IMDB-DATA-VISUALIZATION PROJECT

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Data set consits of top 100 performing movies from the year 2010 to 2016

Major Objectives

• Performed data manipulation, analysis, and visualisation to get various insights about the data
• Finding most popular and unpopular genre among the top 1000 Voters
• Analysis on US vs non-US voters responses
• Finding the most popular trio interms of certain important features
• visualisation of results using different inbuilt packages

Code and Resources Used

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Python Version: 3.7
Packages: pandas, numpy, seaborn, matplotlib

Data Manipulation

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After reading the data and inspecting further we found that there are certain columns which needs data manipulation so we did the following steps.

• Numeric columns like budget and gross are too big compromising its readability, converting $ to million $
• creating profit column with dufference from gross and budget column

Data visualization

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• plotting the results obtained by categorizing different genres to CNT
• Using heatmaps to find the correlation between different gender votes aftecting the rating
• Outlier Analysis using box plots to find the votes casted by under 18 age group for R- rated movies