The following tables list properties of teradataml GeoDataFrame. For more details and examples, see Teradata Package for Python Function Reference.
Generic Usage
from teradataml import GeoDataFrame
geodf = GeoDataFrame("sample_shapes")
geodf.name_of_the_property
Properties inherited from teradataml DataFrame
| Property | Purpose | Return | Example |
|---|---|---|---|
| columns | Get the column names of GeoDataFrame. | List containing column names | >>> load_example_data("geodataframe","sample_streets")
>>> df = GeoDataFrame.from_table('sample_streets')
>>> df.columns
|
| dtypes | Return a MetaData containing the column names and types. | MetaData containing the column names and Python types | >>> load_example_data("geodataframe","sample_streets")
>>> df = GeoDataFrame.from_table('sample_streets')
>>> df.dtypes
|
| iloc | Access a group of rows and columns by integer values or a boolean array. | teradataml GeoDataFrame | >>> load_example_data("geodataframe","sample_streets")
>>> geo_dataframe = GeoDataFrame.from_table('sample_streets')
>>> geo_dataframe = geo_dataframe.select(['skey', 'points', 'linestrings'])>>> geo_dataframe.iloc[1]>>> geo_dataframe.iloc[[1, 2]]>>> geo_dataframe.iloc[5, 1]
>>> geo_dataframe.iloc[(5, 1)]
>>> geo_dataframe.iloc[1:5, 2]
>>> geo_dataframe.iloc[1:5, 0:2]
>>> geo_dataframe.iloc[:, :]
>>> geo_dataframe.iloc[[0, 1, 2], [True, False, True]]
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| index | Return the index_label of the teradataml GeoDataFrame. | str or List of Strings (str) representing the index_label of the GeoDataFrame | >>> load_example_data("geodataframe","sample_cities")
>>> df = GeoDataFrame("sample_cities")
>>> df.index
>>> df = df.set_index(['city_shape', 'city_name'])
>>> df
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| loc | Access a group of rows and columns by labels or a boolean array. | teradataml GeoDataFrame | >>> load_example_data("geodataframe", ["sample_shapes"])
>>> geo_dataframe = GeoDataFrame("sample_shapes")
>>> geo_dataframe = geo_dataframe.select(['skey', 'linestrings', 'polygons'])
>>> geo_dataframe.loc[1004]
>>> geo_dataframe.loc[[1004, 1010]]
>>> geo_dataframe.loc[1004, 'linestrings']
>>> geo_dataframe.loc[(1004, 'linestrings')]
>>> geo_dataframe.loc[1001:1004, 'skey':'linestrings']
>>> geo_dataframe.loc[:, :]
>>> geo_dataframe.loc[geo_dataframe['skey'] > 1005]
>>> geo_dataframe.loc[geo_dataframe['skey'] > 1005, ['skey', 'linestrings']]
>>> geo_dataframe.loc[geo_dataframe['skey'] == 1005, 'skey':'polygons']
>>> geo_dataframe.loc[geo_dataframe['skey'] == 1005, [True, False, True]]
|
| Get the underlying object name on which GeoDataFrame is created. | Str representing the object name of GeoDataframe. | >>> load_example_data("geodataframe","sample_streets")
>>> df = GeoDataFrame('sample_streets')
>>> df.db_object_name
|
|
| shape | Return a tuple representing the dimensionality of the GeoDataFrame. | Tuple representing the dimensionality of this GeoDataFrame. | >>> load_example_data("geodataframe","sample_streets")
>>> df = GeoDataFrame('sample_streets')
>>> df.shape
|
| size | Return a value representing the number of elements in the GeoDataFrame. | Value representing the number of elements in the GeoDataFrame. | >>> load_example_data("geodataframe","sample_streets")
>>> df = GeoDataFrame('sample_streets')
>>> df.size
|
| tdtypes | Get the teradataml GeoDataFrame metadata containing column names and corresponding teradatasqlalchemy types. | Metadata containing the column names and Teradata types | >>> load_example_data("geodataframe","sample_streets")
>>> df = GeoDataFrame('sample_streets')
>>> df.tdtypes
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Properties specific to Geospatial Data (All Geometry Types)
| Property | Purpose | Return | Example |
|---|---|---|---|
| geometry | Return a GeoColumnExpression for a column containing geometry data. This property is used to run any geospatial operation on GeoDataFrame, that is, any geospatial function ran on the geometry column referenced by this property.
