This document provides an introduction to using lists in Python. It defines what lists are in Python, how to create, access, update, and delete list elements, and some common list operations. It also provides examples of creating lists, accessing values at different indices, updating and deleting elements, and using basic operators like addition and multiplication. Finally, it proposes three exercises involving lists to practice these concepts.
Slides for Lecture 3 of the course: Introduction to Programming with Python offered at ICCBS.
It covers the following topics:
Strings useful string operations.
Slides for Lecture 3 of the course: Introduction to Programming with Python offered at ICCBS.
It covers the following topics:
Strings useful string operations.
In this PPT you learn some basic terminology and basic concept of Python which is a pillar of python programming.So learn Python programming by these PPT.
You get a new presentation every Sunday at 10 AM.
general use of pointer
what is pointer in c language
uses is pointer in c language
representation of pointer in c language
syantax of pointer in c language
program of pointer in c language
Database structure Structures Link list and trees and Recurison complete Adnan abid
Database structure Structures Link list and trees and Recurison complete Database structure Structures Link list and trees and Recurison complete Database structure Structures Link list and trees and Recurison complete Database structure Structures Link list and trees and Recurison complete Database structure Structures Link list and trees and Recurison complete
Database structure Structures Link list and trees and Recurison complete Database structure Structures Link list and trees and Recurison complete Database structure Structures Link list and trees and Recurison complete
A brief overview of using HDF5 with Python and Andrew Collette's h5py module will be presented, including examples which show how and why Python can be used in the place of HDF5 tools. Extensions to the HDF5 API will be proposed which would further improve the utility of Python/h5py.
Slides for Lecture 1 of the course: Introduction to Programming with Python offered at ICCBS.
It covers the following topics:
1.) Variables, Statements and Expressions
2.) Functions
3.) Flow Control
From a talk by Andrew Collette to the Boulder Earth and Space Science Informatics Group (BESSIG) on November 20, 2013.
This talk explores how researchers can use the scalable, self-describing HDF5 data format together with the Python programming language to improve the analysis pipeline, easily archive and share large datasets, and improve confidence in scientific results. The discussion will focus on real-world applications of HDF5 in experimental physics at two multimillion-dollar research facilities: the Large Plasma Device at UCLA, and the NASA-funded hypervelocity dust accelerator at CU Boulder. This event coincides with the launch of a new O’Reilly book, Python and HDF5: Unlocking Scientific Data.
As scientific datasets grow from gigabytes to terabytes and beyond, the use of standard formats for data storage and communication becomes critical. HDF5, the most recent version of the Hierarchical Data Format originally developed at the National Center for Supercomputing Applications (NCSA), has rapidly emerged as the mechanism of choice for storing and sharing large datasets. At the same time, many researchers who routinely deal with large numerical datasets have been drawn to the Python by its ease of use and rapid development capabilities.
Over the past several years, Python has emerged as a credible alternative to scientific analysis environments like IDL or MATLAB. In addition to stable core packages for handling numerical arrays, analysis, and plotting, the Python ecosystem provides a huge selection of more specialized software, reducing the amount of work necessary to write scientific code while also increasing the quality of results. Python’s excellent support for standard data formats allows scientists to interact seamlessly with colleagues using other platforms.
In this PPT you learn some basic terminology and basic concept of Python which is a pillar of python programming.So learn Python programming by these PPT.
You get a new presentation every Sunday at 10 AM.
general use of pointer
what is pointer in c language
uses is pointer in c language
representation of pointer in c language
syantax of pointer in c language
program of pointer in c language
Database structure Structures Link list and trees and Recurison complete Adnan abid
Database structure Structures Link list and trees and Recurison complete Database structure Structures Link list and trees and Recurison complete Database structure Structures Link list and trees and Recurison complete Database structure Structures Link list and trees and Recurison complete Database structure Structures Link list and trees and Recurison complete
Database structure Structures Link list and trees and Recurison complete Database structure Structures Link list and trees and Recurison complete Database structure Structures Link list and trees and Recurison complete
A brief overview of using HDF5 with Python and Andrew Collette's h5py module will be presented, including examples which show how and why Python can be used in the place of HDF5 tools. Extensions to the HDF5 API will be proposed which would further improve the utility of Python/h5py.
Slides for Lecture 1 of the course: Introduction to Programming with Python offered at ICCBS.
It covers the following topics:
1.) Variables, Statements and Expressions
2.) Functions
3.) Flow Control
From a talk by Andrew Collette to the Boulder Earth and Space Science Informatics Group (BESSIG) on November 20, 2013.
This talk explores how researchers can use the scalable, self-describing HDF5 data format together with the Python programming language to improve the analysis pipeline, easily archive and share large datasets, and improve confidence in scientific results. The discussion will focus on real-world applications of HDF5 in experimental physics at two multimillion-dollar research facilities: the Large Plasma Device at UCLA, and the NASA-funded hypervelocity dust accelerator at CU Boulder. This event coincides with the launch of a new O’Reilly book, Python and HDF5: Unlocking Scientific Data.
As scientific datasets grow from gigabytes to terabytes and beyond, the use of standard formats for data storage and communication becomes critical. HDF5, the most recent version of the Hierarchical Data Format originally developed at the National Center for Supercomputing Applications (NCSA), has rapidly emerged as the mechanism of choice for storing and sharing large datasets. At the same time, many researchers who routinely deal with large numerical datasets have been drawn to the Python by its ease of use and rapid development capabilities.
Over the past several years, Python has emerged as a credible alternative to scientific analysis environments like IDL or MATLAB. In addition to stable core packages for handling numerical arrays, analysis, and plotting, the Python ecosystem provides a huge selection of more specialized software, reducing the amount of work necessary to write scientific code while also increasing the quality of results. Python’s excellent support for standard data formats allows scientists to interact seamlessly with colleagues using other platforms.
