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BAINIDA
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Map as data visualization 犢犖犖 犖犖迦犖迦牽犖∇ 犖÷犖犖犖 犖ム犖犢犖ム鹸犖犖犖犖伍献 犖犖犖. 犖犖犖. 犖о犖. (Business analytics) 犖犖迦犖迦牽犖∇犖犖巌犖犖犢犖犖о鹸犖犖 Statistical graphic and data visualization 犖犖犖犢犖犖 犖犖迦犖迦牽犖∇ 犖犖. 犖犖迦犖犖犢 犖犖園犖犖巌犖о牽犖о鹸犖犖犢

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Data Visualization: Map Mr. Montree Lorlertsakul
Whats in a map?? 犖犖園硯犖犢犖 犖犖園犖犢犖о (Scale) 犖犖巌絹 犖犖園犖ム険犖犖犖犢 (Legend)
Data visualization. map
Type of data visualization. 1D/Linear 2D/Planar 3D/Volumetric Temporal nD/Multidimensional Tree/Hierarchical Network https://guides.library.duke.edu/datavis/vis_types
2D/Planar Choropleth Cartogram Dot distribution map Proportional symbol map Contour/isopleth/isarithmic map Dasymetric map Self-organizing map
2D/Planar Choropleth Cartogram Dot distribution map Proportional symbol map Contour/isopleth/isarithmic map Dasymetric map Self-organizing map
2D/Planar Choropleth Cartogram Dot distribution map Proportional symbol map Contour/isopleth/isarithmic map Dasymetric map Self-organizing map
2D/Planar Choropleth Cartogram Dot distribution map Proportional symbol map Contour/isopleth/isarithmic map Dasymetric map Self-organizing map
2D/Planar Choropleth Cartogram Dot distribution map Proportional symbol map Contour/isopleth/isarithmic map Dasymetric map Self-organizing map
2D/Planar Choropleth Cartogram Dot distribution map Proportional symbol map Contour/isopleth/isarithmic map Dasymetric map Self-organizing map
2D/Planar Choropleth Cartogram Dot distribution map Proportional symbol map Contour/isopleth/isarithmic map Dasymetric map Self-organizing map
2D/Planar Choropleth Cartogram Dot distribution map Proportional symbol map Contour/isopleth/isarithmic map Dasymetric map Self-organizing map
Type of data visualization. Noninteractive Interactive
Noninteractive map Package = ggmap Map <- get_map(location = c(lon = 100.54, lat = 13.76), zoom = 11.5, maptype = 'toner', source = "google")
Noninteractive map
Noninteractive map
Interactive map https://www.bloomberg.com/graphics/2016-election-results/
Interactive map
Spatial analysis Heatmap Vector Spatial Analysis (Buffers) Nearest Neighborhood Analysis Spatial Regression Analysis Etc.
Spatial analysis : Heatmap
Spatial analysis : Buffers https://docs.qgis.org/2.8/en/docs/gentle_gis_introduction/vector_spatial_analysis_buffers.html
Spatial analysis : Nearest Neighborhood Analysis http://www.qgistutorials.com/en/docs/nearest_neighbor_analysis.html
Spatial analysis : Spatial Regression Analysis 0.722 -3091.83 6225.66 6319.74 犖犖園硯犢犖犖犖犢犖 Coefficient Std.Error z-value Probability 犖犢犖о犖犢犖橿見犖犖園犖犖劇犖犖犖朽 0.418 0.0410112 10.185 0.000 犖犢犖橿犖犖犖朽 91.532 15.663 5.844 0.000 犖犖犖巌県犖園犖÷見犖橿犖 7.215 2.318 3.112 0.002 犢犖犖巌犢犖犖犖 2558 24.764 3.19883 7.741 0.000 犖犖橿犖о犖犖園犖* 17.427 1.57959 11.033 0.000 犖犖橿犖о犖犖犢犖о権犖犖橿権犖犖園犖犖犖÷* 9.570- 1.38599 -6.905 0.000 犖犖犖橿犖犖劇犖犖犖朽犢犖犖犖犖犖橿牽* 3.211 1.28915 2.491 0.013 犖犖橿犖о犖犢犖犖犖犖橿牽犖犖犖橿犖* 2.596- 1.70919 -1.519 0.129 犖犖橿犖橿犖犖萎犖÷鹸犖犖犖朽犖犖巌犢犖犖ム元犢犖* 2.591 1.40957 1.838 0.066 犢犖犖÷犖犖犖犢犖犖巌犖犖犖犢 9.375 2.71482 3.453 0.001 犢犖犖犖犖犖橿牽犖犖巌犢犖÷犖犢犖 12.852 6.8775 1.869 0.062 犖犖萎権犖萎見犢犖橿犖犖橿 BTS 7.638- 1.15808 -6.596 0.000 犖犖萎権犖萎見犢犖橿犖犖橿 MRT 4.668- 1.39518 -3.345 0.001 犖犖萎権犖萎見犢犖橿犖犖橿 ARL 1.676 1.87409 0.894 0.371 犖犖萎権犖萎見犢犖橿犖犖橿犖犖犖 4 犖犢犖犖犖犖犖橿犖 3.533- 2.37667 -1.486 0.137 犖犖萎権犖萎見犢犖橿犖犖橿犖犖犖 6 犖犢犖犖犖犖犖橿犖 1.017- 2.16949 -0.469 0.639 犖犖劇犖犖犖朽犢犖犖劇犖犖犖橿犖巌犖∇犖犖犖 (犖犖朽犖犖) 4.303- 5.31112 -0.810 0.418 犖犖劇犖犖犖朽犖犖∇弦犢犖犖橿絹犖園権犖犖犖橿犖犢犖犖÷験犖 (犖犖朽犢犖橿犖橿献) 1.080 5.05385 0.214 0.831 犖犖劇犖犖犖朽犖犖∇弦犢犖犖橿絹犖園権犖犖犖橿犖犢犖犖犖橿犖犖ム験犖 (犖犖朽肩 犢犖) 4.118- 4.6482 -0.886 0.376 犖犖園犖犖犖萎硯犖園犖犖犖犖犖犖犢犖÷犖犢犖橿犖 犢犖橿犖犖萎権犖 11.057 3.61682 3.057 0.002 犖犖劇犖犖犖朽犖犢犖橿犖÷犖犢犖о検 犖犖 2554 4.019- 2.8187 -1.426 0.154 犖犖о検犖犖園硯犢犖犖 19 * Standardized Schwarz criterion R-squared Log likelihood Akaike info criterion