|
teradataml GeoDataFrameColumn | >>> load_example_data("geodataframe", ["sample_cities", "sample_streets"])
>>> cities = GeoDataFrame("sample_cities")
>>> streets = GeoDataFrame("sample_streets")
>>> city_streets = cities.join(streets, how="cross", lsuffix="l", rsuffix="r")
>>> city_streets.geometry.name
>>> city_streets.geometry = city_streets.street_shape
>>> city_streets.geometry.name
>>> geom_type = city_streets.geometry.geom_type
>>> is_simple = city_streets.geometry.is_simple
>>> is_valid = city_streets.geometry.is_valid
|
| boundary | Return the boundary of the Geometry value. | GeoDataFrame with result column containing Geometry values | >>> gdf = GeoDataFrame("sample_shapes")
>>> gdf = gdf.select(["skey", "polygons", "linestrings"])
>>> print(gdf.geometry.name)
>>> gdf.boundary
|
| centroid | Return the mathematical centroid of an ST_Polygon or ST_MultiPolygon value. | GeoDataFrame with result column containing Geometry values | >>> gdf = GeoDataFrame("sample_shapes")
>>> gdf = gdf.select(["skey", "polygons", "linestrings"])[gdf.skey.isin([1001, 1002, 1003])]
>>> print(gdf.geometry.name)
>>> gdf.centroid
|
| convex_hull | Return the convex hull of the Geometry value. | GeoDataFrame with result column containing Geometry values | >>> gdf = GeoDataFrame("sample_shapes")
>>> gdf = gdf.select(["skey", "polygons", "linestrings"])
>>> print(gdf.geometry.name)
>>> gdf.convex_hull
|
| coord_dim | Return the coordinate dimension of a geometry. | GeoDataFrame Resultant column contains:
|
>>> gdf = GeoDataFrame("sample_shapes")
>>> gdf = gdf.select(["skey", "polygons", "linestrings"])
>>> print(gdf.geometry.name)
>>> gdf.coord_dim
|
| dimension | Return the dimension of the Geometry type. | GeoDataFrame Resultant column contains:
|
>>> gdf = GeoDataFrame("sample_shapes")
>>> gdf = gdf.select(["skey", "polygons", "linestrings"])
>>> print(gdf.geometry.name)
>>> gdf.dimension
|
| geom_type | Return the Geometry type of the Geometry value. | GeoDataFrame Resultant column contains any of the following strings:
|
>>> gdf = GeoDataFrame("sample_shapes")
>>> gdf = gdf.select(["skey", "polygons", "linestrings"])
>>> print(gdf.geometry.name)
>>> gdf.geom_type
|
| is_3D | Test if a Geometry value has Z coordinate value. | GeoDataFrame Resultant column contains:
|
>>> gdf = GeoDataFrame("sample_shapes")
>>> gdf = gdf.select(["skey", "polygons", "linestrings"])
>>> print(gdf.geometry.name)
>>> gdf.is_3D
|
| is_empty | Test if a Geometry value corresponds to the empty set. | GeoDataFrame Resultant column contains:
|
>>> gdf = GeoDataFrame("sample_shapes")
>>> gdf = gdf.select(["skey", "polygons", "linestrings"])
>>> print(gdf.geometry.name)
>>> gdf.is_empty
|
| is_simple | Test if a Geometry value has no anomalous geometric points, such as self intersection tangency. | GeoDataFrame Resultant column contains:
|
>>> gdf = GeoDataFrame("sample_shapes")
>>> gdf = gdf.select(["skey", "polygons", "linestrings"])
>>> print(gdf.geometry.name)
>>> gdf.is_simple
|
| is_valid | Test if a Geometry value is well-formed. | GeoDataFrame Resultant column contains:
|
>>> gdf = GeoDataFrame("sample_shapes")
>>> gdf = gdf.select(["skey", "polygons", "linestrings"])
>>> print(gdf.geometry.name)
>>> gdf.is_valid
|
| max_x | Return the maximum X coordinate of a Geometry value. | GeoDataFrame Resultant column contains a NULL, if the Geometry is an empty set. |
>>> gdf = GeoDataFrame("sample_shapes")
>>> gdf = gdf.select(["skey", "polygons", "linestrings"])
>>> print(gdf.geometry.name)
>>> gdf.max_x
|
| max_y | Return the maximum Y coordinate of a Geometry value. | GeoDataFrame Resultant column contains a NULL, if the Geometry is an empty set. |
>>> gdf = GeoDataFrame("sample_shapes")
>>> gdf = gdf.select(["skey", "polygons", "linestrings"])
>>> print(gdf.geometry.name)
>>> gdf.max_y
|
| max_z | Return the maximum Z coordinate of a Geometry value. | GeoDataFrame Resultant column contains a NULL, if the Geometry is an empty set. |
>>> gdf = GeoDataFrame("sample_shapes")
>>> gdf = gdf.select(["skey", "polygons", "linestrings"])
>>> print(gdf.geometry.name)
>>> gdf.max_z
|
| min_x | Return the minimum X coordinate of a Geometry value. | GeoDataFrame Resultant column contains a NULL, if the Geometry is an empty set. |