Slides for Lecture 5 of the course: Introduction to Programming with Python offered at ICCBS.
It covers the following topics:
1.)Python Modules
2.)File I/O
3.)Exceptions & Error Handling
An introduction to the Python programming language and its numerical abilities will be presented. With this background, Andrew Collette's H5Py module--an HDF5-Python interface--will be explained highlighting the unique and useful similarities between Python data structures and HDF5.
This tutorial is designed for anyone who needs to work with data stored in HDF5 files. The tutorial will cover functionality and useful features of the HDF5 utilities h5dump, h5diff, h5repack, h5stat, h5copy, h5check and h5repart. We will also introduce a prototype of the new h52jpeg conversion tool and recently released h5perf_serial tool used for performance studies. We will briefly introduce HDFView. Details of the HDFView and HDF-Java will be discussed in a separate tutorial.
Learn about how to use the Python language and its constructs in different situations. With classification of scenarios done already you can use this material as a reference guide too.
Learn the language and its idioms by trying out the sample code or by looking at code snippet.
This presentation was created for Next Craft JMP Student Program to help students jump start with Python programming.
Python is a widely used high-level programming language for general-purpose programming. Python is a simple, powerful and easy to learn the programming language. It is commonly used for Web and Internet development, Scientific and Numeric computing, Business application and Desktop GUI development etc. The basic data structures in python are lists, dictionaries, tuples, strings and sets
• List is a collection, which is ordered and changeable. Allows duplicate members.
• Tuple is a collection, which is ordered and unchangeable. Allows duplicate members.
• Set is a collection, which is unordered and unindexed. No duplicate members.
• Dictionary is a collection, which is unordered, changeable and indexed. No duplicate members.
My Statement of Accomplishment for Introduction to Systematic Program Design - Part 1 by The University of British Columbia and offered through Coursera.
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How Recreation Management Software Can Streamline Your Operations.pptxwottaspaceseo
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Enterprise Resource Planning System includes various modules that reduce any business's workload. Additionally, it organizes the workflows, which drives towards enhancing productivity. Here are a detailed explanation of the ERP modules. Going through the points will help you understand how the software is changing the work dynamics.
To know more details here: https://blogs.nyggs.com/nyggs/enterprise-resource-planning-erp-system-modules/
Check out the webinar slides to learn more about how XfilesPro transforms Salesforce document management by leveraging its world-class applications. For more details, please connect with sales@xfilespro.com
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4. Lists
The most basic data structure in Python is the sequence.
Each element of a sequence is assigned a number - its
position or index. The first index is zero, the second index
is one, and so forth.
Python has six built-in types of sequences, but the most
common ones are lists and tuples, which we would see
in this tutorial.
There are certain things you can do with all sequence
types. These operations include indexing, slicing, adding,
multiplying, and checking for membership. In addition,
Python has built-in functions for finding the length of a
sequence and for finding its largest and smallest
elements.
5. Creating Lists
Creating a list is as simple as putting different comma-separated
values between squere brackets. For example:
list1 = ['physics', 'chemistry', 1997, 2000];
list2 = [1, 2, 3, 4, 5 ];
list3 = ["a", "b", "c", "d"];
6. Accessing Values in Lists:
To access values in lists, use the square brackets for slicing along
with the index or indices to obtain value available at that index.
Following is a simple example:
list1 = ['physics', 'chemistry', 1997, 2000];
list2 = [1, 2, 3, 4, 5, 6, 7 ];
print "list1[0]: ", list1[0]
print "list2[1:5]: ", list2[1:5]
7. Updating Lists
You can update single or multiple elements of lists by giving the slice
on the left-hand side of the assignment operator, and you can add
to elements in a list with the append() method. Following is a simple
example:
list = ['physics', 'chemistry', 1997, 2000];
print "Value available at index 2 : "
print list[2];
list[2] = 2001;
print "New value available at index 2 : "
print list[2];
8. Delete Lists Elements
To remove a list element, you can use either the del statement if you
know exactly which element(s) you are deleting or the remove()
method if you do not know. Following is a simple example:
list1 = ['physics', 'chemistry', 1997, 2000];
print list1;
del list1[2];
print "After deleting value at index 2 : "
print list1;
9. Basic List Operations
Lists respond to the + and * operators much like strings; they mean
concatenation and repetition here too, except that the result is a
new list, not a string.
In fact, lists respond to all of the general sequence operations we
used on strings in the prior chapter.
11. Exercise 0
Create a program that will keep track of items for a shopping list.
The program should keep asking for new items until nothing is
entered (no input followed by enter/return key). The program should
then display the full shopping list.
12. Exercise 1
Given an array of ints, return True if 6 appears as either the first or last
element in the array. The array will be length 1 or more.
first_last6([1, 2, 6]) → True
first_last6([6, 1, 2, 3]) → True
first_last6([13, 6, 1, 2, 3]) → False
13. Exercise 2
Given an array of ints, return True if the array is length 1 or more, and
the first element and the last element are equal.
same_first_last([1, 2, 3]) → False
same_first_last([1, 2, 3, 1]) → True
same_first_last([1, 2, 1]) → True
14. Exercise 3
Return the number of even ints in the given array. Note: the % "mod"
operator computes the remainder, e.g. 5 % 2 is 1.
count_evens([2, 1, 2, 3, 4]) → 3
count_evens([2, 2, 0]) → 3
count_evens([1, 3, 5]) → 0
15. Any Queries?
Link to Facebook Group:
https://www.facebook.com/groups/introtopython.iccbs/
Email:
farjad_bullet@rocketmail.com