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Extracted movie data using the omdb API. Also performed data cleansing and transformation.

Python 100.00%
data-extraction python movie-api data-cleaning omdb-api mongodb json big-data nosql

moviedataextraction_python's Introduction

Overview

For movie data extraction, I have used Python to access movie data. I have imported the omdb package. Next, I set up the omdb API to be used to pull movie data. Finally, I used the search() method to extract movie data. For the target keywords, I have extracted title, imdb ID, year of release & movie type. Here, I have set to calls limit to 20, since it allowed only a limited of API calls per day. The page count can be extended upto 100.

Movie API source

http://www.omdbapi.com/

Target Keywords

“Canada”, “University”, “Moncton”, “Halifax”, “Toronto”, “Vancouver”, “Alberta”, “Niagara”.

File description

  • movie_extraction.py: This python script file has the code for API setup, movie data extraction for title, imdb ID, year of release & movie type and data cleaning process.

  • movie_extraction_pt2.py: Script to extract movie rating, genre, and plot from the stored movie data.

  • movie_data_cleaned.json:

Data Cleaning

For all the movie data, I have removed emoticons, symbols, pictographs, transport/map symbols, flags(iOS), special characters and tags. For removing the special characters, I have used regex substitution. For cleaning all the emojis, symbols, etc. I have created a separate custom function named “clean_emoji”. This function also performs a regex operation to substitute and clean data.

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