Python: A Comprehensive Guide to Understanding the Programming Language - Prof. Parmar, Study notes of Information Technology

Download Python: A Comprehensive Guide to Understanding the Programming Language - Prof. Parmar and more Study notes Information Technology in PDF only on Docsity!

PYTHON

Prepared By: Dhruvik Parmar

What is Python?

■ ■ Created in 1990 by Guido van Rossum. About the origin of Python, Van Rossum wrote in 1996: Over six years ago, in December 1989, I was looking for a “hobby” programming project that would keep me occupied during the week around Christmas. My office would be closed, but I had a home computer, and not much else on my hands. I decided to write an interpreter for the new scripting language I had been thinking about lately: a descendant of ABC that would appeal to Unix/C hackers. I chose Python as a working title for the project.

■ names[0] ‘Ben’ ■ names[1] ‘Chen’ ■ names[2] ‘Yaqin’ ■ names[-2] ‘Chen’ ■ names[-3] ‘Ben’

Control Flow

■ (^) Things that are False •The boolean value false. •The numbers 0(integer),0.0(float) and 0j(complex). •The empty string “”. •The empty list[], empty dictionary{} and empty set().

Tools used for exploring data

graphically

Matplotlib: A library in Python that provides a wide range of static, animated, and interactive visualizations. It is widely used for creating line plots, scatter plots, bar plots, histograms, and more. Scikit Learn: A Python library that provides a range of supervised and unsupervised learning algorithms. It also includes tools for data preprocessing, model selection, and data visualization. A web-based data visualization tool that allows users to create interactive charts, graphs, and dashboards. It supports a wide range of chart types, including scatter plots, line charts, bar charts, and more. Seaborn: A Python library that provides a high-level interface for creating informative and attractive statistical graphics. It is built on top of Matplotlib and provides additional functionality for creating heatmaps, violin plots, and more

Pandas: A Python library that provides data structures and functions for working with structured data. It includes tools for data cleaning, data manipulation, and data visualization. D3: A JavaScript library that provides tools for creating dynamic and interactive data visualizations in web browsers. It is widely used for creating interactive charts, maps, and more. Bokeh: A Python library that provides tools for creating interactive data visualizations in web browsers. It supports a wide range of chart types, including scatter plots, line charts, bar charts, and more. Altair: A Python library that provides a declarative interface for creating statistical visualizations. It is built on top of Vega-Lite and provides additional functionality for creating interactive visualizations

Applications of Data Science

Data Science is the deep study of a large quantity of data, which involves extracting some meaning from the raw, structured, and unstructured data. Extracting meaningful data from large amounts use processing of data and this processing can be done using statistical techniques and algorithm, scientific techniques, different technologies, etc. It uses various tools and techniques to extract meaningful data from raw data. Data Science is also known as the Future of Artificial Intelligence.

Example:

For Example, Jagroop loves books to read but every time he wants to buy some books he is always confused about which book he should buy as there are plenty of choices in front of him. This Data Science Technique will be useful. When he opens Amazon he will get product recommendations on the basis of his previous data. When he chooses one of them he also gets a recommendation to buy these books with this one as this set is mostly bought. So all Recommendations of Products and Showing sets of books purchased collectively is one of the examples of Data Science.

In Transport Data Science is also entered in real-time such as the Transport field like Driverless Cars. With the help of Driverless Cars, it is easy to reduce the number of Accidents. For Example, In Driverless Cars the training data is fed into the algorithm and with the help of Data Science techniques, the Data is analyzed like what as the speed limit in highways, Busy Streets, Narrow Roads, etc. And how to handle different situations while driving etc.

In Finance Data Science plays a key role in Financial Industries. Financial Industries always have an issue of fraud and risk of losses. Thus, Financial Industries needs to automate risk of loss analysis in order to carry out strategic decisions for the company. Also, Financial Industries uses Data Science Analytics tools in order to predict the future. It allows the companies to predict customer lifetime value and their stock market moves. For Example, In Stock Market, Data Science is the main part. In the Stock Market, Data Science is used to examine past behavior with past data and their goal is to examine the future outcome. Data is analyzed in such a way that it makes it possible to predict future stock prices over a set timetable.

Detecting Tumor. Drug discoveries. Medical Image Analysis. Virtual Medical Bots. Genetics and Genomics. Predictive Modeling for Diagnosis etc. In Health Care In the Healthcare Industry data science act as a boon. Data Science is used for:

Image Recognition Currently, Data Science is also used in Image Recognition. For Example, When we upload our image with our friend on Facebook, Facebook gives suggestions Tagging who is in the picture. This is done with the help of machine learning and Data Science. When an Image is Recognized, the data analysis is done on one’s Facebook friends and after analysis, if the faces which are present in the picture matched with someone else profile then Facebook suggests us auto-tagging.

Airline Routing Planning With the help of Data Science, Airline Sector is also growing like with the help of it, it becomes easy to predict flight delays. It also helps to decide whether to directly land into the destination or take a halt in between like a flight can have a direct route from Delhi to the U.S.A or it can halt in between after that reach at the destination. Data Science in Gaming In most of the games where a user will play with an opponent i.e. a Computer Opponent, data science concepts are used with machine learning where with the help of past data the Computer will improve its performance. There are many games like Chess, EA Sports, etc. will use Data Science concepts.

Medicine and Drug Development The process of creating medicine is very difficult and time-consuming and has to be done with full disciplined because it is a matter of Someone’s life. Without Data Science, it takes lots of time, resources, and finance or developing new Medicine or drug but with the help of Data Science, it becomes easy because the prediction of success rate can be easily determined based on biological data or factors. The algorithms based on data science will forecast how this will react to the human body without lab