The document discusses installing Python 3 on Ubuntu and Windows systems. It provides step-by-step instructions for installing Python 3.8 using apt on Ubuntu and downloading/running the installer on Windows. Basic Python data visualization techniques like line plots, bar charts, histograms, box plots, and scatter plots are then introduced using the Matplotlib library. Code examples are given for creating each type of plot.
This slide includes: Control Flow and Functions.
That is Boolean values and operators.
It include Iteration,Fruitful functions,Scope of Variable and Modules.
In this PPT you will learn how to use looping in python.
For more presentation in any subject please contact us on
raginijain0208@gmail.com.
You get a new presentation every Sunday at 10 AM.
Learn more about Python by clicking on given below link
Python Introduction- https://www.slideshare.net/RaginiJain21/final-presentation-on-python
Basic concept of Python -https://www.slideshare.net/RaginiJain21/python-second-ppt
Python Datatypes - https://www.slideshare.net/RaginiJain21/data-types-in-python-248466302
Python Library & Module - https://www.slideshare.net/RaginiJain21/python-libraries-and-modules
Basic Python Programs- https://www.slideshare.net/RaginiJain21/basic-python-programs
Python Media Libarary - https://www.slideshare.net/RaginiJain21/python-media-library
Machine Learning With Python From India’s Most Advanced Learner’s Community. 200+ High-Quality Lectures. 4 Months Live Mentor-ship. 15+ Projects. Industry Insights.
Visit- https://insideaiml.com/course-details/Machine-Learning-with-Python-Statistics
In this chapter we are going to get familiar with recursion and its applications. Recursion represents a powerful programming technique in which a method makes a call to itself from within its own method body. By means of recursion we can solve complicated combinatorial problems, in which we can easily exhaust different combinatorial configurations, e.g. generating permutations and variations and simulating nested loops. We are going to demonstrate many examples of correct and incorrect usage of recursion and convince you how useful it can be.
This slide includes: Control Flow and Functions.
That is Boolean values and operators.
It include Iteration,Fruitful functions,Scope of Variable and Modules.
In this PPT you will learn how to use looping in python.
For more presentation in any subject please contact us on
raginijain0208@gmail.com.
You get a new presentation every Sunday at 10 AM.
Learn more about Python by clicking on given below link
Python Introduction- https://www.slideshare.net/RaginiJain21/final-presentation-on-python
Basic concept of Python -https://www.slideshare.net/RaginiJain21/python-second-ppt
Python Datatypes - https://www.slideshare.net/RaginiJain21/data-types-in-python-248466302
Python Library & Module - https://www.slideshare.net/RaginiJain21/python-libraries-and-modules
Basic Python Programs- https://www.slideshare.net/RaginiJain21/basic-python-programs
Python Media Libarary - https://www.slideshare.net/RaginiJain21/python-media-library
Machine Learning With Python From India’s Most Advanced Learner’s Community. 200+ High-Quality Lectures. 4 Months Live Mentor-ship. 15+ Projects. Industry Insights.
Visit- https://insideaiml.com/course-details/Machine-Learning-with-Python-Statistics
In this chapter we are going to get familiar with recursion and its applications. Recursion represents a powerful programming technique in which a method makes a call to itself from within its own method body. By means of recursion we can solve complicated combinatorial problems, in which we can easily exhaust different combinatorial configurations, e.g. generating permutations and variations and simulating nested loops. We are going to demonstrate many examples of correct and incorrect usage of recursion and convince you how useful it can be.
Dev Concepts: Data Structures and AlgorithmsSvetlin Nakov
Brief overview of the "data structures" and "algorithms" concepts.
Watch the video lesson from Svetlin Nakov and learn more at: https://softuni.org/dev-concepts/what-are-data-structures-and-algorithms
In this chapter we are going to get familiar with some of the basic presentations of data in programming: lists and linear data structures. Very often in order to solve a given problem we need to work with a sequence of elements. For example, to read completely this book we have to read sequentially each page, i.e. to traverse sequentially each of the elements of the set of the pages in the book. Depending on the task, we have to apply different operations on this set of data. In this chapter we will introduce the concept of abstract data types (ADT) and will explain how a certain ADT can have multiple different implementations. After that we shall explore how and when to use lists and their implementations (linked list, doubly-linked list and array-list). We are going to see how for a given task one structure may be more convenient than another. We are going to consider the structures "stack" and "queue", as well as their applications. We are going to get familiar with some implementations of these structures.
