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Movies Correlation Project

Overview and Purpose

In this Project i have worked on a dataset having data related to movies. I have downloaded this dataset from kaggle.I have done this project on Jupyter notebook using python libraries like pandas, matplotlib, seaborn numpy.

The purpose of this project is to see whether there is any correlation between the different fields.

I am considering two hypothesis:

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  • Budget High Correlation with Gross

  • Company High Correlation with Gross      

Importing Modules and Dataset

In this Project i have use pandas,seaborn,numpy,matplotlib

Importing Modules.png

Importing movies dataset and creating a dataframe named as 'movies' using read_csv function of pandas module.

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Copying the dataframe and storing it in another dataframe so my original dataframe remains safe,if something goes wrong in that case i have my original dataframe with me

Data import
Data

Data Cleaning and Tranforming Using Pandas

Here i have spllited the column 'released' to seperate date value 

Splitting column Code.png
Data after spltting column.png

Looking for any missing values in the data

Looking for Missing Data.png

Looking at the results most of the fields have null values.

Looking for missing data by null values.png

Maximum null values are in budget field

Summing of null values.png

Filling null values by median values using .fillna method 

filling null values Median of budget.png
filling null values Median of Gross.png
Filling the null Values.png

Droping the irrelevent columns from the dataset

Dropping irrelavent columns.png

Checking if there is any missing data still left

Checking any null values left.png

Changing the data type

Changing Data Types.png

Data after Cleaning

Cleaned Data.png

Visualization

Plotting the Budget vs Gross Scatter plot using Matplotlib library to see is there any relation between Budget and Gross

Scatter Plot.png

Plotting the Budget vs Gross regression plot using seaborn library

Regression Plot.png

Correlation 

Correlation matrix showing how the fields are correlated with each other

Correlation.png

Heat map showing the correlation in the more dynamic way. It can be seen that there is high correlation between budget and gross

Heat map.png

Converting the field having 'object' data type into 'Categorical' data type and by using cat.codes method assigning a unique code to a each category 

Converting string into int.png
Correlation of numerized Data.png

Heat map showing correlation matrix after changing the data type

Heat map of numerized Data.png
Unstacking of matrix.png
Sorting the Matrix.png

Conclusion

From the Result it can be concluded that 1 hypothesis came True and other was False.

It was seen that there was no correlation between company and gross hence this hypothesis was false.

But there was high correlation between budget and gross hence our this hypothesis came True
Sorting values in descending order.png
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