HERE Map Content(HMC) is a global and use-case agnostic Platform Data API catalog. It publishes HERE map data for Location Service development purposes. The catalog enables users to selectively consume features and attributes of interest for their use-case and select updated partitions only when getting the latest map data from the HERE Platform.
For more details: https://docs.here.com/intro-to-mapping-concepts/docs/mapping-concepts-intro
Content bindings provide access to content exposed in a layer(s). Bindings can be based on one of the existing layers, or based on a group of more layers.
Goal of content bindings is to provide a uniform way for final users to access a variety of complex data models, in a python-friendly way.
PySDK also supports below HMC bindings based on multiple layers.
Administrative boundary for a segment
Environmental zones for a segment
Speed limit from navigation and advanced navigation attributes layers
Street name for a segment
Binding have the following high-level API:
get gives all the objects for one or more partitions
get_ref gives a single object
get_referencing gives all the objects based on reference given
Please note get_ref or get_referencing works only if object_type() have RefType.
Python
from here.platform import Platform
from here.geopandas_adapter import GeoPandasAdapter
from here.content.hmc2 import HMC
import pandas as pd
from here.platform.adapter import make_ref
from IPython.display import display, FileLink
platform = Platform()
hmc = HMC(platform, adapter=GeoPandasAdapter())
display(f"Catalog Id: {hmc.content.catalog_hrn} , Version:{hmc.content.version}")
'Catalog Id: hrn:here:data::olp-here:rib-2 , Version:8747'
Python
def types_to_df(types):
def to_record(kv):
k, v = kv
return {
"Type": k,
"Data Class": '.'.join([v.__module__, v.__qualname__]),
"Index by partition": v.indexer.partition is not None,
"Index by ID": v.indexer.identifier is not None,
"Ref Types": ", ".join(v.indexer.refs.keys()) or None
}
return pd.DataFrame.from_records(map(to_record, types.items()), index="Type")
Warning: Before running below cells please make sure you add your API key. Please use API Id as API key.
Python
## Install HERE Map Widget for Jupyter. This is needed for using Here Maps
#!pip install here-map-widget-for-jupyter
Python
# Functions needed for using Here Maps
from ipyleaflet import GeoData
import here.geotiles.heretile as ht
from ipyleaflet import Map
import geopandas as gpd
from shapely.geometry.polygon import Polygon
import os
# replace your API key here.
api_key = os.environ["LS_API_KEY"]
def plot_geometry(dataFrame, geo_column):
geoDF = gpd.GeoDataFrame(dataFrame[dataFrame['location.geometry'] != None][[geo_column]].copy(),
geometry=geo_column)
center_point = geoDF[geo_column].centroid.head(1).values
geoData = GeoData(geo_dataframe=geoDF,
style={"strokeColor": "rgba(128,0,128,1)"},
hover_style={"strokeColor": "rgba(255,0,0,1)"},
name='geometry_layer')
m = Map(
api_key=api_key,
center=[center_point.y[0], center_point.x[0]],
zoom=12,
)
m.add_layer(geoData)
return m
def plot_here_tiles(tile_ids):
tiles = [Polygon(ht.get_boundary_ring(t)) for t in tile_ids]
tiles_df = pd.DataFrame(tiles, columns=["geometry"])
geoDF = gpd.GeoDataFrame(tiles_df, geometry='geometry')
center_point = geoDF['geometry'].centroid.head(1).values
geoData = GeoData(geo_dataframe=geoDF, style={"strokeColor": "rgba(128,0,128,1)"},
hover_style={"strokeColor": "rgba(255,0,0,1)"},
name='here_tiles')
m = Map(
api_key=api_key,
center=[center_point.y[0], center_point.x[0]],
zoom=12,
)
m.add_layer(geoData)
return m
def plot_multiple_geometry(geometries):
geoData_1 = GeoData(geo_dataframe=geometries['Nodes'],
style={"strokeColor": "rgba(128,0,128,1)"},
hover_style={"strokeColor": "rgba(255,0,0,1)"},
name='geometry_layer_1')
geoData_2 = GeoData(geo_dataframe=geometries['Segments'],
style={"strokeColor": "rgba(128,0,128,1)"},
hover_style={"strokeColor": "rgba(255,0,0,1)"},
name='geometry_layer_2')
center_point = (geometries['Nodes'].set_crs(epsg=4328, allow_override=True)).centroid.head(1).values
m = Map(
api_key=api_key,
center=[center_point.y[0], center_point.x[0]],
zoom=12,
)
m.add_layer(geoData_1)
m.add_layer(geoData_2)
return m
Layer Id - street-names
Python
tiles = ['23671200-25332448-25332461', '1469256839-1469256831']
Python
street_names = hmc.street_names
types_to_df(street_names.object_types())
Data Class
Index by partition
Index by ID
Ref Types
Type
street
here.content.hmc2.street_names.StreetName
True
True
None
context
here.content.hmc2.place_context.PlaceContext
False
False
None
street_section
here.content.hmc2.street_names.StreetSection
True
True
None
Python
df = street_names.get(tiles, 'street')
df.head(2)
street_name
partition_id
street_id
23671200-25332448-25332461
here:af:street:-BY1y-M9YIMPVcYWPMnljD
[{'full_name': {'value': 'Pueblito', 'language...
