''comma '''0'''''

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| <nowiki>[IPython Terminal]</nowiki>

Type

'''np.<nowiki>std(L[:,0])</nowiki>'''
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Similarly to calculate '''standard''' '''deviation''' we will use the '''function''' '''std'''

Standard deviation for english subject can be found by typing

'''np '''''dot '''s''td '''''inside parentheses '''''L '''''inside square brackets '''''colon''''' comma '''0'''''

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| <nowiki>[IPython Terminal]</nowiki>Type

'''np.std(L,0)'''
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| And for all rows, we do,'''np '''''dot '''s''td '''''inside parentheses '''''L '''''comma '''0.'''''

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"|
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Pause the video here, try out the following exercise and resume the video.

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Show Slide

Exercise 1
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Refer to the file''' football.txt''', that is available in the code files link of this tutorial.

Download and save the file in the present working directory.

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| highlight
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| In '''football.txt''',

* the first column is '''player name''',
* second is '''goals''' '''at home''' and
* third column is '''goals away'''.

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Show Slide

Exercise 1
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| # Find the total goals for each player
# '''Mean''' of home and goals away
# '''Standard''' '''deviation''' of home and goals away

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Ipython Terminal

Type

'''L=np.loadtxt('football.txt',usecols=(1,2), delimiter=',')'''

'''sum(L,1)'''

| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Switch to the terminal,

The solution is,

First,

Type,

'''L''' ''is equal to'' '''np '''''dot '''''loadtxt''' ''inside parentheses inside quotes'' '''football.txt''' ''comma'' usecols is equal to inside parentheses 1 comma 2 comma delimiter is equal to inside quotes comma.

Press enter.

'''np '''''dot''''' sum '''''inside parentheses '''''L '''''comma '''''1.'''

Press enter.

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Ipython Terminal

Type''' np.mean(L,0)'''
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Second,

'''np '''''dot '''''mean '''''inside parentheses '''''L '''''comma '''''0.'''

Press enter.

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| <nowiki>[</nowiki>Ipython Termina]

Type''' np.std(L,0)'''
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Third,

'''np '''''dot '''''std '''''inside parentheses '''''L '''''comma '''''0.'''

|-
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Show Slide

Summary

| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| This brings us to the end of the tutorial.

In this tutorial, we have learnt to,

do the standard '''statistical''' '''operations''' like:

'''sum'''

'''mean'''

'''median''' and

'''standard deviation''' in '''Python'''.

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Assignment

| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Here are some self assessment questions for you to solve

# Given a '''two''' '''dimensional''' '''list '''as, '''<nowiki>two_dimensional_list=[[3,5,8,2,1],[4,3,6,2,1]]</nowiki>''' how do you calculate the mean of each row?
# Calculate the '''median''' of the given '''list'''? '''<nowiki>student_marks=[74,78,56,87,91,82]</nowiki>'''

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Assignment
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| # There is a '''file''' with 6 columns. But we want to load text only from columns 2,3,4,5.

How do we specify that?

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Solution
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| And the answers,

1. To get the mean of each row, we just pass 1 as the second parameter to the function''' mean'''. '''np.mean(two_dimensional_list, 1)'''

2. We use the '''function median''' to calculate the '''median''' of the '''list'''

'''np.median(student_marks)'''

3. To specify the particular columns of a file, we use the parameter '''usecols=(2, 3, 4, 5)'''

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Acknowledgment http://spoken-tutorial.org
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For more details, visit this website.

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@@ Line 51: / Line 51: @@
 * use Lists and
 * access parts of Arrays
-−
 If not, see the pre-requisite '''Python''' tutorials on this website.
@@ Line 108: / Line 108: @@
-Type, '''sudo apt-get install python3 '''''hyphen '''''pip'''
+Type, '''sudo apt-get install python3 '''''hyphen '''''pip''' and press Enter.
@@ Line 169: / Line 169: @@
-Type, '''L''' ''is equal to'' '''np '''''dot '''''loadtxt''' ''inside parentheses inside quotes'' '''student_record.txt''' ''comma'' '''usecols is equal to inside parentheses''' 3 comma 4 comma 5 comma 6 comma 7 comma '''delimiter''' ''is equal to inside quotes'' semicolon. Press '''Enter'''.
+Type, '''L''' ''is equal to'' '''np '''''dot '''''loadtxt''' ''inside parentheses inside quotes'' '''student_record.txt''' ''comma'' '''usecols''' is equal to inside parentheses 3 comma 4 comma 5 comma 6 comma 7 comma '''delimiter''' ''is equal to inside quotes'' semicolon. Press '''Enter'''.
@@ Line 221: / Line 221: @@
-In this example, the array '''L '''has 185667 rows and 5 columns.
+In this example, the array '''L '''has one lakh eighty five thousand six hundred and sixty seven rows and 5 columns.
 |-
@@ Line 359: / Line 359: @@
-Note colon comma displays first '''column''' in the '''array''' i.e (that is) English Mark.
+Note colon comma zero displays first '''column''' in the '''array''' i.e (that is) English Mark.
@@ Line 513: / Line 513: @@
 | style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Here are some self assessment questions for you to solve
-# Given a '''two''' '''dimensional''' '''list '''as shown.how do you calculate the mean of each row
+# Given a '''two''' '''dimensional''' '''list '''as shown. How do you calculate the mean of each row
 # Calculate the '''median''' of the given '''list'''?
@@ Line 522: / Line 522: @@
 Assignment
-| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| # There is a '''file''' with 6 columns. But we want to load text only from columns 2,3,4,5.
+| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"|
 How do we specify that?

Python-3.4.3/C2/Statistics/English - Revision history

Nancyvarkey at 16:02, 6 May 2018

Nirmala Venkat at 11:03, 4 May 2018

Priyacst at 10:32, 4 May 2018