Hello everyone! In today's lesson, we'll be diving into another exciting Python Pandas data analysis project, leveraging additional Python libraries. Our dataset will focus on the dynamic field of Covid 19. We'll cover the entire process—from manipulating and grouping the data to in-depth analysis and visualization.
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Source:
https://github.com/Rruhid/data/blob/m...
Chapters:
4:07 - Group the DataFrame df by the 'WHO Region' column and then plotting the sum of confirmed cases for each region in a bar plot.
08:10- Plot a bar graph of the top 10 countries/regions with the highest number of active cases.
10:50 - Calculate the correlation coefficients between the selected columns
17:16 - Check out fatality and recovery rate using scatterplot
22:30 - Using a pie chart to represent the top 10 countries with the highest number of new cases
24:00 - Deaths vs. Recovered on scatterplot
25:30 - Top 10 Countries with the Maximum Number of COVID-19 Death Cases
30:10 - Relation between Confirmed Cases and Deaths by Country/Region
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Data Visualization
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Sales Data
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Data From Zero to Hero covid 19 analysis in pandas
Data science project: Review the insights and analysis generated from our sales data throughout the project.
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Contact Me:
Linkedin: / ruhid-shihkerimov
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