Covid-19 Death Medical Analysis & Visualization using Plotly from Coursera

In this 2-hour long project-based course, you will learn how to build bar graphs, scatter plots, Choropleth maps and Wordcloud to analyze and visualize the global scenario of Covid-19 and perform medical analysis to various conditions that contribute to death due to Covid-19. We will be using two separate datasets for this guided project. The first dataset has been taken from worldometer and the second one has been made available by the Centers for Disease Control and Prevention (CDC), United States.

We will be using Python as our Programming language and Google Colab as our notebook. It is required for you to have a Gmail Account for this project. It is recommended to have some experience in the Python programming language but even if you do not have any prior experience in Python programming or medical science, you will be able to complete this project. This project is beginner-friendly.

We will visualize the current global scenario of Covid-19 using bar graphs and scatter plots followed by geographical data visualization using Choropleth maps. Then we will dive into medical analysis. We will then visualize how Covid deaths vary with respect to age group and how various pre-existing medical conditions vary with age. Then we will visualize and analyze how various medical conditions contribute to Covid death. We will also compare the performance of all the 50 states in the US against Covid. In the final task, we will finish by creating WordCloud text visualization of various medical conditions and condition groups that contribute to Covid deaths.

Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

What's inside

Syllabus

Project Overview

In this 1.5 hours long project, We will use Plotly Express, Choropleth maps and WordCloud to analyze and visualize the current global scenario of Covid-19 and the pre-existing medical conditions of Covid-19 patients. We will also analyze the medical conditions contributing to death due to Covid-19. We will be using two separate datasets for this guided project. The first dataset has been taken from worldometer and the second one has been made available by the Centers for Disease Control and Prevention (CDC), United States. We will begin by Importing all the necessary libraries and datasets. Then we will visualize the current global scenario of Covid-19 using bar graphs and scatter plots followed by geographic visualization using Choropleth maps. Then we will dive into medical Analysis. We will then visualize how Covid deaths vary with respect to the age group and how various pre-existing medical conditions vary with age. Then we will visualize and analyze how various medical conditions contribute to covid death. We will also compare the performance of all the 50 states in the US against Covid. In the final task, we will finish by creating WordCloud Text Visualization of various medical conditions and condition groups that contribute to covid deaths. We will be using Plotly Express and Matplotlib for Visualization.

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Develops data visualization skills using Python libraries, useful for analysis and presentation of medical data

Explores the global impact of Covid-19 and how underlying medical conditions contribute to its severity

Suitable for beginners with no prior experience in medical science or Python programming

Leverages real-world datasets from Worldometer and the Centers for Disease Control and Prevention (CDC) for practical analysis

Provides hands-on experience with data visualization tools and techniques

Requires a Gmail account and does not provide equivalent options for non-Gmail users

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Covid-19 Death Medical Analysis & Visualization using Plotly with these activities:

Read and comprehend the assigned chapters from the supplemental course text

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Review the key concepts, theories, and methodologies related to Covid-19 and data analysis in preparation for the course.

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Identify the key concepts and terminologies relevant to the course.
Summarize the main points and arguments presented in each chapter.
Reflect on the implications of the discussed concepts and methodologies for your own understanding of the subject matter.

Review foundational concepts in Python programming

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Refreshing your understanding of Python programming fundamentals will strengthen your ability to follow along with the course material and complete the course projects.

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Review basic data types, operators, and control flow in Python.
Complete a few practice exercises on Python programming basics.

Practice Python coding exercises and data analysis tasks

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Reinforce your understanding of Python programming and data analysis techniques by completing coding exercises and data analysis tasks.

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Identify coding exercises and data analysis tasks that cover the key concepts of the course.
Attempt to solve the exercises and tasks independently.
Review your solutions and identify areas for improvement.

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Organize and expand your notes, assignments, quizzes, and exams

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Improve your retention, organization, and understanding of the course material.

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Gather your notes, assignments, quizzes, and exams in one organized location.
Review the material and identify areas where you can expand your understanding.
Create additional notes, summaries, or mind maps to reinforce your learning.

Explore online tutorials and resources to learn additional skills

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Enhance your knowledge and skills by exploring additional resources and tutorials beyond the course curriculum.

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Identify areas where you would like to improve your skills.
Search for online tutorials and resources that cover these areas.
Follow the tutorials and complete the exercises to reinforce your learning.

Develop a data visualization dashboard on Covid-19 data

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Apply your data analysis and visualization skills to a real-world dataset.