>>> gdf = GeoDataFrame("sample_shapes")
>>> gdf = gdf.select(["skey", "polygons", "linestrings"])
>>> print(gdf.geometry.name)
>>> gdf.min_x
|
| min_y | Return the minimum Y coordinate of a Geometry value. | GeoDataFrame Resultant column contains a NULL, if the Geometry is an empty set. |
>>> gdf = GeoDataFrame("sample_shapes")
>>> gdf = gdf.select(["skey", "polygons", "linestrings"])
>>> print(gdf.geometry.name)
>>> gdf.min_y
|
| min_z | Return the minimum Z coordinate of a Geometry value. | GeoDataFrame Resultant column contains a NULL, if the Geometry is an empty set. |
>>> gdf = GeoDataFrame("sample_shapes")
>>> gdf = gdf.select(["skey", "polygons", "linestrings"])
>>> print(gdf.geometry.name)
>>> gdf.min_z
|
| srid | Get the spatial reference system identifier of the Geometry value. | GeoDataFrame | >>> gdf = GeoDataFrame("sample_shapes")
>>> gdf = gdf.select(["skey", "polygons", "linestrings"])
>>> print(gdf.geometry.name)
>>> gdf.srid
|
Properties for Point Geometry
| Property | Purpose | Return | Example |
|---|---|---|---|
| x | Get the X coordinate of an ST_Point value. | GeoDataFrame | >>> gdf = GeoDataFrame("sample_shapes")
>>> gdf = gdf.select(["skey", "points", "linestrings"])[gdf.points.geom_type == "ST_Point"]
>>> print(gdf.geometry.name)
>>> gdf.x
|
| y | Get the Y coordinate of an ST_Point value. | GeoDataFrame | >>> gdf = GeoDataFrame("sample_shapes")
>>> gdf = gdf.select(["skey", "points", "linestrings"])[gdf.points.geom_type == "ST_Point"]
>>> print(gdf.geometry.name)
>>> gdf.y
|
| z | Get the Z coordinate of an ST_Point value. | GeoDataFrame | >>> gdf = GeoDataFrame("sample_shapes")
>>> gdf = gdf.select(["skey", "points", "linestrings"])[gdf.points.geom_type == "ST_Point"]
>>> print(gdf.geometry.name)
>>> gdf.z
|
Properties for LineString Geometry
| Property | Purpose | Return | Example |
|---|---|---|---|
| is_closed_3D | Test whether a 3D LineString or 3D MultiLineString is closed, taking into account the Z coordinates in the calculation. | GeoDataFrame Resultant column contains:
|
>>> gdf = GeoDataFrame("sample_shapes")
>>> gdf = gdf.select(["skey", "polygons", "linestrings"])[gdf.linestrings.is_3D == 1]
>>> print(gdf.geometry.name)
>>> gdf.geometry = gdf.linestrings
>>> gdf.is_closed_3D
|
| is_closed | Test if a Geometry type that represents an ST_LineString, GeoSequence, or ST_MultiLineString value is closed. | GeoDataFrame Resultant column contains:
|
>>> gdf = GeoDataFrame("sample_shapes")
>>> gdf = gdf.select(["skey", "polygons", "linestrings"])[gdf.skey.isin([1001, 1002, 1003])]
>>> print(gdf.geometry.name)
>>> gdf.geometry = gdf.linestrings
>>> gdf.is_closed
|
| is_ring | Test if a Geometry type that represents an ST_LineString or a GeoSequence value is a ring. | GeoDataFrame Resultant column contains:
|
>>> gdf = GeoDataFrame("sample_shapes")
>>> gdf = gdf.select(["skey", "polygons", "linestrings"])[~gdf.skey.isin([1009, 1008, 1010, 1007])]
>>> print(gdf.geometry.name)
>>> gdf.geometry = gdf.linestrings
>>> gdf.is_ring
|
Properties for Polygon Geometry
| Property | Purpose | Return | Example |
|---|---|---|---|
| area | Return the area measurement of an ST_Polygon or ST_MultiPolygon. For ST_MultiPolygon, returns the sum of the area measurements of the component polygons. | GeoDataFrame | >>> gdf = GeoDataFrame("sample_shapes")
>>> gdf = gdf.select(["skey", "polygons", "linestrings"])
>>> print(gdf.geometry.name)
>>> gdf.area
|
| exterior | Get the exterior ring of a Geometry type that represents an ST_Polygon value. | GeoDataFrame with result column containing ST_LineString Geometry values | >>> gdf = GeoDataFrame("sample_shapes")
>>> gdf = gdf.select(["skey", "polygons", "linestrings"])[gdf.skey.isin([1001, 1002, 1003])]
>>> print(gdf.geometry.name)
>>> gdf.exterior
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| perimeter | Return the boundary length of an ST_Polygon, or the sum of the boundary lengths of the component polygons of an ST_MultiPolygon. | GeoDataFrame | >>> gdf = GeoDataFrame("sample_shapes")
>>> gdf = gdf.select(["skey", "polygons", "linestrings"])
>>> print(gdf.geometry.name)
>>> gdf.perimeter
|