More Related Content

Data visualization. map

  • 1. Data Visualization: Map Mr. Montree Lorlertsakul
  • 2. Whats in a map?? 犖犖園硯犖犢犖 犖犖園犖犢犖о (Scale) 犖犖巌絹 犖犖園犖ム険犖犖犖犢 (Legend)
  • 4. Type of data visualization. 1D/Linear 2D/Planar 3D/Volumetric Temporal nD/Multidimensional Tree/Hierarchical Network https://guides.library.duke.edu/datavis/vis_types
  • 5. 2D/Planar Choropleth Cartogram Dot distribution map Proportional symbol map Contour/isopleth/isarithmic map Dasymetric map Self-organizing map
  • 6. 2D/Planar Choropleth Cartogram Dot distribution map Proportional symbol map Contour/isopleth/isarithmic map Dasymetric map Self-organizing map
  • 7. 2D/Planar Choropleth Cartogram Dot distribution map Proportional symbol map Contour/isopleth/isarithmic map Dasymetric map Self-organizing map
  • 8. 2D/Planar Choropleth Cartogram Dot distribution map Proportional symbol map Contour/isopleth/isarithmic map Dasymetric map Self-organizing map
  • 9. 2D/Planar Choropleth Cartogram Dot distribution map Proportional symbol map Contour/isopleth/isarithmic map Dasymetric map Self-organizing map
  • 10. 2D/Planar Choropleth Cartogram Dot distribution map Proportional symbol map Contour/isopleth/isarithmic map Dasymetric map Self-organizing map
  • 11. 2D/Planar Choropleth Cartogram Dot distribution map Proportional symbol map Contour/isopleth/isarithmic map Dasymetric map Self-organizing map
  • 12. 2D/Planar Choropleth Cartogram Dot distribution map Proportional symbol map Contour/isopleth/isarithmic map Dasymetric map Self-organizing map
  • 13. Type of data visualization. Noninteractive Interactive
  • 14. Noninteractive map Package = ggmap Map <- get_map(location = c(lon = 100.54, lat = 13.76), zoom = 11.5, maptype = 'toner', source = "google")
  • 19. Spatial analysis Heatmap Vector Spatial Analysis (Buffers) Nearest Neighborhood Analysis Spatial Regression Analysis Etc.
  • 21. Spatial analysis : Buffers https://docs.qgis.org/2.8/en/docs/gentle_gis_introduction/vector_spatial_analysis_buffers.html
  • 22. Spatial analysis : Nearest Neighborhood Analysis http://www.qgistutorials.com/en/docs/nearest_neighbor_analysis.html
  • 23. Spatial analysis : Spatial Regression Analysis 0.722 -3091.83 6225.66 6319.74 犖犖園硯犢犖犖犖犢犖 Coefficient Std.Error z-value Probability 犖犢犖о犖犢犖橿見犖犖園犖犖劇犖犖犖朽 0.418 0.0410112 10.185 0.000 犖犢犖橿犖犖犖朽 91.532 15.663 5.844 0.000 犖犖犖巌県犖園犖÷見犖橿犖 7.215 2.318 3.112 0.002 犢犖犖巌犢犖犖犖 2558 24.764 3.19883 7.741 0.000 犖犖橿犖о犖犖園犖* 17.427 1.57959 11.033 0.000 犖犖橿犖о犖犖犢犖о権犖犖橿権犖犖園犖犖犖÷* 9.570- 1.38599 -6.905 0.000 犖犖犖橿犖犖劇犖犖犖朽犢犖犖犖犖犖橿牽* 3.211 1.28915 2.491 0.013 犖犖橿犖о犖犢犖犖犖犖橿牽犖犖犖橿犖* 2.596- 1.70919 -1.519 0.129 犖犖橿犖橿犖犖萎犖÷鹸犖犖犖朽犖犖巌犢犖犖ム元犢犖* 2.591 1.40957 1.838 0.066 犢犖犖÷犖犖犖犢犖犖巌犖犖犖犢 9.375 2.71482 3.453 0.001 犢犖犖犖犖犖橿牽犖犖巌犢犖÷犖犢犖 12.852 6.8775 1.869 0.062 犖犖萎権犖萎見犢犖橿犖犖橿 BTS 7.638- 1.15808 -6.596 0.000 犖犖萎権犖萎見犢犖橿犖犖橿 MRT 4.668- 1.39518 -3.345 0.001 犖犖萎権犖萎見犢犖橿犖犖橿 ARL 1.676 1.87409 0.894 0.371 犖犖萎権犖萎見犢犖橿犖犖橿犖犖犖 4 犖犢犖犖犖犖犖橿犖 3.533- 2.37667 -1.486 0.137 犖犖萎権犖萎見犢犖橿犖犖橿犖犖犖 6 犖犢犖犖犖犖犖橿犖 1.017- 2.16949 -0.469 0.639 犖犖劇犖犖犖朽犢犖犖劇犖犖犖橿犖巌犖∇犖犖犖 (犖犖朽犖犖) 4.303- 5.31112 -0.810 0.418 犖犖劇犖犖犖朽犖犖∇弦犢犖犖橿絹犖園権犖犖犖橿犖犢犖犖÷験犖 (犖犖朽犢犖橿犖橿献) 1.080 5.05385 0.214 0.831 犖犖劇犖犖犖朽犖犖∇弦犢犖犖橿絹犖園権犖犖犖橿犖犢犖犖犖橿犖犖ム験犖 (犖犖朽肩 犢犖) 4.118- 4.6482 -0.886 0.376 犖犖園犖犖犖萎硯犖園犖犖犖犖犖犖犢犖÷犖犢犖橿犖 犢犖橿犖犖萎権犖 11.057 3.61682 3.057 0.002 犖犖劇犖犖犖朽犖犢犖橿犖÷犖犢犖о検 犖犖 2554 4.019- 2.8187 -1.426 0.154 犖犖о検犖犖園硯犢犖犖 19 * Standardized Schwarz criterion R-squared Log likelihood Akaike info criterion