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Collect and clean Covid-19 data from reliable sources.
Determine the most relevant metrics and variables to visualize.
Choose appropriate data visualization techniques to effectively convey the insights.
Create an interactive dashboard that allows users to explore the data and identify trends.

Participate in data analysis or visualization competitions

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Put your skills to the test, receive feedback on your work, and connect with other professionals.

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Identify data analysis or visualization competitions that align with your interests.
Form a team or work individually to prepare your submission.
Participate in the competition and receive feedback on your work.

Develop a presentation on a specific topic related to the course

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Deepen your understanding of a specific topic and improve your communication and presentation skills.

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Choose a topic that aligns with your interests and the course objectives.
Conduct thorough research to gather relevant information and data.
Organize your content into a logical and engaging presentation format.
Practice your presentation and seek feedback from peers or instructors.

Mentor junior students or peers in the course

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Reinforce your understanding of the course material while helping others.

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Identify opportunities to mentor junior students or peers.
Provide guidance and support to help them understand the concepts and complete assignments.
Reflect on your own learning and identify areas where you can improve.

Career center

Learners who complete Covid-19 Death Medical Analysis & Visualization using Plotly will develop knowledge and skills that may be useful to these careers:

Quantitative Analyst (Quant)

Quantitative analyst (Quant) leverage skills in mathematics, finance, and the computer programming language Python to build models of risk, pricing, trading, and other business situations. In this role, you will gain familiarity with big data analysis and visualizations techniques, which are covered in this course.

See salaries and explore the career path for Quantitative Analyst (Quant)

Market Researcher

Market researchers use data analysis techniques to gather and interpret market information to identify trends and make predictions about the future. Knowledge of data visualization, which is developed in this course, can be very helpful to conveying complex data and information in a clear and concise way that is easily understandable to various stakeholders.

See salaries and explore the career path for Market Researcher

Business Analyst

Business analysts use data analysis techniques to identify business needs and develop solutions to improve efficiency and profitability. Python programming and data visualization are used to perform a variety of tasks in this role, from data cleaning to presenting findings in a visually compelling way.

See salaries and explore the career path for Business Analyst

Data Analyst

Data analysts use data analysis techniques to clean, prepare, and analyze data for businesses. This course will help you develop the skills needed to gather, clean, and visualize data, which are essential tasks for data analysts.

See salaries and explore the career path for Data Analyst

Data Scientist

Data scientists use data analysis techniques to solve complex business problems. The programming language Python and data visualization, which are major components of this course, are used extensively in this role and help data scientists to clean, prepare, and visually represent data in order to gain insights and make predictions.

See salaries and explore the career path for Data Scientist

Statistician

Statisticians use data analysis techniques to collect, analyze, interpret, and present data. This course is a helpful introduction to the types of data analysis and visualization techniques used by statisticians.

See salaries and explore the career path for Statistician

Epidemiologist

Epidemiologists use data analysis techniques to investigate the causes and patterns of health and disease in populations. This course provides an introduction to the types of data analysis and visualization techniques used by epidemiologists to identify and analyze patterns and trends in health data.

See salaries and explore the career path for Epidemiologist

Health Informatics Specialist

Health informatics specialists use data analysis techniques to improve the delivery of healthcare services. This course provides an introduction to the types of data analysis and visualization techniques used by health informatics specialists to analyze and interpret health data.

See salaries and explore the career path for Health Informatics Specialist

Public Health Analyst

Public health analysts use data analysis techniques to improve the health of communities. This course will help you develop skills in data analysis and visualization that can be applied to a variety of public health problems.

See salaries and explore the career path for Public Health Analyst

Clinical Research Associate (CRA)

CRAs use data analysis techniques to manage and monitor clinical trials. Familiarity with medical terminology and data visualization techniques, both of which are covered in this course, can be very helpful in this role.

See salaries and explore the career path for Clinical Research Associate (CRA)

Medical Writer

Medical writers use data analysis techniques to interpret and communicate complex medical information. Familiarity with medical terminology and data visualization techniques, both of which are covered in this course, can be very helpful in this role.

See salaries and explore the career path for Medical Writer

Healthcare Data Analyst

Healthcare data analysts use data analysis techniques to improve the quality and efficiency of healthcare services. Familiarity with medical terminology and data visualization techniques, both of which are covered in this course, can be very helpful in this role.

See salaries and explore the career path for Healthcare Data Analyst

Covid-19 Death Medical Analysis & Visualization using Plotly

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