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TwitterBy Data Society [source]
The dataset contains valuable columns that offer insights into the episodes. These columns include: - number_in_season: Represents the episode number within its season. - title: Displays the title of each episode. - image_url: Provides the URL of an image associated with each episode. - normalized_text: Presents the normalized text of dialogues within each episode. - original_air_year: Indicates the year in which an episode originally aired. - number_in_series: Represents the overall episode number throughout The Simpsons series. - raw_text: Shows the raw text of entire episodes.
Moreover, this dataset includes additional useful information such as: - name and normalized_name, which provide alternate representations of an episode's title. - us_viewers_in_millions, which displays viewership statistics specifically for viewers in the United States in millions. - Columns like imdb_rating and imdb_votes showcases ratings and voting details collected from IMDb (Internet Movie Database). - Other columns like timestamp_in_ms, speaking_line, raw_character_text, raw_location_text provide additional context to further analyze script lines.
With this rich collection of data on The Simpsons episodes at hand, it becomes easier to explore patterns and trends over time while also deep-diving into specific episodes or characters. Whether you want to examine viewer engagement or understand key aspects related to individual episodes or their dialogues, this dataset provides a robust foundation for analysis
Understanding the Columns
image_url: The URL of an image associated with the episode. You can use this link to access images related to each episode for visualization or analysis purposes.
imdb_rating: The rating of the episode on IMDb. This column provides a numerical rating for each episode based on user votes.
imdb_votes: The number of votes the episode has received on IMDb. This column indicates how many people have contributed their ratings for each episode.
number_in_season: The episode number within its season. For example, if an episode is titled Simpsons Roasting on an Open Fire and has a value of 1 in this column, it means that it is the first episode in that particular season.
number_in_series: The episode number within the entire series. This column represents the sequential order of episodes across all seasons.
original_air_year: The year in which the episode originally aired.
7 .**production_code**: A unique code assigned to each individual Simpsons' episodes for identification purposes during production stages(scrapped by Todd Schneider).
8 .**title**: Title given by viewers for identifying particular epsiodes
9 .**us_viewers_in_millions**: Viewer count(tv-show)
10 .**views** : Number os views(episode) - same eposide watched multiple times counted again - recommeded not using until required.
11 .**name**: The title of the episode.
12 .**normalized_name**: Normalized version (title) - Debugging or specific tasks
number: Contains the episode number.
raw_text: The raw text of the episode content/spoken lines within an episode. Here contains character names, location, spoken words by characters etc.,
15 timestamp_in_ms: Represents the timestamp of a particular line in milliseconds for an elaborate dialogue breakdown
16 speaking_line: Both speaker and non-speaker texts are present in this column(boolean).
17.**raw_character_text:** The name/speaker for each
- Analyzing the popularity of different episodes: By using the viewer statistics and IMDb ratings provided in this dataset, one can analyze which episodes of The Simpsons are the most popular among viewers. This analysis can help identify patterns or trends in viewer preferences and can provide insights into what makes certain episodes more successful than others.
- Predicting future episode ratings: With the IMDb votes information available in this dataset, one can build a predictive model to forecast the ratings of future episodes. By analyzing historical data and identifying key factors that contribute to higher ratings, such as guest appearances or specific storylines, predictions can be made on how well upcoming episodes will be received by viewers.
- Character analysis and dialogue patterns: The dataset includes i...
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Twitterhttps://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
By IMDB, The Movid Database, Wikipedia
Episode info and viewership numbers for all aired episodes of The Simpsons. Info includes director, writers, viewership (millions), IMDB rating, episode title, and synopsis. Also includes a lookup table of all character names.
- simpsons_episodes.csv: Detailed information on each episode including IMDB, TMDB rating and viewership.
- simpsons_characters.csv: Lookup of each simpson character.
If you use this dataset in your research, please credit IMDB, TMDB, Wikipedia.
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TwitterBy Gove Allen [source]
The Simpsons Dataset is an extensive collection of information about the iconic animated television series, The Simpsons. Curated by IMDB.com, this dataset serves as a valuable resource for teaching SQL to college students. It encompasses various categories like characters, episodes, and other notable aspects related to the popular TV show.
This dataset offers a comprehensive view of the beloved characters that have become synonymous with The Simpsons franchise. Students can explore information such as character names, their corresponding genders, and even their occupation within the fictional town of Springfield.
