According to a survey conducted among adults in the United States in May 2021, 12 percent of respondents said they had no close friends. This marked an increase compared to a three percent share of U.S. adults stating the same thing during a survey conducted in 1990. Conversely, the percentage of Americans who said they had 10 or more close friends decreased from 33 percent in 1990 to 13 percent in 2021. The decrease of larger friend groups went hand in hand with a rise of adults stating they had between one to four close friends.

A stateside social recession? Americans marrying later, working longer hours, and becoming more geographically mobile are some elements posited as potential reasons for the nation's increasing loneliness - all this without mentioning the far-reaching consequences of the COVID-19 pandemic.

Percentage of persons aged 15 years and over by satisfaction with friend relationships, by gender, for Canada, regions and provinces.

The whole data and source can be found at https://emilhvitfeldt.github.io/friends/

"The goal of friends to provide the complete script transcription of the Friends sitcom. The data originates from the Character Mining repository which includes references to scientific explorations using this data. This package simply provides the data in tibble format instead of json files."

Content

• friends.csv - Contains the scenes and lines for each character, including season and episodes.
• friends_emotions.csv - Contains sentiments for each scene - for the first four seasons only.
• friends_info.csv - Contains information regarding each episode, such as imdb_rating, views, episode title and directors.

Uses

• Text mining, sentiment analysis and word statistics.
• Data visualizations.

This statistic shows the results of a 2013 survey among Americans aged 16 and older regarding the qualities they are looking for in a close friend. This statistic only shows the top five answers to that question. 81 percent of the respondents stated a close friend has to be loyal.

Friends is an American television sitcom, created by David Crane and Marta Kauffman, which aired on NBC from September 22, 1994, to May 6, 2004, lasting ten seasons. With an ensemble cast starring Jennifer Aniston, Courteney Cox, Lisa Kudrow, Matt LeBlanc, Matthew Perry and David Schwimmer, the show revolves around six friends in their 20s and 30s who live in Manhattan, New York City. The series was produced by Bright/Kauffman/Crane Productions, in association with Warner Bros. Television. The original executive producers were Kevin S. Bright, Kauffman, and Crane.

friends.csv

friends_emotions.csv

friends_info.csv

citation("tidytuesdayR")

The statistic shows the share of adults who have ever watched the TV sitcom 'Friends' in the United States as of February 2018, broken down by age group. During the survey, ** percent of respondents aged 18 to 34 stated that they had watched every episode of the hit TV show.

Frequency of in-person contact with friends, population aged 15 years and older, by sex, number and percentage, 2013.

This table contains 462 series, with data for years 1990 - 1998 (not all combinations necessarily have data for all years), and was last released on 2007-01-29. This table contains data described by the following dimensions (Not all combinations are available): Geography (26 items: Belgium (French speaking); Austria; Belgium (Flemish speaking); Canada ...), Sex (2 items: Males; Females ...), Age group (3 items: 11 years; 15 years;13 years ...), Response (3 items: More than one; None; One ...).

Financial overview and grant giving statistics of Friends of Imi Ho Ola

Financial overview and grant giving statistics of Friends Helping Friends Foundation

Friends TV Show Dialog Sequences

Friends TV Show Dialog Sequences

By Suriyadeepan R [source]

About this dataset

The dataset sequences.csv provides a comprehensive collection of dialog sequences retrieved from the popular sitcom Friends. This dataset has been curated to offer researchers, data analysts, and machine learning enthusiasts an extensive resource for studying linguistic patterns and analyzing conversational structures in a highly regarded television series.

Each row of the dataset corresponds to a specific sequence of dialogues exchanged between the characters in the Friends TV show. The sequences are arranged consecutively, ensuring continuity within each set of conversations. This dataset captures moments encompassing different scenarios, emotions, and relationships depicted throughout all ten seasons of the series.

By exploring this dataset, individuals can gain insights into various aspects such as character interactions, humor elements, socio-cultural references, sentimental expressions, conflicts resolution approaches utilized by the characters. Additionally, this resource facilitates language modeling tasks and offers opportunities for sentiment analysis or dialogue generation using natural language processing techniques.

The original sources of these dialog transcripts have been meticulously collated to ensure accuracy and fidelity to the original aired episodes. Researchers interested in studying language use across different contexts can utilize this dataset as a valuable tool for training models or devising creative algorithms based on real-life conversations between fictional characters.

Please note that while every effort has been made to ensure consistency in capturing these sequences accurately from diverse scenes across all ten seasons of Friends TV show with high precision; however inadvertent discrepancies may still exist due to variables like dialogue delivery speed or overlapping speech instances

How to use the dataset

Dataset Overview

The dataset consists of a single file named sequences.csv. It contains multiple columns that provide different information about the dialogues in each sequence. The columns available in the dataset are as follows:

• Sequence ID: A unique identifier for each dialogue sequence.
• Season: The season number in which the dialogue sequence belongs.
• Episode: The episode number within the season where the dialogue sequence appears.
• Sequence Index: The index of each dialogue within a particular sequence.
• Character: The name of the character speaking in a specific line of dialogue.
• Dialogue Text: The actual spoken words by a character.

