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.

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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

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)

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

Market Researcher

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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.

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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.

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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.

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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.

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Epidemiologist

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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.

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Public Health Analyst

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Clinical Research Associate (CRA)

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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.

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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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