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I-Shaped Developer
I-shapedSpecialist — deep expertise in Jupyter Notebook
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In this project, I worked with the The Movie Database (TMDB) Box Office Prediction data set. The motion picture industry is raking in more revenue than ever with its expansive growth the world over. Can we build models to accurately predict movie revenue? Could the results from these models be used to further increase revenue? I tried to answer these questions by the way of exploratory data analysis (EDA) in this project and the next. The statistical data visualization libraries Seaborn and Plotly will be my workhorses to generate interactive, publication-quality graphs.
In this Project, I have learned how to preprocess and merge datasets to calculate needed measures and prepare them for an Analysis. In this project I have worked 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. Also another dataset consist of various life factors, scored by the people living in each country around the globe. I have merged these two datasets to see if there is any relationship between the spread of the the virus in a country and how happy people are, living in that country.
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