Difference between revisions of "Python-3.4.3/C2/Statistics/English"
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* '''Ubuntu Linux 16.04''' operating system | * '''Ubuntu Linux 16.04''' operating system | ||
− | * '''Python 3.4.3''' | + | * '''Python 3.4.3 '''and |
* '''IPython 5.1.0''' | * '''IPython 5.1.0''' | ||
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Pre-requisites | Pre-requisites | ||
− | |||
* Load data from files | * Load data from files | ||
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* use Lists and | * use Lists and | ||
* access parts of Arrays | * access parts of Arrays | ||
+ | * | ||
If not, see the pre-requisite '''Python''' tutorials on this website. | If not, see the pre-requisite '''Python''' tutorials on this website. | ||
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− | For this, we need to install Numpy. | + | 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, stands for Numerical Python | + | | 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 | + | It is a library consisting of precompiled functions for mathematical and numerical routines. |
− | NumPy has to be installed separately. | + | '''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;"| | + | | style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Open 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;"| 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;"| Let us first open the '''Terminal '''by pressing '''Ctrl+Alt+T '''keys simultaneously. | ||
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− | You need to have root access for installation as it asks for admin password. | + | You need to have '''root''' access for installation as it asks for '''admin''' '''password'''. |
|- | |- | ||
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'''sudo pip3 install numpy==1.13.3''' | '''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. | + | | 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 | + | Type, '''sudo pip3 install numpy '''is equal to is equal to''' 1.13.3 '''and press''' Enter.''' |
|- | |- | ||
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To get the data as an array, we use the '''loadtxt()''' function. | To get the data as an array, we use the '''loadtxt()''' function. | ||
− | For '''loadtxt() '''function''', '''we need to import '''numpy''' library first. | + | For '''loadtxt() '''function''', '''we need to '''import''' '''numpy''' library first. |
|- | |- | ||
| 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;"| '''<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;"| Switch back to the terminal. |
+ | |||
+ | Now, type '''ipython3''' and press '''Enter'''. | ||
|- | |- | ||
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'''import numpy as np''' | '''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 | + | | 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. | Where '''np''' is alias to numpy and it can be any name. | ||
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− | Type, | + | 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''' | Type''' L '''and press''' enter''' | ||
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− | loadtxt, delimiter and usecols are keywords. | + | '''loadtxt, delimiter''' and '''usecols''' are keywords. |
|- | |- | ||
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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;"| As we can see '''L''' is 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;"| As we can see '''L''' is an '''array'''. | ||
− | We can get the shape of this '''array''' using '''shape''' | + | |
+ | 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 | + | | 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'''. | |
− | '''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 | + | |
|- | |- | ||
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− | To access the first row in an array, we will type '''L '''''inside square brackets '''''0 '''and press | + | To access the first row in an array, we will type '''L '''''inside square brackets '''''0 '''and press '''Enter'''. |
|- | |- | ||
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'''totalmarks '''''is equal to '''''sum '''''inside parentheses '''''L '''''inside square brackets 0 '' | '''totalmarks '''''is equal to '''''sum '''''inside parentheses '''''L '''''inside square brackets 0 '' | ||
− | Press Enter | + | |
+ | Press '''Enter.''' | ||
|- | |- | ||
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Highlight 177.0 | 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''' | + | | 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 '''and press '''Enter.''' |
− | + | ||
− | + | ||
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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;"| Now to get the '''mean''' we can divide the '''totalmarks''' by the length of the '''array.''' | | 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.''' | ||