What is Data Type?
Primitive Types in C#: Integer Types, Floating-Point Types, Decimal Type, Boolean Type, Character Types, Strings, Objects
Value Types and Reference Types
Variables. Using Variables: Declaring, Initializing, Assigning Value, Accessing Value
Literals: The Values of the Variables in the Source Code. Boolean Literals. Integer Literals. Floating-Point Literals, Decimal Literals, String Literals and Escaping Sequences
Exercises: Working with Primitive Types and Variables
Array
Introduction
One-dimensional array
Multidimensional array
Advantage of Array
Write a C program using arrays that produces the multiplication of two matrices.
Algorithm to convert postfix expression into an expression tree. We already have an expression to convert an infix expression to postfix. Read a symbol from the postfix expression. If symbol is an operand, put it in a one node tree and push it on a stack
Chapter 22. Lambda Expressions and LINQIntro C# Book
In this chapter we will become acquainted with some of the advanced capabilities of the C# language. To be more specific, we will pay attention on how to make queries to collections, using lambda expressions and LINQ, and how to add functionality to already created classes, using extension methods. We will get to know the anonymous types, describe their usage briefly and discuss lambda expressions and show in practice how most of the built-in lambda functions work. Afterwards, we will pay more attention to the LINQ syntax – we will learn what it is, how it works and what queries we can build with it. In the end, we will get to know the meaning of the keywords in LINQ, and demonstrate their capabilities with lots of examples.
This project is based on Library Management. Python and MySQL are the programming platforms which are used in making of this project.
Subject-Informatics Practices
Class-11/12
This slide is used to do an introduction for the matplotlib library and this will be a very basic introduction. As matplotlib is a very used and famous library for machine learning this will be very helpful to teach a student with no coding background and they can start the plotting of maps from the ending of the slide by there own.
Dev Concepts: Data Structures and AlgorithmsSvetlin Nakov
Brief overview of the "data structures" and "algorithms" concepts.
Watch the video lesson from Svetlin Nakov and learn more at: https://softuni.org/dev-concepts/what-are-data-structures-and-algorithms
In this chapter we are going to get familiar with some of the basic presentations of data in programming: lists and linear data structures. Very often in order to solve a given problem we need to work with a sequence of elements. For example, to read completely this book we have to read sequentially each page, i.e. to traverse sequentially each of the elements of the set of the pages in the book. Depending on the task, we have to apply different operations on this set of data. In this chapter we will introduce the concept of abstract data types (ADT) and will explain how a certain ADT can have multiple different implementations. After that we shall explore how and when to use lists and their implementations (linked list, doubly-linked list and array-list). We are going to see how for a given task one structure may be more convenient than another. We are going to consider the structures "stack" and "queue", as well as their applications. We are going to get familiar with some implementations of these structures.
What is Data Type?
Primitive Types in C#: Integer Types, Floating-Point Types, Decimal Type, Boolean Type, Character Types, Strings, Objects
Value Types and Reference Types
Variables. Using Variables: Declaring, Initializing, Assigning Value, Accessing Value
Literals: The Values of the Variables in the Source Code. Boolean Literals. Integer Literals. Floating-Point Literals, Decimal Literals, String Literals and Escaping Sequences
Exercises: Working with Primitive Types and Variables
Array
Introduction
One-dimensional array
Multidimensional array
Advantage of Array
Write a C program using arrays that produces the multiplication of two matrices.
Algorithm to convert postfix expression into an expression tree. We already have an expression to convert an infix expression to postfix. Read a symbol from the postfix expression. If symbol is an operand, put it in a one node tree and push it on a stack
Chapter 22. Lambda Expressions and LINQIntro C# Book
In this chapter we will become acquainted with some of the advanced capabilities of the C# language. To be more specific, we will pay attention on how to make queries to collections, using lambda expressions and LINQ, and how to add functionality to already created classes, using extension methods. We will get to know the anonymous types, describe their usage briefly and discuss lambda expressions and show in practice how most of the built-in lambda functions work. Afterwards, we will pay more attention to the LINQ syntax – we will learn what it is, how it works and what queries we can build with it. In the end, we will get to know the meaning of the keywords in LINQ, and demonstrate their capabilities with lots of examples.
This project is based on Library Management. Python and MySQL are the programming platforms which are used in making of this project.