here:af:street:-u0Lsl1fU5PvURIYcAG1lC
[{'full_name': {'value': 'Playa Nanzal', 'lang...
Python
df = street_names.get(tiles, 'context')
df.head(2)
classification_type
city
postal_code
country
state
region
county
district
sub_district
further_zone
default_mapping
political_view
political_view_exception
0
DISTRICT
[{'preference': 'PRIMARY', 'place_ref': {'part...
<NA>
[{'preference': 'PRIMARY', 'place_ref': {'part...
[{'preference': 'PRIMARY', 'place_ref': {'part...
<NA>
[{'preference': 'PRIMARY', 'place_ref': {'part...
[{'preference': 'ALTERNATIVE', 'place_ref': {'...
<NA>
<NA>
0
<NA>
<NA>
1
DISTRICT
[{'preference': 'PRIMARY', 'place_ref': {'part...
<NA>
[{'preference': 'PRIMARY', 'place_ref': {'part...
[{'preference': 'PRIMARY', 'place_ref': {'part...
<NA>
[{'preference': 'PRIMARY', 'place_ref': {'part...
[{'preference': 'ALTERNATIVE', 'place_ref': {'...
<NA>
<NA>
0
<NA>
<NA>
Python
df = street_names.get(tiles, 'street_section')
df.head(2)
street_index
administrative_context_index
associated_street_section_index
government_code
partition_id
streetsection_id
23671200-25332448-25332461
here:af:streetsection:-2OIuTs2s5HVoHz.Z2SI0B
55
57
[67, 103, 177, 214]
here:af:streetsection:-4x.rC.hY5jLe.Rm56mkED
25
64
[82]
Layer Id - traffic-patterns
Python
traffic_patterns = hmc.traffic_patterns
types_to_df(traffic_patterns.object_types())
Data Class
Index by partition
Index by ID
Ref Types
Type
traffic_pattern
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
holiday_pattern
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
Python
traffic_pattern = traffic_patterns.get(tiles,"traffic_pattern")
traffic_pattern.head(2)
segments
forward
backward
attribute.traffic_pattern
0
[{'ref': {'partition': '23618502', 'identifier...
True
False
[{'day_of_week': 'SUNDAY', 'speed_pattern': [{...
1
[{'ref': {'partition': '23618502', 'identifier...
False
True
[{'day_of_week': 'SUNDAY', 'speed_pattern': [{...
Python
holiday_pattern = traffic_patterns.get(tiles,"holiday_pattern")
holiday_pattern.head(2)
segments
forward
backward
attribute.holiday
0
[{'ref': {'partition': '23618502', 'identifier...
True
False
[{'holiday_name': 'New Years Day', 'holiday_da...
1
[{'ref': {'partition': '23618502', 'identifier...
False
True
[{'holiday_name': 'New Years Day', 'holiday_da...
Python
### Construct a new Reference by giving partition and identifier.
traffic_pattern_ref = make_ref(23618502,"here:cm:segment:76770511")
Python
traffic_pattern_attributes = traffic_patterns.get_referencing(
23618502, "traffic_pattern", "first_segment",
)
traffic_pattern_attributes.head(2)
segments
forward
backward
attribute.traffic_pattern
ref_partition
ref_identifier
23618502
here:cm:segment:76770511
[{'ref': {'partition': '23618502', 'identifier...
