This node will visualize the given geometric elements using the matplotlib. It can be used to create Choropleth Maps by assigning a marker color column. The node further supports various settings to adapt the legend to your needs. For more information on the settings, please refer to the geopandas.GeoDataFrame.plot.
Select the geometry column to visualize.
Select line width column. The width is fixed by default. If a line width column is selected, the width will be scaled by the values of the column.
Select a unified line width, can be set to none.
Set the title of the figure.
Set the size of the figure title.
If checked, the axis will be set off.
Select the type of output image.
Group of settings that define the size of the geometric objects. The size column should be numerical. The size is fixed by default. If the 'Marker size column' is selected, the 'Marker size scale' option will be ignored, and size will be scaled by the values of the column. For point features, the size is the radius of the circle. For line features, the size is the width of the line. For polygon features, the size is the radius of the centroid of the polygon.
Select marker size column.
Select the size scale of the markers. If the Marker size column is selected, this option will be ignored. Noticed that the size scale only works for point features.
Group of settings that define the coloring of the geometric objects. The color column can be either nominal or numerical. If a numerical column is selected you might want to enable the classification of the numeric values to group them into bins prior to assigning a color to each bin using the color map information. If a nominal column is selected the color map will be used to assign a color to each unique value in the column. Noticed that if a nominal column is selected the classification settings will be ignored.
Select marker color column to be plotted. If numerical you might want to adapt the classification settings accordingly. If nominal the color map will be used to assign a color to each unique value in the column. Noticed that if a nominal column is selected the classification settings will be ignored. Select 'None' if you want a unified marker color.
Select marker color. It will assign a unified color for all features. If a 'Marker color column' is selected, this option will be ignored. Select none if you don't want to set a unified marker color.
Select the color map to use for the color column. See Colormaps in Matplotlib.
If checked, the numerical marker color column will be classified using the selected classification method. The 'Number of classes' will be used to determine the number of bins.
Select the classification method to use for the selected numerical marker color column.
Select the number of classes used by the classification method.
Set the edge color. See Colormaps in Matplotlib.
Group of settings that define if a color legend is shown on the map and if so how it should be formatted. The color legend is only shown if you have selected a color column. More details about the legend settings can be found matplotlib.pyplot.legend and matplotlib.pyplot.colorbar.
If checked, the color legend will be shown in the plot.
Set the caption for the legend. By default, the caption is the name of the selected color column or empty for heat map.
Set the font size for the legend caption.
If checked, the legend will be horizontally expanded to fill the axes area.
Select the location for the legend.
Select the number of columns for the legend.
Select the size for the legend.
Select the font size for the legend.
Select the label color for the legend.
If checked, a frame will be shown in the legend.
Select the transparent value for the legend frame.
Select the border pad for the legend.
Select the label spacing for the legend.
Select the shrinking value for the color bar legend. Only works for color bar.
Select the pad value for the color bar legend. Only works for color bar
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