COVID19 Data Analysis Using Python -- Coursera Project

This COVID19 dataset, published by John Hopkins University, consists of the data related to the cumulative number of confirmed cases, per day, in each country. Also, there is another dataset consisting of various life factors, scored by the people living in each country around the globe. By merging these two datasets, the relationship between the spread of the virus in a country and how happy people are, living in that country is found out.

A data analysis project that explores global COVID-19 trends using Python, with a focus on cases, deaths, and recovery rates over time. It involves data cleaning, visualization, and statistical insights using libraries like Pandas, Matplotlib, and Seaborn to understand the pandemic's impact.

MADE on rhyme.com using jupyter notebook

Data Analysis on COVID19 dataset, published by John Hopkins University

we are going to work with COVID19 dataset, published by John Hopkins University, which consist of the data related to cumulative number of confirmed cases, per day, in each Country.

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how to preprocess and merge datasets to calculate needed measures and prepare them for an Analysis. In this project, we are going to work with the COVID19 dataset, published by John Hopkins University, which consists of the data related to the cumulative number of confirmed cases, per day, in each Country. Also, we have another dataset consist of various life factors, scored by the people living in each country around the globe. We are going to merge these two datasets to see if there is any relationship between the spread of the virus in a country and how happy people are, living in that country.

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Here I have done an analytical research about current covid 19 situation

Used Python to work with COVID-19 dataset published by Johns Hopkins University and other datasets consisting of various life factors, scored by people living in each country worldwide and Merged two datasets to determine relationship between spread of virus in country and happiness level of country’s citizens

This project uses Python to analyze COVID-19 data alongside happiness scores from the World Happiness Report, investigating their correlation. It requires Python, Jupyter Notebook, pandas, numpy, matplotlib, and seaborn. Contributions are encouraged.

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In this project, we are going to work with the COVID19 dataset, published by John Hopkins University, which consists of the data related to the cumulative number of confirmed cases, per day, in each Country. Also, we have another dataset consist of various life factors, scored by the people living in each country around the globe. We are going to merge these two datasets to see if there is any relationship between the spread of the virus in a country and how happy people are, living in that country.

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Exploration and Visualization of covid19 in Nigeria using Python

COVID19 Data Analysis Using Python and Machine Learning

Covid19 data Analysis using python pandas numpy matplotlib seaborn

COVID19: Global Data Analysis Using Python. Check out its web page at https://yesdeepakmittal.github.io/COVID19/

Python is used to perform sentiment analysis on covid19 Twitter data.

"COVID-19 Data Analysis Repository: Delve into comprehensive insights using Python, Scikit-learn, Seaborn, and other data science packages. Analyze the coronavirus dataset to discern patterns and identify demographics most affected by the virus. Contribute to the global understanding of COVID-19's impact. #DataAnalysis #COVID19 #ScikitLearn #Seabo

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Covid19-Data-Analysis-using-python

COVID19 Data Analysis Using Python

Covid19 Data Analysis Using Python

Covid19 Data Analysis Using Python

COVID19 Data Analysis Using Python

COVID19 Data Analysis Using Python