University Institute of Engineering
Department ofComputer Science & Engineering
Experiment number : 98
Student Name:Mrigaank Jaswal
UID:22BCS14681
Branch: Computer Science & Engineering
Section/Group: 404/B
Semester: First
Date of Performance: 7 DEC 2022
Subject Name: DISRUPTIVETECHNOLOGIES-I
Subject Code: 22ECH-102
1.Aim of the practical: Apply appropriate machinelearning model for
accurateprediction of air quality index.
2. Tool Used: Google Colab , Pandas Module , Numpy module
Panda module 
pandas is a Python package that provides fast, flexible, and expressive data structures
designed to make working with "relational" or "labeled" data both easy and intuitive. It aims
to be the fundamental high-level building block for doing practical, real world data analysis
in Python. Additionally, it has the broader goal of becoming the most powerful and flexible
open source data analysis / manipulation tool available in any language. It is already well
on its way towards this goal.
Numpy module 
NumPy is a module for Python. The name is an acronym for "Numeric Python" or "Numerical
Python". It is pronounced /ˈnʌmpaɪ/ (NUM-py) or less often /ˈnʌmpi (NUM-pee)). It is an
extension module for Python, mostly written in C. This makes sure that the precompiled
mathematical and numerical functions and functionalities of Numpy guarantee great execution
speed.
University Institute of Engineering
Department ofComputer Science & Engineering
3. Basic Concept/ Command Description:
Machine Learning 
Machine learning (ML) is a field of inquiry devoted to understanding and building
methods that 'learn', that is, methods that leverage data to improve performance on some
set of tasks.[1] It is seen as a part of artificial intelligence. Machine learning algorithms
build a model based on sample data, known as training data, in order to make predictions
or decisions without being explicitly programmed to do so.[2] Machine learning
algorithms are used in a wide variety of applications, such as in medicine, email
filtering, speech recognition, agriculture, and computer vision, where it is difficult or
unfeasible to develop conventional algorithms to perform the needed tasks.[3][4] A
subset of machine learning is closely related to computational statistics, which focuses on
making predictions using computers, but not all machine learning is statistical learning.
The study of mathematical optimization delivers methods, theory and application
domains to the field of machine learning. Data mining is a related field of study, focusing
on exploratory data analysis through unsupervised learning.[6][7] Some implementations
of machine learning use data and neural networks in a way that mimics the working of
a biological brain.[8][9] In its application across business problems, machine learning is
also referred to as predictive analytics.
4. Code:
Task 1  Download required modules . Download Numpy and Pandas
Task 2  Now Input the data set into Your Project file and provide Variables to the
File path .
University Institute of Engineering
Department ofComputer Science & Engineering
Task 3  Now Import the Data and subsetting the station .
Task 4  Now We will use head() function to view the first n rows of a pandas
DataFrame.
University Institute of Engineering
Department ofComputer Science & Engineering
Task 5  Now We will use Group the Data with pandas DataFrame.
And later we will do Sub Indexing calculations
Task 6 Now we Calculate sub Indexing of various Groups and will provides their in
Comments
University Institute of Engineering
Department ofComputer Science & Engineering
University Institute of Engineering
Department ofComputer Science & Engineering
University Institute of Engineering
Department ofComputer Science & Engineering
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University Institute of Engineering
Department ofComputer Science & Engineering
University Institute of Engineering
Department ofComputer Science & Engineering
Task 7 Now We have to find AQI values of Given by Rounding off all the sub indexing
University Institute of Engineering
Department ofComputer Science & Engineering
University Institute of Engineering
Department ofComputer Science & Engineering
Task 8 Now We have to Print Number of condition found as result of AQI Values
University Institute of Engineering
Department ofComputer Science & Engineering
Task 9  Now we will have to Read the CSV data in Panda
University Institute of Engineering
Department ofComputer Science & Engineering
Task 10  Now we will have to load the CSV data in Panda and print the result
University Institute of Engineering
Department ofComputer Science & Engineering
Learning outcomes (What I have learnt):
1. I get Know about Air Quality Index
2. Learnt about Panda
3. Learnt About Numpy
4. I get know about the accuracy of the Dataset
Evaluation Grid (To be filled by Faculty):
Sr. No.
1.
2.
3.
Parameters
Student Performance (task
implementation and result evaluation)
Viva-Voce
Worksheet Submission (Record)
Signature of Faculty (with Date):
Marks Obtained
Maximum Marks
12
10
Total Marks Obtained:
8
30