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]] |
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 |
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 |
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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 |
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.
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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:
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>>> 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:
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>>> 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:
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>>> 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:
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>>> 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:
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>>> 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:
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>>> 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:
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>>> 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 |
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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 |
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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:
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>>> 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:
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>>> 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:
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>>> 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 |
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 |