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{|border=1
| <center>'''Time'''</center>
| <center>'''Narration'''</center>

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| 00:01
| Hello Friends. Welcome to the tutorial on "'''Statistics'''” using '''Python'''

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| 00:07
| At the end of this tutorial, you will be able to - Do '''statistical''' operations in '''Python'''

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| 00:14
| '''Sum''' a set of numbers and Find their '''mean, median''' and '''standard deviation'''

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| 00:22
| To record this tutorial, I am using '''Ubuntu Linux 16.04''' operating system

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| 00:29
| '''Python 3.4.3 '''and '''IPython 5.1.0'''

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| 00:36
| To practise this tutorial, you should know how to load data from files

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| 00:42
| use '''Lists''' and access parts of '''Arrays'''

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| 00:47
|If not, see the pre-requisite '''Python''' tutorials on this website.

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| 00:53
| For this tutorial, we will use the data file '''student_record.txt '''which we used in the earlier tutorial.

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| 01:03
|You can also find this file in the '''Code Files''' link of this tutorial.

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| 01:08
|Please download it in '''Home directory''' and use it.

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| 01:12
| We will use mathematical and logical operations on this '''array structured file'''.

For this, we need to install '''Numpy'''.

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| 01:22
| '''NumPy''', stands for '''Numerical Python.'''

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| 01:26
|It is a library consisting of '''pre-compiled functions''' for mathematical and numerical routines.

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| 01:33
|'''NumPy''' has to be installed separately.

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| 01:37
| Let us first open the '''Terminal '''by pressing '''Ctrl+Alt+T '''keys simultaneously.

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|01:45
| Let us install latest '''pip'''.

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

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| 01:53
|Type, '''sudo apt-get install python3 hyphen pip''' and press '''Enter'''.

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| 02:03
|You need to have '''root''' access for installation as it asks for '''admin password'''.

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| 02:15
| Next, we need to install '''numpy library''' as we will be using '''numpy library''' throughout the tutorial.

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| 02:24
|Type, '''sudo pip3 install numpy '''is equal to is equal to''' 1.13.3 '''and press''' Enter.'''

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| 02:38
| The installation is completed successfully. We can see the '''terminal prompt''' without any error.

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| 02:47
| Next we will learn about '''loadtxt() function.'''

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| 02:52
|To get the data as an '''array''', we use the '''loadtxt() function.'''

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| 02:58
|For '''loadtxt() function''', we need to '''import numpy library''' first.

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| 03:04
| Switch back to the '''terminal'''.Now, type '''ipython3''' and press '''Enter'''.

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| 03:12
| Type '''import numpy as np''' and press '''Enter'''.

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

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| 03:24
| Let us load the data from the file '''student_record.txt '''as an '''array'''.

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| 03:32
|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''' and Press '''Enter'''.

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| 04:04
|Type''' L '''and press''' Enter'''.

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| 04:07
| We get the '''output''' in the form of an '''array'''.

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| 04:11
| '''loadtxt''' loads data from an external file.

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| 04:16
|
'''Delimiter''' specifies the kind of character that the '''fields''' of data is separated by.

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

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| 04:27
|'''loadtxt, delimiter''' and '''usecols''' are '''keywords'''.

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| 04:33
| So '''columns''' 3,4,5,6,7 from '''student_record.txt '''are loaded here.

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| 04:42
|The 'comma' between '''column numbers''' is added because '''usecols''' is a '''sequence'''.

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| 04:49
| As we can see '''L''' is an '''array'''. We can get the shape of this '''array''' using '''shape.'''

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| 04:58
| Type, '''L dot shape '''and press '''Enter'''.

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| 05:04
| We get a '''tuple''' giving the numbers of '''rows''' and '''columns''' respectively.

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| 05:11
|In this example, the array '''L '''has one lakh eighty five thousand six hundred and sixty seven rows and 5 columns.

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| 05:22
| Let us switch back to the '''student_record.txt''' file.

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| 05:28
| Let us start applying statistical operations on these.

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

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| 05:39
| Switch back to the '''terminal'''.

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

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|05:54
| Now to sum this, type, '''totalmarks '''is equal to '''sum '''inside parentheses '''L '''inside square brackets '''0 ''' and Press '''Enter.'''

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| 06:09
| Type '''totalmarks '''and press '''Enter.'''

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

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| 06:19
| Now to get the '''mean''' we can divide the '''totalmarks''' by the length of the '''array.'''

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| 06:26
|Type, '''totalmarks '''divided by '''len''' inside parentheses '''L''' inside square brackets '''''0 '''and press '''Enter.'''

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| 06:40
| Or simply use the '''function mean'''. Type '''np dot mean''' inside parentheses '''L '''inside square brackets '''0 '''and press''' Enter.'''

