Difference between revisions of "Python-3.4.3/C2/Statistics/English"
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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;"| At the end of this tutorial, you will be able to - | | 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''' | * Do '''statistical''' operations in '''Python''' | ||
* '''Sum''' a set of numbers | * '''Sum''' a set of numbers | ||
− | * Find their '''mean | + | * Find their '''mean, median''' and '''standard deviation''' |
− | + | ||
− | + | ||
|- | |- | ||
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* '''Python 3.4.3 '''and | * '''Python 3.4.3 '''and | ||
* '''IPython 5.1.0''' | * '''IPython 5.1.0''' | ||
− | |||
− | |||
|- | |- | ||
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* load data from files | * load data from files | ||
− | * use Lists and | + | * use '''Lists''' and |
− | * access parts of Arrays | + | * access parts of '''Arrays''' |
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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>[File Browser]</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>[File Browser]</nowiki> | ||
− | open and Show | + | open and Show the file''' student_record.txt''' |
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− | You can also find this file | + | You can also find this file in the '''Code Files''' link of this tutorial. |
− | Please download it in '''Home''' | + | Please download it in '''Home directory''' and use it. |
|- | |- | ||
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Show''' '''the''' '''file''' student_record.txt''' | 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. | + | | 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'''. |
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− | It is a library consisting of | + | It is a library consisting of '''pre-compiled functions''' for mathematical and numerical routines. |
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− | Type, '''sudo apt-get install python3 ''''' | + | Type, '''sudo apt-get install python3 hyphen pip''' and press '''Enter'''. |
− | You need to have '''root''' access for installation as it asks for '''admin | + | 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 | + | | 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. |
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− | We can see the terminal prompt without any error. | + | We can see the '''terminal prompt''' without any error. |
|- | |- | ||
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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;"| Next we will learn about '''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()''' | + | To get the data as an '''array''', we use the '''loadtxt() function.''' |
− | For '''loadtxt() | + | 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;"| Switch back 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 back to the '''terminal'''. |
Now, type '''ipython3''' and press '''Enter'''. | 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 | + | | 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''' L '''and 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;"| Let us load the data from the file '''student_record.txt '''as 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;"| Let us load the data from the file '''student_record.txt '''as an '''array'''. |
− | Type, '''L | + | 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''' | + | Type''' L '''and press''' Enter'''. |
|- | |- | ||
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− | '''Delimiter''' specifies the kind of character | + | '''Delimiter''' specifies the kind of character that the '''fields''' of data is separated by. |
− | '''usecols''' specifies the columns to be used. | + | '''usecols''' specifies the '''columns''' to be used. |
− | '''loadtxt, delimiter''' and '''usecols''' are keywords. | + | '''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;"| 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. | + | | 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'''. | + | The 'comma' between '''column numbers''' is added because '''usecols''' is a '''sequence'''. |
|- | |- | ||
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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.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 | + | | 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'''. |
|- | |- | ||
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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;"| | | 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. | + | | 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.txt''' file. |
|- | |- | ||
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− | How do you find the | + | How do you find the sum of marks of all subjects for the first student? |
|- | |- | ||
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'''<nowiki>L[0]</nowiki>''' | '''<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. | + | | 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 | + | To access the first row in an '''array''', we will type '''L '''inside square brackets '''0 '''and press '''Enter'''. |
|- | |- | ||
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'''<nowiki>totalmarks=sum(L[0])</nowiki>''' | '''<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 | + | | 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 | + | '''totalmarks '''is equal to '''sum '''inside parentheses '''L '''inside square brackets '''0 ''' |
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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 | + | | 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.''' |
− | We got | + | We got sum of marks of all subjects of the first student. |
|- | |- | ||
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− | Type, '''totalmarks '''divided by '''len | + | Type, '''totalmarks '''divided by '''len''' inside parentheses '''L''' inside square brackets '''''0 '''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;"| Or simply use the '''function mean'''. | | 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 | + | Type '''np dot mean''' inside parentheses '''L '''inside square brackets '''0 '''and press''' Enter.''' |
|- | |- | ||
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− | For this we will look into the '''documentation''' of '''mean.''' | + | For this, we will look into the '''documentation''' of '''mean.''' |
− | Type, '''np | + | Type, '''np dot mean questionmark '''and press Enter''.'' |
Read the text for more information. | Read the text for more information. | ||
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Two-Dimensional array | 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. | + | | 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'''. |
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− | To calculate '''mean''' across all columns, we have to pass extra parameter | + | To calculate '''mean''' across all '''columns''', we have to pass extra parameter 1 for the '''axis'''. |
