This article shows and helps to learn basic python programming language. Initially, learn to write your program in python, then create a Jupyter notebook. Learn how to do simple coding by using pythons Jupyter notebooks. Learners will explore how to use a python variable to store values, and learn to differentiate between variables.
Overview
There are no prequisites for this course. You will begin by installing the Anaconda distribution for python and getting started with simple coding using Jupyter notebooks. You can work with common built-in functions, definind variables and also with strings.
Installing Anaconda on Windows
Download and install the python programming language on your machine. Type in your window, install anaconda on windows. Anaconda is a open source distribution of the python. Open source means that is completely free for any developer. Anaconda distribution also provides the packages called conda. conda is nothing but the package manager. Also Anaconda distribution can also be installed in on any operating system. And simply follow the instructions in order to set up on your machine. Make sure you agree with the license agreement. After following those instructions and setup python using the Anaconda distribution.
Jupyter notebooks on windows for python
Interract with Python using Jupyter notebooks, by opening command prompt on your windows. And go to terminal shell window. create a directory and store your demo files here. Ypu can confirm whether python has been installed successfully on your machine by simply running the command python.Jupyter notebook is nothing but interative shell to code our python code. You can also type your commanc prompt command within your Jupyter notebook.
Variables in python
When you interact with python, you will see that there ae many different ways to assign values to variables. Recognize the first line here a=b=c=World. The statement will be evaluated from right to left, world is assigned to the variable c, the value in variable c is assigned to b. Python will find the commas and assign values accordingly. In python it is possible to assign the a value to a variable using the value in another variable.
Data types
Different types of values, strings, floating points, integers. In python you can always create your own data types using classes. If you pass in a decimal to the type function, the type function will correctly interpret this of type float.
Python also supports for the arithmetic operations on complex numbers. May not use it very often but you should that its possible. If you cant remeber complex numbers from your high school math, you can forgot it. You can work with complex numbers in python, incase you ever have to do so.
Also work with string values before. If you pass in a binary number to the type of function, ypu will see that the binary number is nothing but an integer. A string is a sequence of charecters specified within double quotes or single quoted. We have already seen that string can be multiplies by an integer.
When you hit Shift+Enter and execute the bit of coe, you will find the input text box comes up on screen with in your jupyter notebook.
Formatting operations
you can use variable called my_var, which is set to the string value barks. Using the arithmetic operator the manual concatenation s hard to read. And anything within curly braces in that string will be interpreted as an expression. If the backslash charecter is used to escape codes and for special charecters. If you want a backslash within your string, you simply specified two backslashes.
The most important concept to understand is that in Python, functions are objects. This means a function can return another function and one function can take another function as an argument. We can also define a function within another function. Functions can also be assigned to a variable.
Python framework and packages
PyUnit (unit testing), PyDoc (documentation), SciPy (algebra and numerical), Pandas (data management), Sci-Kit learn (ML and data science), Tensorflow (AI), Numpy (array and numerical), BeautifulSoap, Flask (microframework), Pyramid (enterprise applications), Django (UI MVVM), urllib (web pages scraping), Tkinter (GUI), mock (mocking library), PyChecker, Pylint (module code analysis)