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FIMUS imputes numerical and categorical missing values by using a data set’s existing patterns including co-appearances of attribute values, correlations among the attributes and similarity of values belonging to an attribute.
The goal of this project is to visualize the top searches for common health issues in the United States, from Cancer to Diabetes, and compare them with the actual location of occurrences for those same health conditions to understand how search data reflects life for millions of Americans.
an analysis was conducted on the Wine Data to discern the factors that play a pivotal role in determining the quality of wine. An exploration of the correlations between these attributes and the overall wine quality was undertaken, while considering the interplay with other relevant factors
Perform data analysis, explore YouTube disliked datasets using NumPy and Pandas libraries and perform exploratory data analysis to gain meaningful insights.
A/B tests are very commonly performed by data analysts and data scientists. It is important that you get some practice working with the difficulties of these.