Python plot sin, cos and tan, using pylab and numpy

import pylab as pl
import numpy as np

X = np.linspace(0, 2*np.pi, 360, endpoint=True)
Y = np.sin(X)
Y2 = np.cos(X)
pl.plot(X, Y)
pl.plot(X, Y2)

pl.show()

numpy and matplotlib are needed in this example.

Install for Python 2:
$ sudo apt-get install python-numpy
$ sudo apt-get install python-matplotlib

Install for Python 3:
$ sudo apt-get install python3-numpy
$ sudo apt-get install python3-matplotlib

Python Tools for Visual Studio

Turn Visual Studio into a powerful Python development environment with Python Tools for Visual Studio.

Python Tools for Visual Studio - free, open-source extension adds all the functionality needed to develop and maintain Python applications in Visual Studio, and deploy to Windows or Linux servers, or to Microsoft Azure.

You can install Python Tools for Visual Studio 2.1 into these versions:

• Visual Studio 2013
• Visual Studio Community 2013
• Visual Studio Express 2013 for Web or for Windows Desktop
• Visual Studio 2012 and 2010

Know more: http://www.visualstudio.com/en-us/explore/python-vs.aspx

This video will help you get up and running with Python in Visual Studio. We will cover installation of PTVS, a Python interpreter, and creating and deploying a project to Azure Websites.

Virtualenv, create isolated Python environments with

virtualenv is a tool to create isolated Python environments.

The basic problem being addressed is one of dependencies and versions, and indirectly permissions. Imagine you have an application that needs version 1 of LibFoo, but another application requires version 2. How can you use both these applications? If you install everything into /usr/lib/python2.7/site-packages (or whatever your platform’s standard location is), it’s easy to end up in a situation where you unintentionally upgrade an application that shouldn’t be upgraded.

Or more generally, what if you want to install an application and leave it be? If an application works, any change in its libraries or the versions of those libraries can break the application.

Also, what if you can’t install packages into the global site-packages directory? For instance, on a shared host.

In all these cases, virtualenv can help you. It creates an environment that has its own installation directories, that doesn’t share libraries with other virtualenv environments (and optionally doesn’t access the globally installed libraries either).

To install globally with pip (if you have pip 1.3 or greater installed globally):

$ [sudo] pip install virtualenv


Visit: http://virtualenv.pypa.io/

Open browser in Python, with webbrowser

import webbrowser

webbrowser.open("https://docs.python.org/3/library/webbrowser.html")

dictionary vs tuple

One of the main differency between dictionary and tuple is 'tuple' indices must be integers and 'tuple' object does not support item assignment.

dictionary = {"day0": "sday", "day1": "Monday"}
print(dictionary["day0"])
dictionary["day0"] = "Sunday"
print(dictionary["day0"])

#tuple indices must be integers
tuple = ("sday", "Monday")
print(tuple[0])
#'tuple' object does not support item assignment
#tuple[0] = "Sunday"

Python Data Visualization Cookbook

Python Data Visualization Cookbook - Over 60 recipes that will enable you to learn how to create attractive visualizations using Python's most popular libraries

Overview

• Learn how to set up an optimal Python environment for data visualization
• Understand the topics such as importing data for visualization and formatting data for visualization
• Understand the underlying data and how to use the right visualizations

In Detail

Today, data visualization is a hot topic as a direct result of the vast amount of data created every second. Transforming that data into information is a complex task for data visualization professionals, who, at the same time, try to understand the data and objectively transfer that understanding to others. This book is a set of practical recipes that strive to help the reader get a firm grasp of the area of data visualization using Python and its popular visualization and data libraries.

Python Data Visualization Cookbook will progress the reader from the point of installing and setting up a Python environment for data manipulation and visualization all the way to 3D animations using Python libraries. Readers will benefit from over 60 precise and reproducible recipes that guide the reader towards a better understanding of data concepts and the building blocks for subsequent and sometimes more advanced concepts.

Python Data Visualization Cookbook starts by showing you how to set up matplotlib and the related libraries that are required for most parts of the book, before moving on to discuss some of the lesser-used diagrams and charts such as Gantt Charts or Sankey diagrams. During the book, we go from simple plots and charts to more advanced ones, thoroughly explaining why we used them and how not to use them. As we go through the book, we will also discuss 3D diagrams. We will peep into animations just to show you what it takes to go into that area. Maps are irreplaceable for displaying geo-spatial data, so we also show you how to build them. In the last chapter, we show you how to incorporate matplotlib into different environments, such as a writing system, LaTeX, or how to create Gantt charts using Python.

This book will help those who already know how to program in Python to explore a new field – one of data visualization. As this book is all about recipes that explain how to do something, code samples are abundant, and they are followed by visual diagrams and charts to help you understand the logic and compare your own results with what is explained in the book.

What you will learn from this book

• Install and use iPython
• Use Python's virtual environments
• Install and customize NumPy and matplotlib
• Draw common and advanced plots
• Visualize data using maps
• Create 3D animated data visualizations
• Import data from various formats
• Export data from various formats

Approach

This book is written in a Cookbook style targeted towards an advanced audience. It covers the advanced topics of data visualization in Python.

Print list of int, and String

This example print list of int, and String:

Print list of int, and String

#generate random 5 number
import random

list=[]     #init a empty list

for x in range(0, 5):
    random_number = random.randint(0, 10)
    print(random_number)
    list.append(random_number)  #append random number to list
    
#print all elements
print('[%s]' % ', '.join(map(str, list)))

strList = ['abc', 'def', 'ghi', 'jkl']
#join strings in list, with ', ' in between each element.
print(', '.join(strList));