True
False
[{'day_of_week': 'SUNDAY', 'speed_pattern': [{...
here:cm:segment:76770511
[{'ref': {'partition': '23618502', 'identifier...
False
True
[{'day_of_week': 'SUNDAY', 'speed_pattern': [{...
Python
holiday_pattern_attributes = traffic_patterns.get_referencing(
23618502, "holiday_pattern", "first_segment",
)
holiday_pattern_attributes.head(2)
segments
forward
backward
attribute.holiday
ref_partition
ref_identifier
23618502
here:cm:segment:76770511
[{'ref': {'partition': '23618502', 'identifier...
True
False
[{'holiday_name': 'New Years Day', 'holiday_da...
here:cm:segment:76770511
[{'ref': {'partition': '23618502', 'identifier...
False
True
[{'holiday_name': 'New Years Day', 'holiday_da...
Layer Id - sign-text
Python
tiles = [18011924]
sign_text = hmc.sign_text
types_to_df(sign_text.object_types())
Data Class
Index by partition
Index by ID
Ref Types
Type
sign_attribute
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
Python
display(sign_text.ref_types())
{'sign_attribute': ['first_segment', 'segment']}
Python
df = sign_text.get(tiles, "sign_attribute")
df.head(2)
segments
forward
backward
attribute.identifier
attribute.destination
0
[{'ref': {'partition': '18011924', 'identifier...
True
True
here:cm:sign:1653326986
[{'destination_segment_anchor_index': 2, 'sign...
1
[{'ref': {'partition': '18011924', 'identifier...
True
True
here:cm:sign:1653327084
[{'destination_segment_anchor_index': 20, 'sig...
Python
df = sign_text.get_referencing(tiles, "sign_attribute", "segment")
df.head(2)
segments
forward
backward
attribute.identifier
attribute.destination
ref_partition
ref_identifier
18011924
here:cm:segment:360301727
[{'ref': {'partition': '18011924', 'identifier...
True
True
here:cm:sign:1653326986
[{'destination_segment_anchor_index': 2, 'sign...
here:cm:segment:360301727
[{'ref': {'partition': '18011924', 'identifier...
True
True
here:cm:sign:1653367409
[{'destination_segment_anchor_index': 2, 'sign...
Python
df = sign_text.get_referencing(tiles, "sign_attribute", "first_segment")
df.head(2)
segments
forward
backward
attribute.identifier
attribute.destination
ref_partition
ref_identifier
18011924
here:cm:segment:360301727
[{'ref': {'partition': '18011924', 'identifier...
True
True
here:cm:sign:1653326986
[{'destination_segment_anchor_index': 2, 'sign...
here:cm:segment:360301727
[{'ref': {'partition': '18011924', 'identifier...
True
True
here:cm:sign:1653367409
[{'destination_segment_anchor_index': 2, 'sign...
Layer Id - administrative-places
Python
admin_places = hmc.admin_places
types_to_df(admin_places.object_types())
Data Class
Index by partition
Index by ID
Ref Types
Type
place
here.content.hmc2.admin_places.Place
True
True
None
context
here.content.hmc2.place_context.PlaceContext
False
False
None
Python
admin_tiles = ["20000001", "20000001-20000002-20030132"]
Python
df = admin_places.get(admin_tiles, "place")
df.head(2)
name
category
alt_category
location_ref.partition
location_ref.identifier
valid_unnamed
daylight_saving_time.day_of_week_of_month_of_year_range.start.day_of_week
daylight_saving_time.day_of_week_of_month_of_year_range.start.week_of_month
daylight_saving_time.day_of_week_of_month_of_year_range.start.month_of_year
daylight_saving_time.day_of_week_of_month_of_year_range.end.day_of_week
...
country.internal_phone_prefix
capital_indicator
population
daylight_saving_time
administrative_restriction
country
capital_indicator.capital_of_county
capital_indicator.capital_of_country
capital_indicator.capital_of_state
capital_indicator.capital_of_city
partition_id
place_id
20000001
here:cm:namedplace:20000001
[{'text': {'value': 'France', 'language': 'fr'...
[{'partition': '', 'identifier': 'here:cm:admi...
<NA>
20000001
here:cm:namedplace-loc:20000001
True
SUNDAY
WEEK_5
MARCH
SUNDAY
...
0
<NA>
<NA>
NaN
NaN
NaN
NaN
NaN
NaN
NaN
here:cm:namedplace:20000002
[{'text': {'value': 'Hauts-de-France', 'langua...