Additionally, this dataset provides detailed insights into each episode of The Simpsons. From episode titles to airdate information, students can discover fascinating facts about all the episodes that have graced our screens over the years. This includes in-depth details such as the season number and episode number each installment belongs to.
Furthermore, this dataset delves into other interesting aspects related to The Simpsons universe. It includes data on voice actors who bring these animated characters to life with their distinctive voices. Additionally, it provides information on guest stars who have made memorable appearances throughout various seasons.
By utilizing this dataset for educational purposes in SQL classes, students can gain hands-on experience working with complex datasets while immersing themselves in one of television's most enduring and beloved shows.
Exploring Character Information
The dataset contains a wide range of information about different characters from The Simpsons. Some key columns that will be useful for analyzing character data include:
id: A unique identifier for each character in the dataset.name: The name of the character.gender: The gender of the character (usually Male or Female).occupation: The occupation or role of the character within the show.hair_color: The color of the character's hair.eye_color: The color of the character's eyes.With these columns, you can perform various analyses such as finding out which occupation category has appeared most frequently, determining gender ratios among characters, comparing hair and eye colors across different demographics, and much more.
Analyzing Episode Details
The dataset also provides extensive information about individual episodes from The Simpsons. Some key columns related to episode details include:
episode_id: A unique identifier for each episode in the dataset.title: The title or name given to that particular episode.original_air_date: Original air date (Provided we had dates.) - Unfortunately missing on our description Nevertheless IMDB link would be availableThese details enable you to explore various aspects related to episodes including their order within seasons, titles patterns , average ratings IMDb.com have assigned*-* Missing info,but normally available at IMDB
(*Note: Ratings data may not be provided in this specific dataset).
Also connect with random fanatics oversight at IMDb URLLinking Characters to Episodes
One of the most interesting aspects of this dataset is linking characters to episodes. Some key columns that help you establish these connections include:
id: A unique identifier for each character in the dataset.episode_id: A unique identifier for each episode in the dataset.By analyzing these columns, you can determine which characters appear in which episodes and analyze their overall presence or frequency within the show. This allows you to create interesting visualizations or run queries to find out details like which character has appeared in the most episodes, which episode features a particular character, and much more.
Overall, this Simpsons TV
- Analyzing character interactions: The dataset can be used to analyze the relationships and interactions between different characters in The Simpsons. By examining which characters frequently appear together or share storylines, researchers can gain insights into the dynamics of the show and how different characters contribute to the overall narrative.
- Studying episode characteristics: The dataset provides various attributes about each episode, such as its title, air date, rating, and number of viewers. Researchers can utili...
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Twitterjamesliu23/simpsons dataset hosted on Hugging Face and contributed by the HF Datasets community
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TwitterScraped from IMDB contains :
Season : Season number Title : Episode Title Airdate : Date of Airing Rating : Imdb public rating Vote Counts : Number of votes given by users Description : Episode plot Description
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TwitterA survey held in April 2018 showed that ***** sitcom ‘The Fresh Prince of Bel-Air’ was U.S. Millennials’ favorite TV show of all time. A total of ** percent of respondents born between 1982 and 1999 had a positive opinion of the show, making ‘Fresh Prince’ more popular among adults in this age group than other hits such as ‘Friends’, ‘Family Guy’, and ‘House’.
Other much-loved shows included ‘Saturday Night Live’, and ‘The Simpsons’, the latter of which was second in the ranking.
What are the most popular TV shows in the U.S.?
In the 2018-2019 season, the most viewed TV show in the United States was NFL Sunday Night Football. The final seasons of ‘The Big Bang Theory’ and ‘Game of Thrones’ also drew in over ** million viewers. Watching television has long been a popular pastime for Americans, and in more recent years, viewers have also begun to stream their favorite content as well as watching it on a traditional TV.
Streaming platforms like Netflix, Hulu, and Amazon Prime Video have created popular digital original series which viewers can enjoy online, ranging from Netflix’s ‘Stranger Things’ to ‘Titans’ from the DC Universe. Digital original TV shows have become just as popular and in demand as beloved sitcoms like ‘Friends’ and animated series ‘The Simpsons’, and attract attention not only among TV fans but also social media users keen to discuss new releases and plot twists.
