Showing 29 of total 29 results (show query)
gojiplus
tuber:Client for the YouTube API
Get comments posted on YouTube videos, information on how many times a video has been liked, search for videos with particular content, and much more. You can also scrape captions from a few videos. To learn more about the YouTube API, see <https://developers.google.com/youtube/v3/>.
Maintained by Gaurav Sood. Last updated 8 months ago.
access-youtubecaptionvideoyoutubeyoutube-apiyoutube-oauth
60.5 match 184 stars 8.99 score 206 scripts
vosonlab
vosonSML:Collecting Social Media Data and Generating Networks for Analysis
A suite of easy to use functions for collecting social media data and generating networks for analysis. Supports Mastodon, YouTube, Reddit and Web 1.0 data sources.
Maintained by Bryan Gertzel. Last updated 8 months ago.
hyperlinkmastodonnetwork-graphredditsnasocial-mediasocial-network-analysisvosonyoutube
27.5 match 79 stars 7.67 score 66 scripts 1 dependentsgojiplus
tubern:R Client for the YouTube Analytics and Reporting API
Get statistics and reports from YouTube. To learn more about the YouTube Analytics and Reporting API, see <https://developers.google.com/youtube/reporting/>.
Maintained by Gaurav Sood. Last updated 7 years ago.
youtubeyoutube-analyticsyoutube-api
31.8 match 12 stars 4.92 score 14 scripts
ijlyttle
vembedr:Embed Video in HTML
A set of functions for generating HTML to embed hosted video in your R Markdown documents or Shiny applications.
Maintained by Ian Lyttle. Last updated 3 years ago.
boxembed-videosrmarkdownshinyvimeoyoutube
12.0 match 58 stars 7.83 score 520 scripts
fhdsl
metricminer:Mine Metrics from Common Places on the Web
Mine metrics on common places on the web through the power of their APIs (application programming interfaces). It also helps make the data in a format that is easily used for a dashboard or other purposes. There is an associated dashboard template and tutorials that are underdevelopment that help you fully utilize 'metricminer'.
Maintained by Candace Savonen. Last updated 2 days ago.
9.6 match 2 stars 6.13 score 21 scripts
selesnow
rytstat:Work with 'YouTube API'
Provide function for get data from 'YouTube Data API' <https://developers.google.com/youtube/v3/docs/>, 'YouTube Analytics API' <https://developers.google.com/youtube/analytics/reference/> and 'YouTube Reporting API' <https://developers.google.com/youtube/reporting/v1/reports>.
Maintained by Alexey Seleznev. Last updated 10 months ago.
21.1 match 1 stars 2.78 score 12 scripts
davisj95
YTAnalytics:Wrapper for 'YouTube Analytics' API
Simplify working with the 'YouTube Analytics' API <https://developers.google.com/youtube/analytics>. Collect data for your channel including geography, traffic sources, time period, etc.
Maintained by Jake Davis. Last updated 10 hours ago.
14.7 match 3.40 score
thinkr-open
remedy:'RStudio' Addins to Simplify 'Markdown' Writing
An 'RStudio' addin providing shortcuts for writing in 'Markdown'. This package provides a series of functions that allow the user to be more efficient when using 'Markdown'. For example, you can select a word, and put it in bold or in italics, or change the alignment of elements inside you Rmd. The idea is to map all the functionalities from 'remedy' on keyboard shortcuts, so that it provides an interface close to what you can find in any other text editor.
Maintained by Colin Fay. Last updated 5 years ago.
4.8 match 452 stars 7.83 score 50 scripts
miferreiro
bdpar:Big Data Preprocessing Architecture
Provide a tool to easily build customized data flows to pre-process large volumes of information from different sources. To this end, 'bdpar' allows to (i) easily use and create new functionalities and (ii) develop new data source extractors according to the user needs. Additionally, the package provides by default a predefined data flow to extract and pre-process the most relevant information (tokens, dates, ... ) from some textual sources (SMS, Email, YouTube comments).