Please note that there are no date-related columns included in this dataset.

Analyzing and Exploring Data

Once you have loaded or imported the sequences.csv file into your preferred data analysis tool, you can begin exploring and analyzing its contents using various techniques:

• Descriptive Statistics: You can compute basic descriptive statistics on different columns, such as counting unique values, calculating frequencies, or finding patterns across seasons or episodes.
• Character Analysis: By examining data related to characters' names and dialogues, you can analyze their speaking patterns, most frequent speakers, word count distribution per character, etc.
• Episode Analysis: You may explore specific episodes by filtering data based on season and episode numbers to examine particular events or recurring themes within them.
• .**Dialogue Sentiment Analysis:** Applying sentiment analysis techniques to analyze text content might reveal interesting insights about emotions expressed by different characters during various seasons or episodes.

Ensure to use appropriate data visualization techniques to present your findings, such as bar charts, line plots, word clouds, or heatmaps.

Potential Use Cases

• Natural Language Processing (NLP) and Sentiment Analysis: Analyzing the sentiment of characters' dialogues over time or identifying specific emotions expressed during crucial moments in the show.
• Character Interaction Analysis: Identifying character pairs who frequently engage in conversations or analyzing how relationships between characters evolve throughout different seasons.
• Dialogue Generation Models: Training language

Research Ideas

• Sentiment Analysis: The dataset can be used to analyze the sentiment of each dialogue sequence in order to understand the overall mood or tone of specific episodes or characters.
• Dialogue Generation: By training a language model...

Comprehensive YouTube channel statistics for Pongskiez & Friends, featuring 519,000 subscribers and 145,694,038 total views. This dataset includes detailed performance metrics such as subscriber growth, video views, engagement rates, and estimated revenue. The channel operates in the Gaming category and is based in PH. Track 6,088 videos with daily and monthly performance data, including view counts, subscriber changes, and earnings estimates. Analyze growth trends, engagement patterns, and compare performance against similar channels in the same category.

Comprehensive YouTube channel statistics for Rainbow friends Fans, featuring 13,500,000 subscribers and 6,814,898,576 total views. This dataset includes detailed performance metrics such as subscriber growth, video views, engagement rates, and estimated revenue. The channel operates in the Lifestyle category and is based in US. Track 2,785 videos with daily and monthly performance data, including view counts, subscriber changes, and earnings estimates. Analyze growth trends, engagement patterns, and compare performance against similar channels in the same category.

Comprehensive YouTube channel statistics for Oddbods & Friends, featuring 6,700,000 subscribers and 2,949,360,304 total views. This dataset includes detailed performance metrics such as subscriber growth, video views, engagement rates, and estimated revenue. The channel operates in the Entertainment category and is based in US. Track 1,686 videos with daily and monthly performance data, including view counts, subscriber changes, and earnings estimates. Analyze growth trends, engagement patterns, and compare performance against similar channels in the same category.

Comprehensive YouTube channel statistics for Sonic and Friends, featuring 752,000 subscribers and 237,101,173 total views. This dataset includes detailed performance metrics such as subscriber growth, video views, engagement rates, and estimated revenue. The channel operates in the Lifestyle category. Track 533 videos with daily and monthly performance data, including view counts, subscriber changes, and earnings estimates. Analyze growth trends, engagement patterns, and compare performance against similar channels in the same category.

Comprehensive YouTube channel statistics for Green Friends, featuring 472,000 subscribers and 120,842,080 total views. This dataset includes detailed performance metrics such as subscriber growth, video views, engagement rates, and estimated revenue. The channel operates in the Lifestyle category and is based in IN. Track 2,628 videos with daily and monthly performance data, including view counts, subscriber changes, and earnings estimates. Analyze growth trends, engagement patterns, and compare performance against similar channels in the same category.

Financial overview and grant giving statistics of Friends for Kids

Comprehensive YouTube channel statistics for Love Furry Friends - Rescue Channel, featuring 546,000 subscribers and 208,185,160 total views. This dataset includes detailed performance metrics such as subscriber growth, video views, engagement rates, and estimated revenue. The channel operates in the Pets-&-Animals category and is based in US. Track 397 videos with daily and monthly performance data, including view counts, subscriber changes, and earnings estimates. Analyze growth trends, engagement patterns, and compare performance against similar channels in the same category.

Financial overview and grant giving statistics of Friends of the Frg

Financial overview and grant giving statistics of American Friends of Zvehil