Showing 16 of total 16 results (show query)
tidyverse
dplyr:A Grammar of Data Manipulation
A fast, consistent tool for working with data frame like objects, both in memory and out of memory.
Maintained by Hadley Wickham. Last updated 26 days ago.
4.8k stars 24.68 score 659k scripts 7.8k dependents
rdatatable
data.table:Extension of `data.frame`
Fast aggregation of large data (e.g. 100GB in RAM), fast ordered joins, fast add/modify/delete of columns by group using no copies at all, list columns, friendly and fast character-separated-value read/write. Offers a natural and flexible syntax, for faster development.
Maintained by Tyson Barrett. Last updated 2 days ago.
3.7k stars 23.51 score 230k scripts 4.6k dependents
bioc
plyranges:A fluent interface for manipulating GenomicRanges
A dplyr-like interface for interacting with the common Bioconductor classes Ranges and GenomicRanges. By providing a grammatical and consistent way of manipulating these classes their accessiblity for new Bioconductor users is hopefully increased.
Maintained by Michael Love. Last updated 10 days ago.
infrastructuredatarepresentationworkflowstepcoveragebioconductordata-analysisdplyrgenomic-rangesgenomicstidy-data
144 stars 12.66 score 1.9k scripts 20 dependents
markfairbanks
tidytable:Tidy Interface to 'data.table'
A tidy interface to 'data.table', giving users the speed of 'data.table' while using tidyverse-like syntax.
Maintained by Mark Fairbanks. Last updated 2 months ago.
460 stars 11.39 score 732 scripts 11 dependents
nathaneastwood
poorman:A Poor Man's Dependency Free Recreation of 'dplyr'
A replication of key functionality from 'dplyr' and the wider 'tidyverse' using only 'base'.
Maintained by Nathan Eastwood. Last updated 1 years ago.
base-rdata-manipulationgrammar
342 stars 10.79 score 156 scripts 27 dependents
rstudio
pointblank:Data Validation and Organization of Metadata for Local and Remote Tables
Validate data in data frames, 'tibble' objects, 'Spark' 'DataFrames', and database tables. Validation pipelines can be made using easily-readable, consecutive validation steps. Upon execution of the validation plan, several reporting options are available. User-defined thresholds for failure rates allow for the determination of appropriate reporting actions. Many other workflows are available including an information management workflow, where the aim is to record, collect, and generate useful information on data tables.
Maintained by Richard Iannone. Last updated 3 days ago.
data-assertionsdata-checkerdata-dictionariesdata-framesdata-inferencedata-managementdata-profilerdata-qualitydata-validationdata-verificationdatabase-tableseasy-to-understandreporting-toolschema-validationtesting-toolsyaml-configuration
942 stars 10.73 score 284 scriptsbioc
MsCoreUtils:Core Utils for Mass Spectrometry Data
MsCoreUtils defines low-level functions for mass spectrometry data and is independent of any high-level data structures. These functions include mass spectra processing functions (noise estimation, smoothing, binning, baseline estimation), quantitative aggregation functions (median polish, robust summarisation, ...), missing data imputation, data normalisation (quantiles, vsn, ...), misc helper functions, that are used across high-level data structure within the R for Mass Spectrometry packages.
Maintained by RforMassSpectrometry Package Maintainer. Last updated 8 days ago.
infrastructureproteomicsmassspectrometrymetabolomicsbioconductormass-spectrometryutils
16 stars 10.57 score 41 scripts 71 dependents
hope-data-science
tidyfst:Tidy Verbs for Fast Data Manipulation
A toolkit of tidy data manipulation verbs with 'data.table' as the backend. Combining the merits of syntax elegance from 'dplyr' and computing performance from 'data.table', 'tidyfst' intends to provide users with state-of-the-art data manipulation tools with least pain. This package is an extension of 'data.table'. While enjoying a tidy syntax, it also wraps combinations of efficient functions to facilitate frequently-used data operations.
Maintained by Tian-Yuan Huang. Last updated 6 months ago.
100 stars 10.06 score 118 scripts 4 dependents
brry
berryFunctions:Function Collection Related to Plotting and Hydrology
Draw horizontal histograms, color scattered points by 3rd dimension, enhance date- and log-axis plots, zoom in X11 graphics, trace errors and warnings, use the unit hydrograph in a linear storage cascade, convert lists to data.frames and arrays, fit multiple functions.
Maintained by Berry Boessenkool. Last updated 2 months ago.
13 stars 9.43 score 350 scripts 16 dependents
gdemin
maditr:Fast Data Aggregation, Modification, and Filtering with Pipes and 'data.table'
Provides pipe-style interface for 'data.table'. Package preserves all 'data.table' features without significant impact on performance. 'let' and 'take' functions are simplified interfaces for most common data manipulation tasks. For example, you can write 'take(mtcars, mean(mpg), by = am)' for aggregation or 'let(mtcars, hp_wt = hp/wt, hp_wt_mpg = hp_wt/mpg)' for modification. Use 'take_if/let_if' for conditional aggregation/modification. Additionally there are some conveniences such as automatic 'data.frame' conversion to 'data.table'.
Maintained by Gregory Demin. Last updated 5 months ago.
61 stars 8.98 score 248 scripts 7 dependents
wkumler
RaMS:R Access to Mass-Spec Data
R-based access to mass-spectrometry (MS) data. While many packages exist to process MS data, many of these make it difficult to access the underlying mass-to-charge ratio (m/z), intensity, and retention time of the files themselves. This package is designed to format MS data in a tidy fashion and allows the user perform the plotting and analysis.
Maintained by William Kumler. Last updated 6 months ago.
mass-spectrometry-datatidy-data
24 stars 8.78 score 84 scripts 5 dependents
patrickroocks
rPref:Database Preferences and Skyline Computation
Routines to select and visualize the maxima for a given strict partial order. This especially includes the computation of the Pareto frontier, also known as (Top-k) Skyline operator (see Börzsönyi, et al. (2001) <doi:10.1109/ICDE.2001.914855>), and some generalizations known as database preferences (see Kießling (2002) <doi:10.1016/B978-155860869-6/50035-4>).
Maintained by Patrick Roocks. Last updated 2 years ago.
2 stars 5.14 score 115 scripts 4 dependents
inzightvit
iNZightMR:Tools for Exploring Multiple Response Data
Interaction and analysis of multiple response data, along with other tools for analysing these types of data including missing value analysis and calculation of standard errors for a range of covariance matrix results (proportions, multinomial, independent samples, and multiple response).
Maintained by Tom Elliott. Last updated 11 months ago.
1 stars 3.78 score 3 scripts 2 dependents
cran
tis:Time Indexes and Time Indexed Series
Functions and S3 classes for time indexes and time indexed series, which are compatible with FAME frequencies.
Maintained by Brian Salzer. Last updated 4 years ago.
3.35 score 6 dependents
hughparsonage
heims:Decode and Validate HEIMS Data from Department of Education, Australia
Decode elements of the Australian Higher Education Information Management System (HEIMS) data for clarity and performance. HEIMS is the record system of the Department of Education, Australia to record enrolments and completions in Australia's higher education system, as well as a range of relevant information. For more information, including the source of the data dictionary, see <http://heimshelp.education.gov.au/sites/heimshelp/dictionary/pages/data-element-dictionary>.
Maintained by Hugh Parsonage. Last updated 7 years ago.
2.70 score 8 scripts