Python Programming Unit 4 Problem Solving and Data Analysis

PROGRAMMING IN PYTHON
MCA-161
4 Credits (3-0-2)
MCA 5th Sem (2020-21)
R K Dwivedi
Assistant Professor
Department of ITCA
MMMUT Gorakhpur

UNIT IV: Advance Concepts
A. Problem solving:
• Use of Python to solve real time problems
• How Python helps to research problems
• Creating various types of graphs corresponding to any data to show different kinds of results and analysis
B. Data Analysis:
• Understanding problems of data science and machine learning
• Creating codes for data analysis problems in Python
• Other advance programs

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Madan Mohan Malaviya Univ. of Technology, Gorakhpur
A. Problem solving

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1. Use of Python to solve real time problems

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1. Use of Python to solve real time problems
• Python can be used on a server to create web applications.
• It can be used to create GUI based desktop applications(Games, Scientific and Business Applications).
• It is also used to create test frameworks and multimedia applications.
• It is used to develop operating systems and programming language.
• It can be used to handle image processing, text processing and natural language processing.
• It can be used to create programs for machine learning, deep learning, data science, big data and data analytics applications.
• It can also perform complex mathematics along with all cutting edge technology in software industry.
Organizations and tech-giant companies using Python :
1) Google(Components of Google spider and Search Engine)
2) Yahoo(Maps)
3) YouTube
4) Mozilla
5) Dropbox
6) Microsoft
7) Cisco
8) Spotify
9) Quora
10) Instagram
11)Amazon
12)Facebook
13)Uber etc.

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1. Use of Python to solve real time problems …continued
Some Real Time Projects, their Python Codes and Datasets :
https://data-flair.training/blogs/python-project-ideas/
https://data-flair.training/blogs/django-project-ideas/
https://data-flair.training/blogs/data-science-project-ideas/
https://data-flair.training/blogs/artificial-intelligence-project-ideas/
https://data-flair.training/blogs/machine-learning-project-ideas/
https://data-flair.training/blogs/deep-learning-project-ideas/
https://data-flair.training/blogs/iot-project-ideas/
https://data-flair.training/blogs/computer-vision-project-ideas/
https://archive.ics.uci.edu/ml/datasets.php
https://www.kaggle.com/datasets
https://github.com/topics/covid-19

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2. How Python helps to research problems

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2. How Python helps to research problems
It can be used in various types of research areas such as:
• Image Processing
• Text Processing
• Natural Language Processing
• Machine Learning
• Deep Learning
• Data Science
• Big Data Analytics

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3. Creating various types of graphs corresponding to any data
(to show different kinds of results and analysis)

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1. Creating various types of graphs corresponding to any data (to show different kinds of results and analysis)
• Matplotlib is a graph plotting library in python that serves as a visualization utility.
• NumPy (Numerical Python) is a python library used for working with arrays.
• NumPy also has functions for working in the domain of linear algebra, fourier transform, and matrices.
• subplot( ) allows to draw multiple plots in one fig. (subplot(no of rows, no of columns, index of current plot)
• All modern browsers support 140 color names (Syntax: color=‘r’ or color=‘red’ or c=‘r’ or c=‘red’).
• A hexadecimal color is specified with: #RRGGBB (Syntax: color=‘#0000ff’ or c=‘0000ff’).
A. Line Graph:
• linestyle can be written as ls in a shorter syntax.
• linewidth can be written as lw in a shorter syntax.
• color can be written as c in a shorter syntax.
linestyle short syntax
solid' (default) '-'
'dotted' ':'
'dashed' '--'
'dashdot' '-.'
'None' '' or ' '
'r' - Red
'g' - Green
'b' - Blue
'c' - Cyan
'm' - Magenta
'y' - Yellow
'k' - Black
'w' - White

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…continued

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…continued
B. Bar Graph:
• The default width value of the bars is 0.8.
• bar ( ) function displays the bar graph vertically and barh( ) function displays the bar graph horizontally.

