Get to know Netflixify

Problem statement:

There are a lot of movies and TV shows out there and not all of them are of your preferences. Hence, we developed Netflixity, where we will recommend several shows based on your preferences. Fret not as synopsis of the shows are also included to help you choose your movie better.

Question proposed:

1.What factor do people consider when selecting movies or TV shows?

2.How can we find similar movies to the one we liked before?

Possible stakeholder

As our project is used for entertainment purpose, our stakeholder will be general public of all ages. It can be teenagers, working adult or elderly.

Data Science Process

ASKING QUESTION

We list out the problems and questions and how we can answer the questions with the dataset.

FINDING DATA

Find and search suitable dataset online such as kaggle

GETTING DATA

Access the dataset online such as

CLEANING DATA

Correcting and removing corrupt or inaccurate records from the dataset and we also remove columns that we are not using.

ANALYSING DATA

From the data we have, we analysed and visualised it by creating the EDA.

Dataset and application explanation

DATASET USED

We get our dataset from kaggle. the dataset that we decided to used contain type, title, director, cast, country, date added, genre, rating, year released and description. After analysing, we clean the dataset. The missing data and unused column is removed from the dataset.

After the data cleaning, the feature that left in the dataset are type, title, cast, country, year released, rating, genre and lastly the description.

Our shiny app caters to our users’ needs as we allow users to input their;

• Preferred Type of Show
• Favourite Genre
• Country of Show

Users then will get an output of table that consists of type of show, its title, origin country, year of show, rating, genre and synopsis.

Screenshot of Netflixify

NETFLIXIFY Github

KEY ELEMENT

• By using our app, user can enjoy watching shows suitable to their taste. No more spending an hour watching a shows which ended up not to your liking

• As our audience is of all ages, we made the app simple to use.

• Save time. Especially for students and working adults, they wont need to surf internet for a long time just to find a movie to watch during their free time which rarely comes

EXPERIENCES

• During executing the project, it was a challenging yet exciting experience for us.

• We came across several errors and one of the biggest one is to publish our Shiny apps.

• From this project, we learnt to appreciate and use data to make a data product beneficial to public