When a spatial data set contains multiple values at a location (e.g., from different dates or depths/elevations), the number of data points at a location, and even the presence of multiple data points at a location, may not be apparent on a 2-D map. The latest version of MapData.py (https://pypi.org/project/mapdata/) addresses this situation in five ways:
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#Mapping #MapData #DataAnalysis #DataExploration #DataPlotting #Python #FOSS
1. The keystroke Alt-C ('count') will display the number of data values at a location, as a label on the map to the right of the location. This label is displayed only when there is more than one value at a location. An illustration is attached.
2. There are several sets of symbols that can be overplotted without overlapping, allowing data from multiple dimensions to be visualized at the same location. The attached illustration shows the use of the 'q1' through 'q4' symbols.
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3. The new menu option 'Table/Counts by location' displays a table of all unique latitude and longitude values and the number of data values at each location. If there are any text data columns in the data table for which the values have a one-to-one relationship to unique coordinate pairs, those columns will also be shown in the table. If you have a new data set and are trying to figure out whether there is any unique location identifier, this summary will give you the answer.
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4. The new menu option 'Selections/Co-located data' allows you to select data rows at locations that have more than one data row. Or more than any number, or less than any number, or exactly any number. Data rows selected in this way can replace existing selections or be combined with them by union, intersection, or difference.
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5. Right-clicking on a marked location will pop up a table showing all unique labels for that location, and the number of data values for each label.
There are a number of other new features in the latest version, including:
- Display of a 2x2 contingency table with tests of independence and conditional probabilities.
- Display of a Receiver Operating Characteristics curve and statistics.
- Mann-Kendall Trend Test in the bivariate statistics summary.
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- New plot types: total and means by category, and min-max by bins.
- Grouping of data for histograms, to produce stacked bars.
- Opacity adjustment and axis inversion for several plot types.
- Loading, editing, and saving of SQL script files from the data query dialog.
Complete documentation is at https://mapdata.readthedocs.io/
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RDN