Python for Science and Engg: Basic data processing (session 3)

Fossee

Description

Python for Science and Engg:Basic data processingFOSSEEDepartment of Aerospace EngineeringIIT BombaySciPy 2010, Introductory tutorials,Day 1, Session 3FOSSEE (IIT Bombay) Statistics 1 / 36Computing the meanOutline1 Computing the mean2 Processing voluminous dataData processingDictionariesVisualizing dataObtaining statisticsFOSSEE (IIT Bombay) Statistics 2 / 36Computing the meanValue of acceleration due to gravity?We already havependulum.txtqLWe know that T = 2g24 LSo g= 2TCalculate g - acceleration due to gravity for eachpair of L and THence calculate mean gFOSSEE (IIT Bombay) Statistics 3 / 36Computing the meanAcceleration due to gravity - g. . .In []: g_list = []In []: for line in open(’pendulum.txt’):.... point = line.split() L = float(point[0]).... t = float(point[1]) g = 4 pi pi L / (t t)* * * *.... g_list.append(g)FOSSEE (IIT Bombay) Statistics 4 / 36Computing the meanMean g - Classical methodIn []: total = 0In []: for g in g_list:....: total += gIn []: g_mean = total / len(g_list)In []: print ’Mean: ’, g_meanFOSSEE (IIT Bombay) Statistics 5 / 36Computing the meanMean g - Slightly improved methodIn []: g_mean = sum(g_list) / len(g_list)In []: print ’Mean: ’, g_meanFOSSEE (IIT Bombay) Statistics 6 / 36Computing the meanMean g - One linerIn []: g_mean = mean(g_list)In []: print ’Mean: ’, g_mean10 mFOSSEE (IIT Bombay) Statistics 7 / 36Processing voluminous dataOutline1 Computing the mean2 Processing voluminous ...

Sujets

• Python
• Tutoriel
• Calcul (mathématiques)

Informations

• Publié par: mtoledan
• Publié le: 27 juin 2011
• Nombre de lectures: 195
• Langue: English

Extrait

OFSSE

Python for Science and Engg: Basic data processing

EI(ITBom

FOSSEE

Department of Aerospace Engineering IIT Bombay

SciPy 2010, Introductory tutorials, Day 1, Session 3

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Computing the mean Acceleration due to gravity -g. . . In []: g_ ist = [] l In []:forlineinopen(’txpe’.tumulnd): .... point = line.split() .... L = float(point[0]) .... t = float(point[1]) .... g = 4  *  pi * pi * L / (t * t) .... g_list.append(g) FOSSEE (IIT Bombay) Statistics 4 / 36

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We have a huge data file–180,000 records. How do we doteneciffistatistical computations, i.e. find mean, median, standard deviation etc.; How do we draw pie charts?

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Understanding the structure of.tc1xtsls Each line in the file has a student’s details(record) Each record consists of fields separated by ’;’

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Each record consists of: Region Code Roll Number Name Marks of 5 subjects: second lang, first lang., Math, Science, Social Studies Total marks Pass/Fail (P/F) Withheld (W)

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