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Twittermuhammad0-0hreden/simpsons-blip-captions_part_2 dataset hosted on Hugging Face and contributed by the HF Datasets community
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Twitterhttps://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
Name of Cartoon: This column would contain the names of various cartoons or animated series. Examples include "SpongeBob SquarePants," "Tom and Jerry," "The Simpsons," "Pokemon," etc.
Span Over the Years: This column would indicate the time period during which the cartoon aired or was produced. It could be represented as a range (e.g., "1999-2022") or specific years (e.g., "2001-2006, 2015-present").
Rating: This column would contain the ratings of the cartoons. Ratings could be provided by various sources such as IMDb, Rotten Tomatoes, or specific rating agencies. Ratings could be numerical (e.g., out of 10) or categorical (e.g., G, PG, PG-13, etc.).
Description: This column would include a brief description or summary of each cartoon. It would provide an overview of the storyline, main characters, genre, and any other relevant information about the cartoon.
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TwitterMoatasem444/arabic-simpsons-blip-captions dataset hosted on Hugging Face and contributed by the HF Datasets community
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TwitterAttribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
License information was derived automatically
Dataset Card for "simpsons-blip-captions"
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TwitterBy Data Society [source]
The dataset contains valuable columns that offer insights into the episodes. These columns include: - number_in_season: Represents the episode number within its season. - title: Displays the title of each episode. - image_url: Provides the URL of an image associated with each episode. - normalized_text: Presents the normalized text of dialogues within each episode. - original_air_year: Indicates the year in which an episode originally aired. - number_in_series: Represents the overall episode number throughout The Simpsons series. - raw_text: Shows the raw text of entire episodes.
Moreover, this dataset includes additional useful information such as: - name and normalized_name, which provide alternate representations of an episode's title. - us_viewers_in_millions, which displays viewership statistics specifically for viewers in the United States in millions. - Columns like imdb_rating and imdb_votes showcases ratings and voting details collected from IMDb (Internet Movie Database). - Other columns like timestamp_in_ms, speaking_line, raw_character_text, raw_location_text provide additional context to further analyze script lines.
With this rich collection of data on The Simpsons episodes at hand, it becomes easier to explore patterns and trends over time while also deep-diving into specific episodes or characters. Whether you want to examine viewer engagement or understand key aspects related to individual episodes or their dialogues, this dataset provides a robust foundation for analysis
Understanding the Columns
image_url: The URL of an image associated with the episode. You can use this link to access images related to each episode for visualization or analysis purposes.
imdb_rating: The rating of the episode on IMDb. This column provides a numerical rating for each episode based on user votes.
imdb_votes: The number of votes the episode has received on IMDb. This column indicates how many people have contributed their ratings for each episode.
number_in_season: The episode number within its season. For example, if an episode is titled Simpsons Roasting on an Open Fire and has a value of 1 in this column, it means that it is the first episode in that particular season.
number_in_series: The episode number within the entire series. This column represents the sequential order of episodes across all seasons.
original_air_year: The year in which the episode originally aired.
7 .**production_code**: A unique code assigned to each individual Simpsons' episodes for identification purposes during production stages(scrapped by Todd Schneider).
8 .**title**: Title given by viewers for identifying particular epsiodes
9 .**us_viewers_in_millions**: Viewer count(tv-show)
10 .**views** : Number os views(episode) - same eposide watched multiple times counted again - recommeded not using until required.
11 .**name**: The title of the episode.
12 .**normalized_name**: Normalized version (title) - Debugging or specific tasks
number: Contains the episode number.
raw_text: The raw text of the episode content/spoken lines within an episode. Here contains character names, location, spoken words by characters etc.,
15 timestamp_in_ms: Represents the timestamp of a particular line in milliseconds for an elaborate dialogue breakdown
16 speaking_line: Both speaker and non-speaker texts are present in this column(boolean).
17.**raw_character_text:** The name/speaker for each
- Analyzing the popularity of different episodes: By using the viewer statistics and IMDb ratings provided in this dataset, one can analyze which episodes of The Simpsons are the most popular among viewers. This analysis can help identify patterns or trends in viewer preferences and can provide insights into what makes certain episodes more successful than others.
- Predicting future episode ratings: With the IMDb votes information available in this dataset, one can build a predictive model to forecast the ratings of future episodes. By analyzing historical data and identifying key factors that contribute to higher ratings, such as guest appearances or specific storylines, predictions can be made on how well upcoming episodes will be received by viewers.
- Character analysis and dialogue patterns: The dataset includes i...