Pandas: Get the details of the third movie of the DataFrame

Last update on December 21 2024 07:54:00 (UTC/GMT +8 hours)

Write a Pandas program to get the details of the third movie of the DataFrame (movies_metadata.csv file).

Sample Solution:

Python Code :

import pandas as pd
df = pd.read_csv('movies_metadata.csv')
third_movie = df.iloc[2]
print("Details of the third moviee:")
print(third_movie)

Sample Output:

Details of the third moviee:
adult                                                                False
belongs_to_collection    {'id': 119050, 'name': 'Grumpy Old Men Collect...
budget                                                                   0
genres                   [{'id': 10749, 'name': 'Romance'}, {'id': 35, ...
homepage                                                               NaN
id                                                                   15602
imdb_id                                                          tt0113228
original_language                                                       en
original_title                                            Grumpier Old Men
overview                 A family wedding reignites the ancient feud be...
popularity                                                         11.7129
poster_path                               /6ksm1sjKMFLbO7UY2i6G1ju9SML.jpg
production_companies     [{'name': 'Warner Bros.', 'id': 6194}, {'name'...
production_countries     [{'iso_3166_1': 'US', 'name': 'United States o...
release_date                                                    1995-12-22
revenue                                                                  0
runtime                                                                101
spoken_languages                  [{'iso_639_1': 'en', 'name': 'English'}]
status                                                            Released
tagline                  Still Yelling. Still Fighting. Still Ready for...
title                                                     Grumpier Old Men
video                                                                False
vote_average                                                           6.5
vote_count                                                              92
Name: 2, dtype: object  
                                         

Python-Pandas Code Editor:

Sample Table:

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