Scrape IMDB movie rating and details using Python and saving the details of top movies to .csv file

We can scrape the IMDb movie ratings and their details with the help of the BeautifulSoup library of Python. 

Modules Needed:

Below is the list of modules required to scrape from IMDB.

1. requests: Requests library is an integral part of Python for making HTTP requests to a specified URL. Whether it be REST APIs or Web Scraping, requests must be learned for proceeding further with these technologies. When one makes a request to a URI, it returns a response.
2. html5lib: A pure-python library for parsing HTML. It is designed to conform to the WHATWG HTML specification, as is implemented by all major web browsers.
3. bs4: BeautifulSoup object is provided by Beautiful Soup which is a web scraping framework for Python. Web scraping is the process of extracting data from the website using automated tools to make the process faster.
4. pandas: Pandas is a library made over the NumPy library which provides various data structures and operators to manipulate the numerical data.

Approach:

Steps to implement web scraping in python to extract IMDb movie ratings and its ratings:

• Import the required modules.

Python3

from bs4 import BeautifulSoup
import requests
import re
import pandas as pd

• Access the HTML content from the webpage by assigning the URL and creating a soap object.

Python3

# Downloading imdb top 250 movie's data
url = 'http://www.imdb.com/chart/top'
response = requests.get(url)
soup = BeautifulSoup(response.text, "html.parser")

• Extract the movie ratings and their details. Here, we are extracting data from the BeautifulSoup object using Html tags like href, title, etc.

Python3

movies = soup.select('td.titleColumn')
crew = [a.attrs.get('title') for a in soup.select('td.titleColumn a')]
ratings = [b.attrs.get('data-value')
        for b in soup.select('td.posterColumn span[name=ir]')]

• After extracting the movie details, create an empty list and store the details in a dictionary, and then add them to a list.

Python3

# create a empty list for storing
# movie information
list = []

# Iterating over movies to extract
# each movie's details
for index in range(0, len(movies)):

    # Separating movie into: 'place',
    # 'title', 'year'
    movie_string = movies[index].get_text()
    movie = (' '.join(movie_string.split()).replace('.', ''))
    movie_title = movie[len(str(index))+1:-7]
    year = re.search('\((.*?)\)', movie_string).group(1)
    place = movie[:len(str(index))-(len(movie))]
    data = {"place": place,
            "movie_title": movie_title,
            "rating": ratings[index],
            "year": year,
            "star_cast": crew[index],
            }
    list.append(data)

• Now or list is filled with top IMBD movies along with their details. Then display the list of movie details

Python3

for movie in list:
    print(movie['place'], '-', movie['movie_title'], '('+movie['year'] +
          ') -', 'Starring:', movie['star_cast'], movie['rating'])

• By using the following lines of code the same data can be saved into a .csv file be further used as a dataset.

Python3

#saving the list as dataframe
#then converting into .csv file
df = pd.DataFrame(list)
df.to_csv('imdb_top_250_movies.csv',index=False)

Implementation: Complete Code

Python3

from bs4 import BeautifulSoup
import requests
import re
import pandas as pd


# Downloading imdb top 250 movie's data
url = 'http://www.imdb.com/chart/top'
response = requests.get(url)
soup = BeautifulSoup(response.text, "html.parser")
movies = soup.select('td.titleColumn')
crew = [a.attrs.get('title') for a in soup.select('td.titleColumn a')]
ratings = [b.attrs.get('data-value')
        for b in soup.select('td.posterColumn span[name=ir]')]




# create a empty list for storing
# movie information
list = []

# Iterating over movies to extract
# each movie's details
for index in range(0, len(movies)):

    # Separating movie into: 'place',
    # 'title', 'year'
    movie_string = movies[index].get_text()
    movie = (' '.join(movie_string.split()).replace('.', ''))
    movie_title = movie[len(str(index))+1:-7]
    year = re.search('\((.*?)\)', movie_string).group(1)
    place = movie[:len(str(index))-(len(movie))]
    data = {"place": place,
            "movie_title": movie_title,
            "rating": ratings[index],
            "year": year,
            "star_cast": crew[index],
            }
    list.append(data)

# printing movie details with its rating.
for movie in list:
    print(movie['place'], '-', movie['movie_title'], '('+movie['year'] +
        ') -', 'Starring:', movie['star_cast'], movie['rating'])


##.......##
df = pd.DataFrame(list)
df.to_csv('imdb_top_250_movies.csv',index=False)

Output: 

Along with this in the terminal, a .csv file with a given name is saved in the same file and the data in the .csv file will be as shown in the following image.