Gapminder has collected a lot of information about how people live their lives in different countries, tracked across the years, and on a number of different indicators. The dataset was analysed to answer the following questions:
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For countries that have a lower literacy rate, how does the female literacy rate compare to the male literacy rate?
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What is the level of education distribution for men? Does the level of education have a correlation with the sectors these men are employed in?
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Does higher GDP per capita translate to higher CO2 emission per capita?
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In females which cancer is more prevalent now?
For the project mainly Pandas and matplotlib library were used.