General description of python

1. Python Programming
Language
By:
Dr. Abhinav Sharma
Department of EEE
UPES

2. Python
 Python is a high level programming language.
 Python is often described as a "batteries
included" language due to its comprehensive
standard library.
 It was introduced in 1991 by Guido van Rossum,
a Dutch computer programmer.
 The language places strong emphasis on code
reliability and simplicity so that the programmer
can develop applications rapidly.
 It is open-source.

3.  There are large number of programming language like
C, C++, Java, but when compared to all these
languages Python has simplest syntax.
 Python is a cross platform language which means that
the code written for one operating system like
windows will work equally well with Linux, MacOS
without any changes.

4.  Anaconda is a program that consists of python +
couple of python libraries. It also has it’s own
virtual environment and repository.
 Jupyter is a Python notebook ("interactive
python").
 Spyder is just an Integrated Development
Environment (IDE) for python.
 Google Colab notebook executes codes on
Google’s cloud server.

5. Anaconda
Software

6. JupyterLab is a web-based interactive development environment for Jupyter
notebooks, code, and data.
JupyterLab is flexible: configure and arrange the user interface to support a
wide range of workflows in data science, scientific computing, and machine
learning.
JupyterLab is extensible and modular: write plugins that add new components
and integrate with existing ones.

7. Spyder is an open source cross-platform integrated development environment
(IDE) for scientific programming in the Python Programming language.
It integrates with a number of prominent packages in the scientific Python
stack, including Numpy, SciPy, Matplotlib, Pandas as other open source
software.

8. Libraries Required for Machine
Learning in Python
• NumPy
• SciPy
• Pandas
• Matplotlib
• fbprophet
• TensorFlow
• Keras
• pylab
• Scikit-learn

9. Advantages of Python
 Most programs in Python require considerably
less number of lines of code to perform the same
task compared to other languages like C.
 Less Programming time and programming errors.

10. Basic datatypes in Python
 Number- Integers, floating point numbers and complex
numbers fall under Python numbers category. They are
defined by int, float, complex classes in Python. W can
use a type() function to know which class a variable or
value belongs to.
 String- Strings are sequences of character data. String
literals may be delimited using either single or double
quotes. A string in Python can contain as many
characters as you wish. The only limit is your machine’s
memory resources. A string can also be empty.
 List- It is an ordered sequence of items. It is one of the
most used datatype in Python and is very flexible. All the
items in a list do not need to be of the same type.
Declaring a list is pretty straight forward. Items separated
by commas are enclosed within brackets. For example- a
= [1, 2.2, 'python'].

11.  Tuple- It is an ordered sequence of items same as
a list. The only difference is that tuples are
immutable. Tuples once created cannot be
modified. Tuples are used to write-protect data and
are usually faster than lists as they cannot change
dynamically. It is defined within parenthesis ()
where items are separated by commas. Example:
a=(1,2,3+4j,’abc’)
We can use a slicing operator [] to extract an item
but we cannot change its value.
 Dictionary- Dictionary is an unordered collection of
key-value pairs. It is generally used when we have
a huge amount of data. Dictionaries are optimized
for retrieving data. We must know the key to
retrieve the value. In Python, dictionaries are

12. Python Libraries
 Numpy- It is a Python library which is used for
scientific computing. It contains among other things-a
powerful array object, mathematical and statistical
functions.
 Pandas- It is a software library written for the Python
programming language for data manipulation and
analysis. Pandas allows various data manipulation
operations such as merging, reshaping, selecting, as
well as data cleaning, and data wrangling features.
 Matplotlib-It is a plotting library for the Python
programming language which produces 2D plots to
render visualization and helps in exploring the data
sets. Matplotlib.pyplot is a collection of command
style functions that make matplotlib work like
MATLAB.

13.  Pylab- It is a procedural interface to the Matplotlib
object-oriented plotting library. Matplotlib is the
whole package; matplotlib.pyplot is a module in
Matplotlib; and PyLab is a module that gets
installed alongside Matplotlib. PyLab is a
convenience module that bulk imports
matplotlib.pyplot (for plotting) and NumPy (for
Mathematics and working with arrays) in a single
name space.
 Scikit-learn (sklearn)- It is a machine learning
library for the Python programming language. It
contains various classification, regression and
clustering algorithms. Built on NumPy, Scipy and
matplotlib, it is designed to interpolate smoothly
between the libraries.

14. Python io module
 Python io module allows us to manage the file
related input-output operations.
 The scipy.optimize package provides several
commonly used optimization algorithms.
The scipy.optimize package provides several commonly used optimization algorithms.