Cartographic Map Abstraction Using R Programming (Literacy Rate, HDI and Poverty Data Interpolation of Nepal)
Abstract
R programming with map data interaction is another research area for data scientists due to high data publication in modern electronic records web applications at the federal administrative structure of Nepal. However the analysis of map and its presentation on web with interactively with data interperation has not much concern with data scientist while website design around the world. The data like central, province, local administrative government bodies many times published data for civil concerned. The dynamic records presentation with local boundaries map having interactive facilities has a new concept using r programming. Here the researcher could easily have developed the local administrative map using GIS shapefile then local level records generally gathered and stored in ms excel will automatically be integrated with this template easily so that local administrative agencies will easily update web site using r programming i.e rpubs. Which discards the registration domain, and knowledge of web application design intelligent site. The best application of this type of data interactive map with data interoperation would be highly applicable to local governance of Nepal where there was a large type of data and records that were developed in sequential order for public concern. The interactive VDC, district, province data commonly highlights data like, education rates and HDI information of any location that could easily be published. The developed model is available (http://rpubs.com/yagyarimal/556607) with interactive website pages quickly utilizing the intelligent markdown with a flash dashboard design template structure.
References
Acharya, K. K. (2018). Local Governance Restructuring in Nepal: From. Dhaulagiri Journal of Sociology and Anthropology Vol. 12, 2018 PP 37.
Chetri, T. B. (2017). Federal Democratic Republic Nepal:.
Dodge, M. (2008). Understanding Cyberspace Cartographies:. A thesis submitted for the degree of Doctor of Philosophy.
DUTTON, R. W. (2017). Generalising spatial data and dealing with multiple. 125.
Feenstra, R. C. (2015). The Next Generation of the Penn World Table. University of California, Davis and NBER, 3.
Gajdoš, V. U. (2019). Hierarchical Hexagonal Clustering and Indexing. Research Gate.
Government, N. A. (2017). Diagnostic Study of Local Governance in The Asia Foundation. Diagnostic Study of Local Governance in Federal Nepal was implemented with support.
Kennelly, J. S. (2010). Illuminated Choropleth Maps. Annals of the American Association of Geographers 100(3):513-534, Reserch Gate.
Narayan, D. (1999). Can Anyone Hear Us ?Voices From 47 Countries. Poverty Group, PREM World Bank, December 1999.
Nation, U. (2009). HANDBOOK ON GEOSPATIAL INFRASTRUCTURE .
Nepal, N. (2017). DraftNepal’s Sustainable Development Goals Baseline ReportJune2017. National Planning Commission,Government of Nepal.
Nepal, U. (2019). Human Development Index and its components. Human Development Report.
Ozgur, C. (2017). MatLab vs. Python vs. R. Journal of data science: JDS 15(3):355-372.
Paradis, E. (2005). R for Beginners. Emmanuel Paradis (12th September 2005).
Rhind, D. (1988). Personality as a factor in the development of a discipline: the example of computer- assisted cartography," American Cartographer 15:277-90. . Examines the history of the digital revolution in cartography and the effect of key personalit.
Tomlinson, R. (1988). The impact of the transition from analogue to digital cartographic representation. American Cartographer 15:249-62. An overview from a pioneer of GIS. .
Tremblay, K. (2017). ASSESSMENT OF HIGHER EDUCATION. OECD.
UNDP. (2018). Human Development Indices and Indicators: 2018 Statistical Update. 1.
Zavadskyy, V. (2017). The goal of ggvis is to make it easy to describe interactive web graphics in R. https://gist.github.com/VladislavZavadskyy/e31ab07b03a5c22b11982c49669a400b.
.png)