|- | |- | ||
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'''np.mean(L,0)''' | '''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. | + | | 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'''. |
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− | Type '''np | + | Type '''np dot mean '''inside parentheses '''L comma 0''' ''and press '''Enter'''. |
|- | |- | ||
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− | Type '''L | + | Type '''L '''inside square brackets '''colon comma 0 '''and press '''Enter'''. |
− | + | ||
− | + | ||
− | + | ||
− | + | ||
+ | Note '''colon comma zero''' displays first '''column''' in the '''array''' 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 | + | Type '''np dot median '''inside parentheses '''L '''inside square brackets '''colon''' comma '''0 ''' |
− | Press | + | Press '''Enter'''. |
|- | |- | ||
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− | Type '''np | + | Type '''np dot median '''inside parentheses '''L comma 0''' |
− | Press | + | Press '''Enter'''. |
|- | |- | ||
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'''np.<nowiki>std(L[:,0])</nowiki>''' | '''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 | + | | 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 | + | Standard deviation for English subject can be found by typing '''np dot std '''inside parentheses '''L '''inside square brackets '''colon comma 0''' |
− | Press Enter. | + | 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 | + | | 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 std '''inside parentheses '''L comma 0 '''and press '''Enter.''' |
|- | |- | ||
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Exercise 1 | 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 | + | | 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. | + | Download and save the file in the '''present working directory'''. |
− | Currently the present working directory is the '''Home''' | + | Currently the '''present working directory''' is the '''Home directory.''' |
|- | |- | ||
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* second is '''goals''' '''at home''' and | * second is '''goals''' '''at home''' and | ||
* third column is '''goals away'''. | * third column is '''goals away'''. | ||
− | |||
− | |||
|- | |- | ||
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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;"| # Find the total goals for each player | | 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 | # '''Mean''' of home and goals away | ||
− | # '''Standard | + | # '''Standard deviation''' of home and goals away |
− | + | ||
− | + | ||
|- | |- | ||
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The solution is, first, type, | The solution is, first, type, | ||
− | '''L | + | '''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 | + | Press '''Enter'''. |
− | '''np | + | '''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;"| Answer for the second, '''np | + | | 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'''. |
|- | |- | ||
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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, '''np | + | | 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'''. |
|- | |- | ||
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− | In this tutorial, we have learnt to | + | In this tutorial, we have learnt to 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 shown, how do you calculate the '''mean''' of each row? | ||
+ | # 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;"| | | 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. | + | # 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? | How do we specify that? | ||
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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 | + | 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''' |
|- | |- |
Latest revision as of 21:32, 6 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
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Show Slide:
Pre-requisites
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To practise this tutorial, you should know how to -
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[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.
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[File Browser]
Show the file student_record.txt |
We will use mathematical and logical operations on this array structured file.
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Numpy(Numerical Python)
slide:
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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.
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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.
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Highlight prompt after installation | The installation is completed successfully.
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Slide:loadtxt()
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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.
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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.
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Highlight command one by one | So columns 3,4,5,6,7 from student_record.txt are loaded here.
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[IPython Terminal]
Type L.shape |
As we can see L is an array.
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Type L.shape | Type, L dot shape and press Enter. |
[IPython Terminal]
4:45
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We get a tuple giving the numbers of rows and columns respectively.
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Let us switch back to the student_record.txt file. | |
Highlight record | Let us start applying statistical operations on these.
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[IPython Terminal]
Type L[0] |
Switch back to the terminal.
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[IPython Terminal]
Type totalmarks=sum(L[0]) |
Now to sum this, type,
totalmarks is equal to sum inside parentheses L inside square brackets 0
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Type totalmarks
Highlight 177.0 |
Type totalmarks and press Enter.
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[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.
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[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.
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[IPython Terminal]
Type np.mean(L,0) |
Switch back to the terminal.
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[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.
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[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 |
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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