Difference between revisions of "Python-3.4.3/C2/Statistics/English"

Objectives

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

System Specifications

• Ubuntu Linux 16.04 operating system
• Python 3.4.3 and
• IPython 5.1.0

Pre-requisites

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

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

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

open and Show the file student_record.txt

1:08 - text box

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

Please download it in Home directory and use it.

Show the file student_record.txt

For this, we need to install Numpy.

slide:

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

NumPy has to be installed separately.

type sudo apt-get install python3-pip

pip command is used to install python libraries.

Type, sudo apt-get install python3 hyphen pip and press Enter.

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

type

sudo pip3 install numpy==1.13.3

Type, sudo pip3 install numpy is equal to is equal to 1.13.3 and press Enter.

We can see the terminal prompt without any error.

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

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

Now, type ipython3 and press Enter.

Type

import numpy as np

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

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

Type L and 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.

Type L and press enter

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.

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

Type L.shape

We can get the shape of this array using shape.

4:45

Highlight (185667, 5)

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

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

Type

L[0]

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

Type

totalmarks=sum(L[0])

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

Press Enter.

Highlight 177.0

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

Type

totalmarks/len(L[0])

Highlight 35.399999999999999

Type, totalmarks divided by len inside parentheses L inside square brackets 0 and press Enter.

Type

np.mean(L[0])

Type np dot mean inside parentheses L inside square brackets 0 and press Enter.

Type

np.mean?

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

Is there a way to reduce the work?

For this we will look into the documentation of mean.

Type, np dot mean questionmark and press Enter.

Read the text for more information.

Two-Dimensional array

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.

Type

np.mean(L,0)

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

Type np dot mean inside parentheses L comma 0 and press Enter.

Type

L[:,0]

Highlight output array([ 53., 58., 72., ..., 49., 33., 17.])

Type L inside square brackets colon comma 0 and press Enter.

Note colon comma zero displays first column in the array i.e (that is) English Mark.

Type

np.median(L[:,0])

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

Press Enter.

Type

np.median(L,0)

Type np dot median inside parentheses L comma 0

Press Enter.

Type

np.std(L[:,0])

Standard deviation for English subject can be found by typing np dot std inside parentheses L inside square brackets colon comma 0

Press Enter.

np.std(L,0)

Exercise 1

Download and save the file in the present working directory.

Currently the present working directory is the Home directory.

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

Exercise 1

1. Mean of home and goals away
2. Standard deviation of home and goals away

Type

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

sum(L,1)

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 and press enter.

Type np.mean(L,0)

Type np.std(L,0)

Summary

In this tutorial, we have learnt to, do the standard statistical operations like:

sum

mean

median and

standard deviation in Python.

Assignment

1. Given a two dimensional list as shown. How do you calculate the mean of each row
2. Calculate the median of the given list?

Assignment

1. 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?

Solution

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

Fossee Forum

Acknowledgment http://spoken-tutorial.org

For more details, visit this website.

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