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| 06:55
| But we have such a large '''data''' '''set'''.

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

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| 07:04
|Is there a way to reduce the work?

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

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| 07:12
|Type, '''np dot mean questionmark '''and press Enter''.'' Read the text for more information.

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| 07:23
| Type '''q '''to exit the documentation.

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| 07:28
| In the above example, '''L''' is a '''two dimensional array '''like '''matrix'''.

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| 07:35
|We can calculate the '''mean''' across each of the '''axis''' of the '''array'''.

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| 07:41
|The '''axis''' of '''rows''' is referred by 0 and '''columns''' by 1.

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| 07:48
|To calculate '''mean''' across all '''columns''', we have to pass extra parameter 1 for the '''axis'''.

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| 07:57
| Switch back to the '''terminal'''.

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| 08:00
|Let us calculate, '''mean''' of the marks scored by all the students for each subject.

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| 08:07
|Type '''np dot mean '''inside parentheses '''L comma 0''' ''and press '''Enter'''.

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| 08:18
| Next, we will calculate the '''median''' of English marks for all the students.

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| 08:25
|Type '''L '''inside square brackets '''colon comma 0 '''and press '''Enter'''.

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| 08:35
|Note '''colon comma zero''' displays first '''column''' in the '''array''' that is, English Mark.

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| 08:45
| To get the '''median''' we will simply use the '''function median'''.

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| 08:51
|Type '''np dot median '''inside parentheses '''L '''inside square brackets '''colon''' comma '''0 '''

Press '''Enter'''.

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| 09:04
| For all the subjects, we can calculate '''median''' across all '''rows''' using '''median function''' as shown here.

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| 09:13
|Type '''np dot median '''inside parentheses '''L comma 0'''

Press '''Enter'''.

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| 09:24
| Similarly to calculate '''standard''' '''deviation''' we will use the '''function std'''

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| 09:31
|Standard deviation for English subject can be found by typing '''np dot std '''inside parentheses '''L '''inside square brackets '''colon comma 0'''. Press '''Enter'''.

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| 09:50
| And for all '''rows''', we do, '''np dot std '''inside parentheses '''L comma 0 '''and press '''Enter.'''

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| 10:03
| Pause the video here, try out the following exercise and resume the video.

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| 10:09
| Refer to the file''' football.txt''', that is available in the '''Code Files''' link of this tutorial.

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| 10:18
|Download and save the file in the '''present working directory'''.

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| 10:23
|Currently the '''present working directory''' is the '''Home directory.'''

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| 10:28
| In '''football.txt''', the first column is '''player name''',

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| 10:34
| Second is '''goals''' '''at home''' and third is '''goals away'''.

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| 10:42
| Find the total goals for each player

'''Mean''' of home and goals away

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| 10:50
| '''Standard deviation''' of home and goals away

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| 10:55
| Switch to the terminal.

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| 10:58
|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'''.

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| 11:31
|'''np dot sum '''inside parentheses '''L comma 1 '''and press '''Enter'''.

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| 11:39
| The answer for the second, '''np dot mean '''inside parentheses '''L comma 0 '''and press '''Enter'''.

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| 11:50
| Third, '''np dot std '''inside parentheses '''L comma 0 '''and press '''Enter'''.

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| 11:59
| 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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| 12:18
| Here are some self assessment questions for you to solve.

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| 12:23
| Given a '''two dimensional list '''as shown, how do you calculate the '''mean''' of each row?

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| 12:32
| Second. Calculate the '''median''' of the given '''list'''.

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| 12:37
| Third. 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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| 12:51
| And the answers,

To get the '''mean''' of each '''row''', we just pass 1 as the second '''parameter''' to the '''function mean'''

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| 13:02
| '''np.mean '''inside parentheses''' two_dimensional_list comma 1'''

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| 13:11
| We use the '''function median''' to calculate the '''median''' of the '''list'''

'''np.median '''inside parentheses '''student_marks'''

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| 13:24
|Third, To specify the particular '''columns''' of a file, we use the parameter '''usecols '''is equal to inside parentheses '''2, 3, 4, 5'''

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| 13:39
| Please post your timed queries in this forum.

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| 13:43
| Please post your general queries on '''Python''' in this forum.

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| 13:48
| FOSSEE team coordinates the TBC project.

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| 13:53
| Spoken Tutorial Project is funded by NMEICT, MHRD, Govt. of India.

For more details, visit this website.

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| 14:05
| Thats it for the tutorial.

This is Trupti Kini from IIT Bombay signing off. Thank you.

|}

Python-3.4.3/C3/Statistics/English-timed - Revision history

PoojaMoolya: Created page with " {|border=1 | '''Time''' | '''Narration''' |- | 00:01 | Hello Friends. Welcome to the tutorial on "'''Statistics'''” using '''Python''' |..."