− | |||
− | '''totalmarks '''divided by '''len''' ''inside parentheses '''''L'' '''inside square brackets '''''0.''' | + | Type, '''totalmarks '''divided by '''len''' ''inside parentheses '''''L'' '''inside square brackets '''''0 '''and press '''Enter.''' |
|- | |- | ||
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'''np.<nowiki>mean(L[0])</nowiki>''' | '''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;"| Or simply use the '''function mean'''. |
+ | |||
+ | Type '''np '''''dot '''''mean '''''inside parentheses '''''L'' '''inside square brackets '''''0 '''and press''' Enter.''' | ||
|- | |- | ||
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Is there a way to reduce the work? | Is there a way to reduce the work? | ||
− | |||
For this we will look into the '''documentation''' of '''mean.''' | For this we will look into the '''documentation''' of '''mean.''' | ||
− | Type, '''np '''''dot '''''mean '''''questionmark'' | + | |
+ | Type, '''np '''''dot '''''mean '''''questionmark ''and press Enter''.'' | ||
Read the text for more information. | Read the text for more information. | ||
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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 '''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''' | ||
− | | 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 | + | | 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 '''to exit the documentation. |
|- | |- | ||
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Let us calculate, '''mean''' of the marks scored by all the students for each subject. | Let us calculate, '''mean''' of the marks scored by all the students for each subject. | ||
− | Type '''np''' ''dot''' ''mean '''''inside parentheses '''''L '''''comma '''0''' '' | + | |
+ | Type '''np''' ''dot''' ''mean '''''inside parentheses '''''L '''''comma '''0''' ''and press Enter''.'' | ||
|- | |- | ||
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− | Type '''L '''''inside square brackets '''''colon''''' comma '''0''''' | + | Type '''L '''''inside square brackets '''''colon''''' comma '''0 '''''and press Enter'''''.''''' |
− | Note | + | Note colon comma displays first '''column''' in the '''array''' i.e (that is) English Mark. |
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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;"| To get the '''median''' we will simply use the '''function median'''. | | 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''''' | + | Type '''np '''''dot '''''median '''''inside parentheses '''''L '''''inside square brackets '''''colon''''' comma '''0 ''''' |
+ | |||
+ | |||
+ | Press Enter'''''.''''' | ||
|- | |- | ||
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Type '''np '''''dot '''''median '''''inside parentheses '''''L '''''comma '''0''''' | Type '''np '''''dot '''''median '''''inside parentheses '''''L '''''comma '''0''''' | ||
+ | |||
+ | |||
+ | Press Enter'''''.''''' | ||
|- | |- | ||
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− | Standard deviation for | + | Standard deviation for English subject can be found by typing '''np '''''dot '''s''td '''''inside parentheses '''''L '''''inside square brackets '''''colon''''' comma '''0''''' |
− | + | ||
+ | Press Enter. | ||
|- | |- | ||
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'''np.std(L,0)''' | '''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;"| And for all rows, we do, '''np '''''dot '''s''td '''''inside parentheses '''''L '''''comma '''0 '''''and press Enter. |
|- | |- | ||
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Download and save the file in the present working directory. | Download and save the file in the present working directory. | ||
+ | |||
+ | |||
+ | Currently the present working directory is the '''Home''' directory. | ||
|- | |- | ||
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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;"| Switch to the terminal | + | | 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. | Press enter. | ||
− | |||
− | + | '''np '''''dot''''' sum '''''inside parentheses '''''L '''''comma '''''1 '''and press enter. | |
|- | |- | ||
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Type''' np.mean(L,0)''' | 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;"| | + | | style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Answer for the second, '''np '''''dot '''''mean '''''inside parentheses '''''L '''''comma '''''0 '''and press enter. |
− | + | ||
− | '''np '''''dot '''''mean '''''inside parentheses '''''L '''''comma '''''0 | + | |
− | + | ||
− | + | ||
|- | |- | ||
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Type''' np.std(L,0)''' | 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, | + | | 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 '''and press enter. |
− | + | ||