Maintained by Miguel Ferreiro-Díaz. Last updated 1 years ago.
custom-flowcustom-pipespreprocessingr6
6.1 match 8 stars 5.23 score 14 scripts
alshum
hashids:Generate Short Unique YouTube-Like IDs (Hashes) from Integers
An R port of the hashids library. hashids generates YouTube-like hashes from integers or vector of integers. Hashes generated from integers are relatively short, unique and non-seqential. hashids can be used to generate unique ids for URLs and hide database row numbers from the user. By default hashids will avoid generating common English cursewords by preventing certain letters being next to each other. hashids are not one-way: it is easy to encode an integer to a hashid and decode a hashid back into an integer.
Maintained by Alex Shum. Last updated 6 years ago.
3.3 match 18 stars 4.10 score 14 scripts
business-science
anomalize:Tidy Anomaly Detection
The 'anomalize' package enables a "tidy" workflow for detecting anomalies in data. The main functions are time_decompose(), anomalize(), and time_recompose(). When combined, it's quite simple to decompose time series, detect anomalies, and create bands separating the "normal" data from the anomalous data at scale (i.e. for multiple time series). Time series decomposition is used to remove trend and seasonal components via the time_decompose() function and methods include seasonal decomposition of time series by Loess ("stl") and seasonal decomposition by piecewise medians ("twitter"). The anomalize() function implements two methods for anomaly detection of residuals including using an inner quartile range ("iqr") and generalized extreme studentized deviation ("gesd"). These methods are based on those used in the 'forecast' package and the Twitter 'AnomalyDetection' package. Refer to the associated functions for specific references for these methods.
Maintained by Matt Dancho. Last updated 1 years ago.
anomalyanomaly-detectiondecompositiondetect-anomaliesiqrtime-series
1.3 match 339 stars 9.56 score 332 scripts
argocanada
argoFloats:Analysis of Oceanographic Argo Floats
Supports the analysis of oceanographic data recorded by Argo autonomous drifting profiling floats. Functions are provided to (a) download and cache data files, (b) subset data in various ways, (c) handle quality-control flags and (d) plot the results according to oceanographic conventions. A shiny app is provided for easy exploration of datasets. The package is designed to work well with the 'oce' package, providing a wide range of processing capabilities that are particular to oceanographic analysis. See Kelley, Harbin, and Richards (2021) <doi:10.3389/fmars.2021.635922> for more on the scientific context and applications.
Maintained by Dan Kelley. Last updated 30 days ago.
1.5 match 17 stars 7.32 score 203 scripts
atmoschem
vein:Vehicular Emissions Inventories
Elaboration of vehicular emissions inventories, consisting in four stages, pre-processing activity data, preparing emissions factors, estimating the emissions and post-processing of emissions in maps and databases. More details in Ibarra-Espinosa et al (2018) <doi:10.5194/gmd-11-2209-2018>. Before using VEIN you need to know the vehicular composition of your study area, in other words, the combination of of type of vehicles, size and fuel of the fleet. Then, it is recommended to start with the project to download a template to create a structure of directories and scripts.
Maintained by Sergio Ibarra-Espinosa. Last updated 1 months ago.
atmoschematmospheric-chemistryatmospheric-scienceatmospheric-sciencesemissionsemissions-modelvehicular-emissions-inventoriesveinfortranopenmp
1.3 match 46 stars 8.65 score 137 scripts
atomashevic
transforEmotion:Sentiment Analysis for Text, Image and Video using Transformer Models
Implements sentiment analysis using huggingface <https://huggingface.co> transformer zero-shot classification model pipelines for text and image data. The default text pipeline is Cross-Encoder's DistilRoBERTa <https://huggingface.co/cross-encoder/nli-distilroberta-base> and default image/video pipeline is Open AI's CLIP <https://huggingface.co/openai/clip-vit-base-patch32>. All other zero-shot classification model pipelines can be implemented using their model name from <https://huggingface.co/models?pipeline_tag=zero-shot-classification>.
