ArcGIS-based Functions¶

Collection of all functions based on arcpy.

Generate and clip ID-raster

Import ID-raster to ID-array

Export pandas Series to raster

Export all rows of a DataFrame to rasters in a File-Geodatabase,

optionally calculating statistics rasters (mean, sum, max, …)

Import attribute table or dbf table to DataFrame

Join DataFrame columns to attribute table of a Feature Class

Extract values from rasters at point locations and the eight surrounding cells

Extract values from rasters to new fields in a Point Feature Class

Calculate zonal statistics and join to zone Feature Class

`raster_to_array`	Imports all values of a raster and converts them to one-dimensional array.
`create_idraster_germany`	Creates an ID raster in stereographic projection for the extended national RADOLAN grid (900 x 1100 km) or the national grid (900 x 900 km).
`clip_idraster`	Clips a raster to the extent of the clip feature.
`import_idarray_from_raster`	Imports all values of raster and converts them to one-dimensional array.
`create_idarray`	Creates an ID Array for a study area.
`export_to_raster`	Exports series to raster by inserting target values at their corresponding ID values in the ID raster.
`export_dfrows_to_gdb`	Exports all rows of a DataFrame to rasters in a File-Geodatabase.
`attribute_table_to_df`	Load data from dbf table into a pandas DataFrame for subsequent analysis.
`join_df_columns_to_attribute_table`	Join DataFrame columns to attribute table of a feature flass or Shapefile.
`idTable_nineGrid`	Gets the IDs of point locations from an ID raster and calculates the IDs of the eight surrounding cells for every point.
`idTable_to_valueTable`	Selects the values defined in an ID Table from a data Series.
`valueTable_nineGrid`	Selects the values of a nine cell grid around point locations.
`rastervalues_to_points`	Extract values from a list of rasters to new fields in a point Feature Class.
`zonalstatistics`	Calculate Zonal Statistics as Table, join output to copy of zone Feature Class and import resulting table into DataFrame.