Provides functions to access and retrieve metadata from the 'Finna' API <https://api.finna.fi/>, which aggregates content from Finnish archives, libraries, and museums.

Providing classes, methods, and functions to deal with financial networks. 
    Users can easily store information about both physical and legal persons by using pre-made classes that are studied for integration with scraping packages such as 'rvest' and 'RSelenium'.
    Moreover, the package assists in creating various types of financial networks depending on the type of relation between its units depending on the relation under scrutiny (ownership, board interlocks, etc.), the desired tie type (valued or binary), and renders them in the most common formats (adjacency matrix, incidence matrix, edge list, 'igraph', 'network').
    There are also ad-hoc functions for the Fiedler value, global network efficiency, and cascade-failure analysis.

R API client package for 'Fingrid Open Data' 
    <https://data.fingrid.fi/> on the electricity market and the power system. 
    get_data() function holds the main application logic to retrieve 
    time-series data. API calls require free user account registration.
    Data is made available by Fingrid Oyj and distributed under
    Creative Commons 4.0 <https://creativecommons.org/licenses/by/4.0/>.

Annotates Finnish textual survey responses into CoNLL-U format using Finnish treebanks from <https://universaldependencies.org/format.html> using UDPipe as described in Straka and Straková (2017) <doi:10.18653/v1/K17-3009>. Formatted data is then analysed using single or comparison n-gram plots, wordclouds, summary tables and Concept Network plots. The Concept Network plots use the TextRank algorithm as outlined in Mihalcea, Rada & Tarau, Paul (2004) <https://aclanthology.org/W04-3252/>.

Automated time series forecasting developed by Microsoft Finance. The Microsoft Finance Time 
    Series Forecasting Framework, aka Finn, can be used to forecast any component of the income 
    statement, balance sheet, or any other area of interest by finance. Any numerical quantity over time, 
    Finn can be used to forecast it. While it can be applied outside of the finance domain, Finn was built 
    to meet the needs of financial analysts to better forecast their businesses within a company, and has 
    a lot of built in features that are specific to the needs of financial forecasters. Happy forecasting!