Subject-Informatics Practices
Class-11/12
This slide is used to do an introduction for the matplotlib library and this will be a very basic introduction. As matplotlib is a very used and famous library for machine learning this will be very helpful to teach a student with no coding background and they can start the plotting of maps from the ending of the slide by there own.
The Role of Histograms in Exploring Data InsightsCIToolkit
A graph which shows the frequency of continuous data values. Histograms are mainly used to explore data as well as to present the data in an easy and understandable manner. They are often used as the first step to determine the underlying probability distribution of a data set or a sample.
Python for Data Science is a must learn for professionals in the Data Analytics domain. With the growth in IT industry, there is a booming demand for skilled Data Scientists and Python has evolved as the most preferred programming language. Through this blog, you will learn the basics, how to analyze data and then create some beautiful visualizations using Python.
Graph Tea: Simulating Tool for Graph Theory & AlgorithmsIJMTST Journal
Simulation in teaching has recently entered the field of education. It is used at different levels of instruction.
The teacher is trained practically and also imparted theoretical learning. In Computer Science, Graph theory
is the fundamental mathematics required for better understanding Data Structures. To Teach Graph theory &
Algorithms, We introduced Simulation as an innovative teaching methodology. Students can understand in a
better manner by using simulation. Graph Tea is one of such simulation tool for Graph Theory & Algorithms.
In this paper, we simulated Tree Traversal Techniques like Breadth First Search (BFS), Depth First Search
(DFS) and minimal cost spanning tree algorithms like Prims.
Best Data Science Ppt using Python
Data science is an inter-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from many structural and unstructured data. Data science is related to data mining, machine learning and big data.
This slide includes :
Types of Machine Learning
Supervised Learning
Brain
Neuron
Design a Learning System
Perspectives
Issues in Machine Learning
Learning Task
Learning as Search
Hypothesis
Version Spaces
Candidate elimination algorithm
linear Discriminant
Perception
Linear Separability
Linear Regression
Unsupervised Learning
Reinforcement Learning
Evolutionary Learning
GSM-Mobility Management-Call Control
GRPS-Network elements
Radio Resource Management
Mobility Management and Session Management
Small Screen Web Browsing
UTRAN-Core and Radio Network Mobility Management
UMTS Security
This slide includes
Advanced multiplexing
Code Division Multiplexing
Dense Wavelength Division Multiplexing
OFDM
Connectionless
LAN
L3 SWTICH
SLIP
PPP
CORE AND DISTRIBUTION NETWORKS.
Honest Reviews of Tim Han LMA Course Program.pptxtimhan337
Personal development courses are widely available today, with each one promising life-changing outcomes. Tim Han’s Life Mastery Achievers (LMA) Course has drawn a lot of interest. In addition to offering my frank assessment of Success Insider’s LMA Course, this piece examines the course’s effects via a variety of Tim Han LMA course reviews and Success Insider comments.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
Palestine last event orientationfvgnh .pptxRaedMohamed3
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
1. Python for Data Science
(Introduction to Data Visualization)
Dr.M.Rajendiran
Dept. of Computer Science and Engineering
Panimalar Engineering College
2. Install Python 3 On Ubuntu
Prerequisites
Step 1.A system running Ubuntu
Step 2.A user account with sudo privileges
Step 3.Access to a terminal command-line (Ctrl–Alt–T)
Step 4.Make sure your environment is configured to use
Python 3.8
2
3. Install Python 3
Now you can start the installation of Python 3.8.
$sudo apt install python3.8
Allow the process to complete and verify the Python
version was installed successfully
$python ––version
3
4. Installing and using Python on Windows is very simple.
Step 1: Download the Python Installer binaries
Step 2: Run the Executable Installer
Step 3: Add Python to environmental variables
Step 4: Verify the Python Installation
4
5. Python Installation
Open the Python website in your web browser.
https://www.python.org/downloads/windows/
Once the installer is downloaded, run the Python installer.
Add the following path
C:Program FilesPython37-32: for 64-bit installation
Once the installation is over, you will see a Python Setup
Successful window.
You are ready to start developing Python applications in
your Windows 10 system.
5
6. iPython Installation
If you already have Python installed, you can use pip to
install iPython using the following command:
$pip install iPython
To use it, type the following command in your computer’s
terminal:
$ipython
6
7. Data Visualization
A picture is worth a million words.
Data visualization plays an essential role in the representation of
both small and large data.
