Data & Analytics

R packages for data validation. Use for validating data quality and constraints.

R tidyr package for data tidying. Use for pivot_longer, pivot_wider, separate, unite, and handling missing values.

R stringr package for string manipulation. Use for pattern matching, extraction, replacement, and string operations.

R stringi package for string processing. Use for fast, consistent string manipulation with ICU library.

R reshape2 package for data reshaping. Use for melting and casting data between wide and long formats.

R purrr package for functional programming. Use for map, reduce, iteration, and list manipulation.

R lubridate package for date-time manipulation. Use for parsing, extracting, and arithmetic with dates and times.

R janitor package for data cleaning. Use for cleaning dirty data and creating tabulations.

R fuzzyjoin package for fuzzy matching joins. Use for joining tables by inexact matching on strings, numbers, or distances.

R dplyr package for data manipulation. Use for filter, select, mutate, summarize, group_by, joins, and data transformation.

R data.table package for fast data manipulation. Use for high-performance data operations with concise syntax.

R broom package for tidying model outputs. Use for converting statistical model results to tidy data frames.

R data manipulation with dplyr, data.table, tidyr. Use for filtering, selecting, mutating, grouping, summarizing, reshaping data frames.

R DataExplorer package for EDA. Use for automated exploratory data analysis and reporting.

R yaml package for YAML parsing. Use for reading/writing YAML configuration files.

R writexl package for writing Excel files. Use for creating .xlsx files without Java dependency.

R vroom package for fast reading of delimited files. Use for reading large CSV/TSV files with lazy loading.

R rio package for data import/export. Use for reading/writing any file format with a single function.

R readxl package for reading Excel files. Use for importing .xls and .xlsx files.

R readr package for reading rectangular data. Use for fast CSV, TSV, and fixed-width file reading.

R qs package for quick serialization of R objects. Use for fast saving/loading of any R object with high compression.

R jsonlite package for JSON parsing. Use for reading, writing, and converting JSON data.

R haven package for SPSS, Stata, SAS files. Use for reading/writing .sav, .dta, .sas7bdat files with labels.

R fst package for fast serialization of data frames. Use for ultra-fast reading/writing of data frames with compression.