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…continued

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…continued
C. Pie Chart:
• By default the plotting of the first wedge starts from the x-axis and move counterclockwise.
• pie( ) function is used to draw the pie charts.
• pie(populationShare, labelsWedge, colors, startAngle, explode, shadow)
• legend(title = "Four Fruits:", loc='lower right')
Location String Location Code
'best' 0
'upper right' 1
'upper left' 2
'lower left' 3
'lower right' 4
'right' 5
'center left' 6
'center right' 7
'lower center' 8
'upper center' 9
'center' 10

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…continued

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…continued

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…continued
D. Histogram:
• A histogram is a graph showing frequency distributions.
• It is a graph showing the number of observations within each given interval.
• hist() function to create histograms.
• Create a histogram to represent following:
❖ 2 people from 140 to 145cm
• For this, function numpy.random.normal(170, 10, 250) can be used which shows that NumPy uses Normal
Distribution to randomly generate an array with 250 values, where the values will concentrate around 170,
and the standard deviation is 10.

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…continued

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B. Data Analysis

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1. Understanding problems of data science and machine learning

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1. Understanding problems of data science and machine learning
A. Introduction:

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1. Understanding problems of data science and machine learning …continued
B. Procedure:

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C. Applications:

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A. Introduction:

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B. Relation among AI, ML, NN, and DL:

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C. Types of ML:
•Supervised Learning – Train Me!
•Unsupervised Learning – I am self sufficient in learning
•Reinforcement Learning – My life My rules! (Hit & Trial)

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D. Techniques used in ML:

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E. Procedure (View 1)
Usually 80% data for training, and 20% data for testing

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F. Applications (View 1):

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2. Creating codes for data analysis problems in Python

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2. Creating codes for data analysis problems in Python
First of all, import or load the dataset and then analyse it.
A. The basic process of loading data from a CSV file with Pandas
# Load the Pandas libraries with alias 'pd'
import pandas as pd
# Read data from file 'filename.csv' (in the same directory)
data = pd.read_csv("filename.csv")
# Preview the first 5 lines of the loaded data
data.head()
import pandas
filename = ‘indians-diabetes.data.csv'
names = ['preg', 'plas', 'pres', 'skin', 'test', 'mass', 'pedi', 'age', 'class']
data = pandas.read_csv(filename, names=names)
print(data.shape)
OR

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2. Creating codes for data analysis problems in Python …continued
C. The basic process of loading data from a CSV file with Python Standard Library
B. The basic process of loading data from a CSV file with NumPy
import numpy
filename = 'indians-diabetes.data.csv'
raw_data = open(filename, 'rt')
data = numpy.loadtxt(raw_data, delimiter=",")
print(data.shape)
import csv
import numpy
filename = 'indians-diabetes.data.csv'
raw_data = open(filename, 'rt')
reader = csv.reader(raw_data, delimiter=‘,’ , quoting=csv.QUOTE_NONE)
x = list(reader)
data = numpy.array(x).astype('float')
print(data.shape)

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2. Creating codes for data analysis problems in Python …continued
D. Data Analysis

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3. Other advance programs

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3. Other advance programs: Calendar (I)

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3. Other advance programs : Calendar (II) …continued

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3. Other advance programs: Calculator …continued
https://data-flair.s3.ap-south-1.amazonaws.com/python-projects/dataflair-python-calculator.zip

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3. Other advance programs: Currency Converter …continued
https://data-flair.s3.ap-south-1.amazonaws.com/python-projects/currency-converter-project.zip

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3. Other advance programs: Music Player …continued
https://project-gurukul.s3.ap-south-1.amazonaws.com/python-projects/music-player-python.zip

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3. Other advance programs: Alarm Clock …continued
https://data-flair.s3.ap-south-1.amazonaws.com/python-projects/DataFlair-Alarm-Clock.zip

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