Data visualization is the graphical representation of data in order to
interactively and efficiently understanding to clients and customers.
Data visualization enable us to extract information, better
understand the data, and make more effective decisions.
One of the key role of data scientist is the ability to tell a compelling
story, visualizing data and findings in an approachable and
motivating way.
8. Data Visualization
With a tiny domain knowledge, data visualizations can be used to
express and demonstrate key relationships in plots and charts.
There are five key basic data visualization.
1. Line Plot
2. Bar Chart
3. Histogram Plot
4. Box and Whisker Plot
5. Scatter Plot
9. Data Visualization
Matplotlib
Matplotlib is one of the most popular python library packages used
for data visualization.
It is numerical mathematics extension NumPy.
It provides an object-oriented programming for embedding plots into
applications.
It uses general-purpose graphic tools like Tkinter, wxpython, etc.,
It can be used in Python and IPython, Jupyterlab and
Jupyternotebook.
10. Data Visualization
We will learn how to create a line plot with matplotlib.
The following example creates a sequence of floating point values
as the x-axis and a sine wave as a function of the x-axis as the
observations on the y-axis.
The outputs are plotted as a line plot.
The pyplot module from matplotlib package is imported with an alias
pyplot.
from matplotlib import pyplot
We need an array of numbers to plot. NumPy library which is
imported with the sin alias.
from numpy import sin
11. Data Visualization
The drawings of line plot can be shown by calling the show()
function.
pyplot.show()
The line plot can be saved to file using savefig() function.
pyplot.savefig('my_image.png')
Line plots are useful for presenting time series data as well as any
order data.
A line plot is used to present observations collected at consistent
intervals.
A line plot can be created by calling the plot() function.
The complete program is as follows:
13. Data Visualization
Bar chart
A bar chart or graph that presents categorical data with rectangular
bars with heights proportional to the values.
The bars can be plotted vertically or horizontally.
A bar graph shows comparisons among distinct categories.
One axis represent categories and other axis represent value.
Matplotlib provides the bar() function that can be used in the python.
Syntax: bar(x, height, width, bottom, align)
x: sequence of scalar
height: The height of the bars
width: The width of the bars
bottom: The coordinates of the bars bases.
align: Alignment of the bars to the x coordinates.
15. Data Visualization
Histograms
A histogram is a graphical illustration that organizes a group of data
points into user-specified ranges.
In a histogram, it is the area of the bar that shows the frequency of
occurrences for each bin.
A Histogram has two axes that is x axis and y axis.
The x axis represent event whose frequency you have to count.
The y axis represent frequency.
The different heights of bar show different frequency of occurrence
of data.
Histograms uses in image processing, brightness, equalize an
image and computer vision.
16. Data Visualization
A histogram plot can be created by calling the hist() function and
passing in a list or array.
pyplot.hist(x)
The following parameters for a histogram:
x : array or sequence of arrays
bins : integer or sequence or optional
Example:
Consider a semester examination result that we have to make a
histogram graph of your results, showing the overall frequency of
occurrence of grade in class.
marks=(45,54,65,56,74,47,87,78,98,89,100,72,58,28,44,49,71,80)
18. Data Visualization
Box and Whisker Plot
A boxplot is generally used to summarize the distribution of a data
sample, also called box and whisker plot
A set of data containing the minimum, first quartile, median, third
quartile, and maximum.
In a box plot, we draw a box from the first quartile to the third
quartile.
Vertical line goes through the box at the median.
The whiskers go from each quartile to the minimum or maximum.
The x-axis is used to represent the data sample and y-axis
represents the observation values.
19. Data Visualization
Example:
We use the numpy.random.normal() function to create the
data for boxplots.
It has three parameters such as mean and standard deviation
and number of values.
Boxplots can be drawn by calling the boxplot() function.
pyplot.boxplot(x)
21. Data Visualization
Scatter Plot
A scatterplot is a graphic tool used to display the relationship
between two quantitative variables.
A scatterplot consists of an X axis, a Y axis and a series of dots.
Scatter plots can be created by calling the scatter() function.
pyplot.scatter(x, y)
Scatter plots are useful for showing the association between two
variables.
The example below creates two data samples such as marks of
boys and girls in two different colours.
23. Conclusion
Python is great as a programming language
It is great for data science.
There are many visualization libraries:
Matplotlib
seaborn
bokesh
holoviews
datashader
folium
yt
email:mrajen@rediffmail.com