Maintained by Aleksandar Tomašević. Last updated 2 months ago.
1.7 match 26 stars 6.40 score 12 scripts
tuncerkerem
experimentr:Datasets Used in Social Science Experiments: A Hands-on Introduction
Contains all the datasets that were used in Social Science Experiments: A Hands-On Introduction and in its R Companion. Relevant materials can be found at <https://osf.io/b78je>.
Maintained by Kerem Tuncer. Last updated 3 years ago.
3.8 match 2.70 score 8 scriptsvosonlab
VOSONDash:User Interface for Collecting and Analysing Social Networks
A 'Shiny' application for the interactive visualisation and analysis of networks that also provides a web interface for collecting social media data using 'vosonSML'.
Maintained by Bryan Gertzel. Last updated 2 years ago.
r-shinyrstudioshinysocial-network-analysisvoson
1.8 match 56 stars 4.45 score 6 scripts
giocomai
ytdlpr:R wrapper for yt-dlp, focused on extracting and processing subtitles
Get subtitles from YouTube and parse them.
Maintained by Giorgio Comai. Last updated 9 months ago.
4.3 match 1.70 score
kenjisato
juicedown:'juice' + 'markdown': Convert 'R Markdown' into 'HTML' with Inline Styles
A convenience tool to create 'HTML' with inline styles using 'juicyjuice' and 'markdown' packages. It is particularly useful when working on a content management system (CMS) whose code editor eliminates style and link tags. The main use case of the package is the learning management system, 'Moodle'. Additional helper functions for teaching purposes are provided. Learn more about 'juicedown' at <https://kenjisato.github.io/juicedown/>.
Maintained by Kenji Sato. Last updated 2 years ago.
2.0 match 2.70 score 4 scripts
oobianom
r2social:Seamless Integration of Sharing and Connect Buttons in Markdown and Apps
Implementation of 'JQuery' <https://jquery.com> and 'CSS' styles to allow easy incorporation of various social media elements on a page. The elements include addition of share buttons or connect with us buttons or hyperlink buttons to 'Shiny' applications or dashboards and 'Rmarkdown' documents.Sharing capability on social media platforms including 'Facebook' <https://www.facebook.com>, 'Linkedin' <https://www.linkedin.com>, 'X/Twitter' <https://x.com>, 'Tumblr' <https://www.tumblr.com>, 'Pinterest' <https://www.pinterest.com>, 'Whatsapp' <https://www.whatsapp.com>, 'Reddit' <https://www.reddit.com>, 'Baidu' <https://www.baidu.com>, 'Blogger' <https://www.blogger.com>, 'Weibo' <https://www.weibo.com>, 'Instagram' <https://www.instagram.com>, 'Telegram' <https://www.telegram.me>, 'Youtube' <https://www.youtube.com>.
Maintained by Obinna Obianom. Last updated 8 months ago.
0.8 match 6 stars 5.42 score 29 scripts
bquast
attention:Self-Attention Algorithm
Self-Attention algorithm helper functions and demonstration vignettes of increasing depth on how to construct the Self-Attention algorithm, this is based on Vaswani et al. (2017) <doi:10.48550/arXiv.1706.03762>, Dan Jurafsky and James H. Martin (2022, ISBN:978-0131873216) <https://web.stanford.edu/~jurafsky/slp3/> "Speech and Language Processing (3rd ed.)" and Alex Graves (2020) <https://www.youtube.com/watch?v=AIiwuClvH6k> "Attention and Memory in Deep Learning".
Maintained by Bastiaan Quast. Last updated 1 years ago.
