Data visualization. map
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Map as data visualization โดย อาจารย์ มนตรี ล้อเลิศสกุล สถบ. สถม. วทม. (Business analytics) อาจารย์พิเศษในวิชา Statistical graphic and data visualization สอนโดย อาจารย์ ดร. อานนท์ ศักดิ์วรวิชญ์
Data visualization. map
- 1. Data Visualization: Map Mr. Montree Lorlertsakul
- 2. What’s in a map?? หัวข้อ สัดส่วน (Scale) ทิศ สัญลักษณ์ (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")
- 18. Interactive map
- 19. Spatial analysis • Heatmap • Vector Spatial Analysis (Buffers) • Nearest Neighborhood Analysis • Spatial Regression Analysis • Etc.
- 20. Spatial analysis : Heatmap
- 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 ตัวแปรต้น Coefficient Std.Error z-value Probability ถ่วงน้ำหนักพื้นที่ 0.418 0.0410112 10.185 0.000 ค่ำคงที่ 91.532 15.663 5.844 0.000 บริษัทมหำชน 7.215 2.318 3.112 0.002 เปิดในปี 2558 24.764 3.19883 7.741 0.000 จำนวนชั้น* 17.427 1.57959 11.033 0.000 จำนวนหน่วยขำยทั้งหมด* 9.570- 1.38599 -6.905 0.000 ขนำดพื้นที่โครงกำร* 3.211 1.28915 2.491 0.013 จำนวนช่องกำรจรำจร* 2.596- 1.70919 -1.519 0.129 รำคำประเมินที่ดินเฉลี่ย* 2.591 1.40957 1.838 0.066 แถมเฟอร์นิเจอร์ 9.375 2.71482 3.453 0.001 โครงกำรติดแม่น้ำ 12.852 6.8775 1.869 0.062 ระยะห่ำงจำก BTS 7.638- 1.15808 -6.596 0.000 ระยะห่ำงจำก MRT 4.668- 1.39518 -3.345 0.001 ระยะห่ำงจำก ARL 1.676 1.87409 0.894 0.371 ระยะห่ำงจำกถนน 4 ช่องจรำจร 3.533- 2.37667 -1.486 0.137 ระยะห่ำงจำกถนน 6 ช่องจรำจร 1.017- 2.16949 -0.469 0.639 พื้นที่เพื่อพำณิชยกรรม (สีแดง) 4.303- 5.31112 -0.810 0.418 พื้นที่อยู่อำศัยหนำแน่นมำก (สีน้ำตำล) 1.080 5.05385 0.214 0.831 พื้นที่อยู่อำศัยหนำแน่นปำนกลำง (สีส ้ม) 4.118- 4.6482 -0.886 0.376 ฝั่งตะวันออกของแม่น้ำเจ ้ำพระยำ 11.057 3.61682 3.057 0.002 พื้นที่น้ำไม่ท่วม ปี 2554 4.019- 2.8187 -1.426 0.154 รวมตัวแปร 19 * Standardized Schwarz criterion R-squared Log likelihood Akaike info criterion
Editor's Notes
- #4: Pandora -- This map from streaming website Pandora attempts to show the favourite dance music tracks in 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 world’s most polluted cities. The map was created by AQICN, a Chinese website that tracks global air pollution stats.
- #5: http://blog.visme.co/how-to-communicate-technical-information/ https://guides.library.duke.edu/datavis/vis_types https://sites.google.com/site/thematicmap2557/cartogram
- #7: 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
- #8: 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
- #9: 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
- #11: Dasymetric map
- #12: Dasymetric map
- #13: A self-organizing map showing U.S. Congress voting 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 plot shows the grouping when the data are split into two clusters. The second plot shows average distance to neighbours: larger distances are darker. The third plot predicts Republican (red) or Democratic (blue) party membership. The other plots each 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 in Synapse.
- #14: https://guides.library.duke.edu/datavis/vis_types
- #20: http://www.qgistutorials.com/en/docs/nearest_neighbor_analysis.html
- #24: การวิเคราะห์สมการถดถอยเชิงที่ตั้ง (Spatial Regression) คำนึงอิทธิพลทางภูมิศาสตร์ที่ได้ครอบคลุมอิทธิพลของที่ตั้ง