Editor's Notes

  1. Pandora -- This map from streaming website Pandora attempts to show thefavourite dance music tracksin each US state//top Pandora dance tracks by state http://brilliantmaps.com/air-pollution/ -- As the map above shows, China is home to many of the worldsmost pollutedcities. The map was created byAQICN, a Chinese website that tracks global air pollution stats.
  2. http://blog.visme.co/how-to-communicate-technical-information/ https://guides.library.duke.edu/datavis/vis_types https://sites.google.com/site/thematicmap2557/cartogram
  3. Choropleth:this is a map that has its areas of interest categorized in colors or patterns. Its goal is to offer an overall view of how a certain feature like population density is different from area to area. Read more at http://blog.visme.co/how-to-communicate-technical-information/#POhOS1DLfSOmU9LS.99
  4. Cartogram:this type of map substitutes land area or distance for certain variables. For example, the size of districts can be altered to show how many citizens there are in contrast with other districts Read more at http://blog.visme.co/how-to-communicate-technical-information/#POhOS1DLfSOmU9LS.99
  5. Dot Distribution Map:this map representation uses dots to signal the presence of certain factors within a certain area. One dot represents the location of the phenomenon that data recorded. Thus, it is convenient to observe the impact of a certain agent in an entire country Read more at http://blog.visme.co/how-to-communicate-technical-information/#POhOS1DLfSOmU9LS.99
  6. Dasymetric map
  7. Dasymetric map
  8. A self-organizing map showingU.S. Congressvoting patterns. The input data was a table with a row for each member of Congress, and columns for certain votes containing each member's yes/no/abstain vote. The SOM algorithm arranged these members in a two-dimensional grid placing similar members closer together.The first plotshows the grouping when the data are split into two clusters.The second plotshows average distance to neighbours: larger distances are darker.The third plotpredictsRepublican(red) orDemocratic(blue) party membership.The other plotseach overlay the resulting map with predicted values on an input dimension: red means a predicted 'yes' vote on that bill, blue means a 'no' vote. The plot was created inSynapse.
  9. https://guides.library.duke.edu/datavis/vis_types
  10. http://www.qgistutorials.com/en/docs/nearest_neighbor_analysis.html
  11. 犖犖迦牽犖о鹸犢犖犖犖迦鍵犖犢犖犖÷犖迦牽犖犖犖犖犖∇犖犖巌犖犖朽犖犖園犖 (Spatial Regression) 犖犖橿犖謹犖犖巌犖犖巌犖ム犖迦犖犖項検犖巌絹犖迦肩犖犖犢犖犖朽犢犖犢犖犖犖犖犖犖ム幻犖÷賢犖巌犖犖巌犖ム犖犖犖犖朽犖犖園犖