Soil Science Example

Input Data

The input data:

The input file looks like:
'8639-SAM',21,01-MAY-87,15,24.06,16.85,958.8,0.0,0.0,-6.61,4.52,.09,10.68,.4,22.56,24.43,16.58,37.69,43.44,-8.54,210.09,210.08,161.58,472.54,99.51,295.69,'GGGGGGGGGGGGGGGG*GGGC*** ',23-MAY-89,'CPI-MRG'
'8639-SAM',21,01-MAY-87,45,22.83,16.28,958.85,0.0,0.0,-6.11,3.94,.06,10.24,.38,20.8,24.04,16.58,16.29,-6.07,-9.23,210.09,210.08,65.85,196.59,39.0,116.72,'GGGGGGGGGGGGGGGG*GGGGGGG ',23-MAY-89,'CPI-MRG'


We are trying to find lots of rain before a clear day.


Click here to see our model of creating visualizations.

The visualization is created as follows:

  1. Define Window 0 showing the global picture: solar radiation versus date, quality of solar radiation versus date, rain versus date, and quality of solar radiation versus date.
  2. link the X axes of the views.
  3. Define Window 1 as a copy of Window 0. It shows a zoomed in view.
  4. Create a cursor to show the relationship between the Window 0 and Window 1.
  5. Navigate Window 1 to find areas where there are lots of rain before a clear day, using the top views are reference points.
  6. Windows 2, 3, 4 and 5 are windows that have been duplicated, showing possible places where there are lots of rain before a clear day.


Here is a close up of a different window. The top two views are global pictures of solar radiation and rain. The bottom two views are zoomed in pictures.
  1. This example shows need need to generate different views of the same data, and to keep track interesting places in the data.
  2. Seasonal variation in the solar radiation observed for the first view: high in the sumer, and low in the winter.
  3. Seasonal variation in the rain observed for the second view: high in the summer and spring.
  4. Daily variation in the solar radiation, shown in the third view: radiation is high around noon.
  5. Lots of rain before a clear day observed for the 3rd and fourth views.

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