− | '''np '''''dot '''''std '''''inside parentheses '''''L '''''comma '''''0 | + | |
|- | |- | ||
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− | In this tutorial, we have learnt to, | + | In this tutorial, we have learnt to, do the standard '''statistical''' '''operations''' like: |
− | + | ||
− | do the standard '''statistical''' '''operations''' like: | + | |
'''sum''' | '''sum''' | ||
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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;"| Here are some self assessment questions for you to solve | | 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 | + | # Given a '''two''' '''dimensional''' '''list '''as shown.how do you calculate the mean of each row |
− | # Calculate the '''median''' of the given '''list'''? | + | # Calculate the '''median''' of the given '''list'''? |
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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;"| And the answers, | | 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 | + | 1. To get the mean of each row, we just pass 1 as the second parameter to the function''' mean'''. '''np.mean '''''inside parentheses''''' two_dimensional_list '''''comma''''' 1''' |
2. We use the '''function median''' to calculate the '''median''' of the '''list''' | 2. We use the '''function median''' to calculate the '''median''' of the '''list''' | ||
− | '''np.median | + | '''np.median '''''inside parentheses '''''student_marks''' |
− | 3. To specify the particular columns of a file, we use the parameter '''usecols | + | 3. 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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Fossee Forum | Fossee Forum | ||
− | | style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Please post your general queries on Python in this forum. | + | | style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Please post your general queries on '''Python''' in this forum. |
|- | |- | ||
− | | 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;"| Show Slide Textbook Companion |
− | + | ||
− | Textbook Companion | + | |
| style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| FOSSEE team coordinates the TBC project. | | style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| FOSSEE team coordinates the TBC project. | ||
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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;"| Spoken Tutorial Project is funded by NMEICT, MHRD, Govt. of India. | | style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Spoken Tutorial Project is funded by NMEICT, MHRD, Govt. of India. | ||
− | For more details, visit this website. | + | For more details, visit 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;"| Previous slide | | style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Previous slide | ||
− | | style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| This is Trupti | + | | style="background-color:#ffffff;border:0.5pt solid #000001;padding-top:0cm;padding-bottom:0cm;padding-left:0.088cm;padding-right:0.191cm;"| Thats it for the tutorial. |
+ | |||
+ | |||
+ | This is Trupti Kini from IIT Bombay signing off. Thank you. | ||
|} | |} |
Revision as of 16:02, 4 May 2018
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Show Slide | Hello Friends. Welcome to the tutorial on "Statistics” using Python |
Show Slide
Objectives
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At the end of this tutorial, you will be able to -
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Show Slide
System Specifications |
To record this tutorial, I am using
|
Show Slide:
Pre-requisites
|
To practise this tutorial, you should know how to -
If not, see the pre-requisite Python tutorials on this website. |
[File Browser]
open and Show the file student_record.txt
|
For this tutorial, we will use the data file student_record.txt which we used in the earlier tutorial.
|
[File Browser]
Show the file student_record.txt |
We will use mathematical and logical operations on this array structured file.
|
Numpy(Numerical Python)
slide:
|
NumPy, stands for Numerical Python.
|
Open terminal by pressing Ctrl+Alt+T keys simultaneously | Let us first open the Terminal by pressing Ctrl+Alt+T keys simultaneously. |
[Terminal] Install latest Python
type sudo apt-get install python3-pip |
Let us install latest pip.
|
Install numpy
type sudo pip3 install numpy==1.13.3 |
Next, we need to install numpy library as we will be using numpy library throughout the tutorial.
|
Highlight prompt after installation | The installation is completed successfully.
|
Slide:loadtxt()
|
Next we will learn about loadtxt() function.
For loadtxt() function, we need to import numpy library first. |
[Terminal] type ipython3 | Switch back to the terminal.
Now, type ipython3 and press Enter. |
[IPython Terminal]
Type import numpy as np |
Type, import numpy as np and press Enter.
