An implementation of calls designed to collect and organize in an easy way the data from the Steam API specifically for the Counter-Strike Global Offensive Game (CS Go) <https://developer.valvesoftware.com/wiki/Steam_Web_API>.

Package for CShapes 2.0, a GIS dataset of country borders (1886-today). Includes functions for data extraction and the computation of distance matrices and -lists.

A collection of user-submitted functions to aid in the analysis of hydrological data, particularly for users in Canada. The functions focus on the use of Canadian data sets, and are suited to Canadian hydrology, such as the important cold region hydrological processes and will work with Canadian hydrological models. The functions are grouped into several themes, currently including Statistical hydrology, Basic data manipulations, Visualization, and Spatial hydrology. Functions developed by the Floodnet project are also included. CSHShydRology has been developed with the assistance of the Canadian Society for Hydrological Sciences (CSHS) which is an affiliated society of the Canadian Water Resources Association (CWRA). As of version 1.2.6, functions now fail gracefully when attempting to download data from a url which is unavailable.

Set of generalised tools for the flexible computation of climate 
  related indicators defined by the user. Each method represents a specific 
  mathematical approach which is combined with the possibility to select an 
  arbitrary time period to define the indicator. This enables a wide range of 
  possibilities to tailor the most suitable indicator for each particular climate 
  service application (agriculture, food security, energy, water management, ...). 
  This package is intended for sub-seasonal, seasonal and decadal climate 
  predictions, but its methods are also applicable to other time-scales, 
  provided the dimensional structure of the input is maintained. Additionally, 
  the outputs of the functions in this package are compatible with 'CSTools'. 
  This package is described in 'Pérez-Zanón et al. (2023) 
  <doi:10.1016/j.cliser.2023.100393>' and it was developed in the context of 
  'H2020 MED-GOLD' (776467) and 'S2S4E' (776787) projects. See 'Lledó et al. (2019) 
  <doi:10.1016/j.renene.2019.04.135>' and 'Chou et al., 2023 
  <doi:10.1016/j.cliser.2023.100345>' for details.