The project involves analyzing structural data related to different areas using Python. Students will be divided into groups to choose a dataset, import and process the data using pandas and matplotlib. The analysis will include an overview of the data, exploring its properties and columns, and visualizing information through graphs. Students are instructed to collaborate in Jupyter notebooks, citing sources and presenting their work which will be graded based on tasks like data manipulation, exploratory analysis, modeling and visualization.

1. 1
Project
Data Analysis Using Python – In Different Areas
The goal of the project is to provide a simplified analysis of simple structural data related to
different area as your defining of a certain problem i.e:(the number of cases of coronavirus
infection and the number of deaths across the countries of the world since the outbreak of the
virus).
Implement the practical side of the project using basic Python and special libraries such as
pandas, numpy and matplotlib as well as using the jupyter tool. You have to apply
1- Import the data.
2- Data processing and preparation for the analysis stage.
3- Obtain basic information about the data.
4- Show information from the data in the form of graphs.
The project should include the following topics:
• Data Overview
• Data properties (columns)
• Mechanism of Analysis
o Analyzing data using Python - Phase 1 (reading data)
o Data analysis using Python – Phase2 (data preparation)
o Data analysis using Python - Phase 3 (Data exploration)
o Analyzing data using Python -Phase 4 (Data Analysis)
Instructions:
o You will be divided into groups as Bb groups.
o Each group must choose a leader.
o Each group leader must equally distribute tasks among members.
o You will be practicing what we learned in the labs.
o Using internet resources is allowed, but you should cite the original work.
o Each group must submit their work in one Jupyter Notebook, containing names and IDs
of group members through GitHub
o On the due date of the project, each group will present their work, and members will be
asked few questions during the presentation (BE PREPARED)
o No late submission will be accepted under any circumstances.

2. 2
• Each team will be graded on
 Importing the data into a dataframe.  Ability to manipulate the data inside
the dataframe (renaming, grouping,
slicining).
 Performing Exploratory Data Analysis.  Applying ML algorithms (i.e.
Regression).
 Using the right visualization techniques.  Comments on the code used for
development.
• Each team member will be also graded based on:
 Knowledge about the methods and tools used in the project.
Deliverable instructions
• submit the report at the submission area
• total project marks =10
• Due date: on Thursday 3-Nov.-2022 (9-4-1444)
Good Luck