R Wrapper for the 'OneMap.Sg API'

An R wrapper for the 'OneMap.Sg' API < https://www.onemap.gov.sg/docs/>. Functions help users query data from the API and return raw JSON data in "tidy" formats. Support is also available for users to retrieve data from multiple API calls and integrate results into single dataframes, without needing to clean and merge the data themselves. This package is best suited for users who would like to perform analyses with Singapore's spatial data without having to perform excessive data cleaning.

Text Analysis for All

An R 'shiny' app designed for diverse text analysis tasks, offering a wide range of methodologies tailored to Natural Language Processing (NLP) needs. It is a versatile, general-purpose tool for analyzing textual data. 'tall' features a comprehensive workflow, including data cleaning, preprocessing, statistical analysis, and visualization, all integrated for effective text analysis.

'Geocoordinate Validation Service'

The 'Geocoordinate Validation Service' (GVS) runs checks of coordinates in latitude/longitude format. It returns annotated coordinates with additional flags and metadata that can be used in data cleaning. Additionally, the package has functions related to attribution and metadata information. More information can be found at < https://github.com/ojalaquellueva/gvs/tree/master/api>.

Sites, Population, and Records Cleaning Skills

Data cleaning including 1) generating datasets for time-series and case-crossover analyses based on raw hospital records, 2) linking individuals to an areal map, 3) picking out cases living within a buffer of certain size surrounding a site, etc. For more information, please refer to Zhang W,etc. (2018) .

GIS Integration

Designed to facilitate the preprocessing and linking of GIS (Geographic Information System) databases < https://www.sciencedirect.com/topics/computer-science/gis-database>, the R package 'GISINTEGRATION' offers a robust solution for efficiently preparing GIS data for advanced spatial analyses. This package excels in simplifying intrica procedures like data cleaning, normalization, and format conversion, ensuring that the data are optimally primed for precise and thorough analysis.

Tidy Messy Data

Tools to help to create tidy data, where each column is a variable, each row is an observation, and each cell contains a single value. 'tidyr' contains tools for changing the shape (pivoting) and hierarchy (nesting and 'unnesting') of a dataset, turning deeply nested lists into rectangular data frames ('rectangling'), and extracting values out of string columns. It also includes tools for working with missing values (both implicit and explicit).

Client for 'GenderAPI.io'

Provides an interface to the 'GenderAPI.io' web service (< https://www.genderapi.io>) for determining gender from personal names, email addresses, or social media usernames. Functions are available to submit single or batch queries and retrieve additional information such as accuracy scores and country-specific gender predictions. This package simplifies integration of 'GenderAPI.io' into R workflows for data cleaning, user profiling, and analytics tasks.

Simple Data Frames

Provides a 'tbl_df' class (the 'tibble') with stricter checking and better formatting than the traditional data frame.

Tools for Accessing the Botanical Information and Ecology Network Database

Provides Tools for Accessing the Botanical Information and Ecology Network Database. The BIEN database contains cleaned and standardized botanical data including occurrence, trait, plot and taxonomic data (See < https://bien.nceas.ucsb.edu/bien/> for more Information). This package provides functions that query the BIEN database by constructing and executing optimized SQL queries.

Economics and Pricing Tools

Functions to aid in micro and macro economic analysis and handling of price and currency data. Includes extraction of relevant inflation and exchange rate data from World Bank API, data cleaning/parsing, and standardisation. Inflation adjustment calculations as found in Principles of Macroeconomics by Gregory Mankiw et al (2014). Current and historical end of day exchange rates for 171 currencies from the European Central Bank Statistical Data Warehouse (2020) < https://sdw.ecb.europa.eu/curConverter.do>.