0.5 match 2 stars 5.48 score 6 scripts 5 dependents
manalytics
opitools:Analyzing the Opinions in a Big Text Document
Designed for performing impact analysis of opinions in a digital text document (DTD). The package allows a user to assess the extent to which a theme or subject within a document impacts the overall opinion expressed in the document. The package can be applied to a wide range of opinion-based DTD, including commentaries on social media platforms (such as 'Facebook', 'Twitter' and 'Youtube'), online products reviews, and so on. The utility of 'opitools' was originally demonstrated in Adepeju and Jimoh (2021) <doi:10.31235/osf.io/c32qh> in the assessment of COVID-19 impacts on neighbourhood policing using Twitter data. Further examples can be found in the vignette of the package.
Maintained by Monsuru Adepeju. Last updated 2 years ago.
0.5 match 12 stars 5.30 score 11 scripts
condwanaland
scrobbler:Download 'Scrobbles' from 'Last.fm'
'Last.fm'<https://www.last.fm> is a music platform focussed on building a detailed profile of a users listening habits. It does this by 'scrobbling' (recording) every track you listen to on other platforms ('spotify', 'youtube', 'soundcloud' etc) and transferring them to your 'Last.fm' database. This allows 'Last.fm' to act as a complete record of your entire listening history. 'scrobbler' provides helper functions to download and analyse your listening history in R.
Maintained by Conor Neilson. Last updated 1 years ago.
0.5 match 4 stars 4.92 score 21 scripts
g-rade
actLifer:Creating Actuarial Life Tables
Contains data and functions that can be used to make actuarial life tables. Each function adds a column to the inputted dataset for each intermediate calculation between mortality rate and life expectancy. Users can run any of our functions to complete the life table until that step, or run lifetable() to output a full life table that can be customized to remove optional columns. Methods for creating lifetables are as described in Zedstatistics (2021) <https://www.youtube.com/watch?v=Dfe59glNXAQ>.
Maintained by Grace Rade. Last updated 1 years ago.
0.5 match 4.00 score 5 scripts
ropenspain
comidistar:Puntuaciones de las Catas a Ciegas de El Comidista
Base de datos documentada con las puntuaciones de las catas a ciegas de El Comidista, información sobre los productos y su precio, y metadatos sobre el vídeo subido a YouTube.
Maintained by Gonzalo Garcia-Castro. Last updated 11 months ago.
0.5 match 5 stars 3.40 score 4 scripts
bentaylor1
deepNN:Deep Learning
Implementation of some Deep Learning methods. Includes multilayer perceptron, different activation functions, regularisation strategies, stochastic gradient descent and dropout. Thanks go to the following references for helping to inspire and develop the package: Ian Goodfellow, Yoshua Bengio, Aaron Courville, Francis Bach (2016, ISBN:978-0262035613) Deep Learning. Terrence J. Sejnowski (2018, ISBN:978-0262038034) The Deep Learning Revolution. Grant Sanderson (3brown1blue) <https://www.youtube.com/playlist?list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi> Neural Networks YouTube playlist. Michael A. Nielsen <http://neuralnetworksanddeeplearning.com/> Neural Networks and Deep Learning.
Maintained by Benjamin Taylor. Last updated 2 years ago.
0.8 match 1.34 score 22 scripts
pdlotko
BallMapper:The Ball Mapper Algorithm
The core algorithm is described in "Ball mapper: a shape summary for topological data analysis" by Pawel Dlotko, (2019) <arXiv:1901.07410>. Please consult the following youtube video <https://www.youtube.com/watch?v=M9Dm1nl_zSQfor> the idea of functionality. Ball Mapper provide a topologically accurate summary of a data in a form of an abstract graph. To create it, please provide the coordinates of points (in the points array), values of a function of interest at those points (can be initialized randomly if you do not have it) and the value epsilon which is the radius of the ball in the Ball Mapper construction. It can be understood as the minimal resolution on which we use to create the model of the data.
Maintained by Pawel Dlotko. Last updated 6 years ago.
0.8 match 1.00 score 5 scripts