Where np is alias to numpy and it can be any name. |
Type
L=np.loadtxt('student_record.txt', usecols=(3,4,5,6,7), delimiter=';')
|
Let us load the data from the file student_record.txt as an array.
|
Highlight the output | We get the output in the form of an array. |
Highlight command one by one | loadtxt loads data from an external file.
|
Highlight command one by one | So columns 3,4,5,6,7 from student_record.txt are loaded here.
|
[IPython Terminal]
Type L.shape |
As we can see L is an array.
|
Type L.shape | Type, L dot shape and press Enter. |
[IPython Terminal]
4:45
|
We get a tuple giving the numbers of rows and columns respectively.
|
Let us switch back to the student_record.txt file. | |
Highlight record | Let us start applying statistical operations on these.
|
[IPython Terminal]
Type L[0] |
Switch back to the terminal.
|
[IPython Terminal]
Type totalmarks=sum(L[0]) |
Now to sum this, type,
totalmarks is equal to sum inside parentheses L inside square brackets 0
|
Type totalmarks
Highlight 177.0 |
Type, totalmarks and press Enter.
|
[IPython Terminal]
Type totalmarks/len(L[0]) Highlight 35.399999999999999 |
Now to get the mean we can divide the totalmarks by the length of the array.
|
[IPython Terminal]
Type np.mean(L[0]) |
Or simply use the function mean.
Type np dot mean inside parentheses L inside square brackets 0 and press Enter. |
[IPython Terminal]
Type np.mean? |
But we have such a large data set.
Read the text for more information. |
Type q and press enter | Type q to exit the documentation. |
show slide
Two-Dimensional array |
In the above example, L is a two dimensional array like matrix.
|
[IPython Terminal]
Type np.mean(L,0) |
Switch back to the terminal.
|
[IPython Terminal]
Type L[:,0] Highlight output array([ 53., 58., 72., ..., 49., 33., 17.]) |
Next, we will calculate the median of English marks for all the students.
|
[IPython Terminal]
Type np.median(L[:,0]) |
To get the median we will simply use the function median.
Type np dot median inside parentheses L inside square brackets colon comma 0
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[IPython Terminal]
Type np.median(L,0) |
For all the subjects, we can calculate median across all rows using median function as shown here.
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[IPython Terminal]
Type np.std(L[:,0]) |
Similarly to calculate standard deviation we will use the function std
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[IPython Terminal]Type
np.std(L,0) |
And for all rows, we do, np dot std inside parentheses L comma 0 and press Enter. |
Pause the video here, try out the following exercise and resume the video. | |
Show Slide
Exercise 1 |
Refer to the file football.txt, that is available in the code files link of this tutorial.
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highlight | In football.txt,
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Show Slide
Exercise 1 |
# Find the total goals for each player
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Ipython Terminal
Type L=np.loadtxt('football.txt',usecols=(1,2), delimiter=',')
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Switch to the terminal.
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.
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Ipython Terminal
Type np.mean(L,0) |
Answer for the second, np dot mean inside parentheses L comma 0 and press enter. |
[Ipython Termina]
Type np.std(L,0) |
Third, np dot std inside parentheses L comma 0 and press enter. |
Show Slide
Summary
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This brings us to the end of the tutorial.
sum mean median and standard deviation in Python. |
Show Slide
Assignment
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Here are some self assessment questions for you to solve
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Show Slide
Assignment |
# 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? |
Show Slide
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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 inside parentheses two_dimensional_list comma 1 2. We use the function median to calculate the median of the list np.median inside parentheses student_marks 3. To specify the particular columns of a file, we use the parameter usecols is equal to inside parentheses 2, 3, 4, 5 |
Show SlideForum | Please post your timed queries in this forum. |
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Fossee Forum |
Please post your general queries on Python in this forum. |
Show Slide Textbook Companion | FOSSEE team coordinates the TBC project. |
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Acknowledgment http://spoken-tutorial.org |
Spoken Tutorial Project is funded by NMEICT, MHRD, Govt. of India.
For more details, visit this website. |
Previous slide | Thats it for the tutorial.
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