[{'partition': '', 'identifier': 'here:cm:admi...
<NA>
20000001
here:cm:namedplace-loc:20000002
True
NaN
NaN
NaN
NaN
...
NaN
<NA>
<NA>
<NA>
<NA>
<NA>
NaN
NaN
NaN
NaN
2 rows × 50 columns
Python
df = admin_places.get(admin_tiles, "context")
df.head(2)
classification_type
city
postal_code
country
state
region
county
district
sub_district
further_zone
default_mapping
political_view
political_view_exception
0
COUNTRY
<NA>
<NA>
[{'preference': 'PRIMARY', 'place_ref': {'part...
<NA>
<NA>
<NA>
<NA>
<NA>
<NA>
0
<NA>
<NA>
1
STATE
<NA>
<NA>
[{'preference': 'PRIMARY', 'place_ref': {'part...
[{'preference': 'PRIMARY', 'place_ref': {'part...
<NA>
<NA>
<NA>
<NA>
<NA>
0
<NA>
<NA>
Layer Id - administrative-locations
Python
admin_locations = hmc.admin_locations
types_to_df(admin_locations.object_types())
Data Class
Index by partition
Index by ID
Ref Types
Type
location
here.content.hmc2.admin_locations.Location
True
True
None
Python
df = admin_locations.get(partition="21000001", object_type="location")
df.head(2)
location_type
display_position
geometry
address_relation
area_type
segment_anchor.oriented_segment_ref
segment_anchor.attribute_orientation
segment_anchor_side
accessors
political_geometry
alternate_geometry
within_location_ref.partition_name
within_location_ref.identifier
bounding_box
level_info
partition_id
location_id
21000001
here:cm:namedplace-loc:21000001
AREA
POINT (0 0)
MULTIPOLYGON (((-80.4463 25.0527, -80.44623 25...
ADDRESS_RELATION_UNSPECIFIC
AREA_TYPE_STANDARD
[]
RELATIVE_DIRECTION_UNKNOWN
SIDE_UNKNOWN
<NA>
[]
[]
here:cm:namedplace-loc:21000002
AREA
POINT (0 0)
MULTIPOLYGON (((-92.29196 46.60708, -92.29199 ...
ADDRESS_RELATION_UNSPECIFIC
AREA_TYPE_STANDARD
[]
RELATIVE_DIRECTION_UNKNOWN
SIDE_UNKNOWN
<NA>
[]
[]
Layer Id - administrative_place_profiles
Python
admin_place_profiles = hmc.admin_place_profiles
Python
df = admin_place_profiles.get(partition = "21000001", object_type="admin_place_profile_attributes")
df.head(2)
administrative_place_ref.partition
administrative_place_ref.identifier
move_over
make_way
overtake_pass
merging
right_of_way
keep_right
solid_lane_travers_general
solid_lane_exception
color_temp_marking
dashed_width_lar
dashed_width_non_lar
spaces_marking_lar
spaces_marking_non_lar
solid_edge_width_lar
solid_edge_width_non_lar
average_lane_width_mtrw
average_lane_width_non_mtrw
partition_id
21000001
21000001
here:cm:namedplace:21000001
<NA>
<NA>
<NA>
<NA>
<NA>
<NA>
<NA>
<NA>
<NA>
0.15
0.1
0.15
0.15
0.15
0.1
3.6
3.3
21000001
21000001
here:cm:namedplace:21000002
3
True
False
5
1
True
False
63
13
<NA>
<NA>
<NA>
<NA>
<NA>
<NA>
<NA>
<NA>
Python
### Construct a new Reference by giving partition and identifier.
ref = make_ref("21000001", "here:cm:namedplace:21000002")
Python
admin_place_profiles.get_referencing(
partition = "21000001", object_type="admin_place_profile_attributes", ref_type="place", referenced_obj=ref
)
partition_id
administrative_place_ref.partition
administrative_place_ref.identifier
move_over
make_way
overtake_pass
merging
right_of_way
keep_right
solid_lane_travers_general
solid_lane_exception
color_temp_marking
dashed_width_lar
dashed_width_non_lar
spaces_marking_lar
spaces_marking_non_lar
solid_edge_width_lar
solid_edge_width_non_lar
average_lane_width_mtrw
average_lane_width_non_mtrw
0
21000001
21000001
here:cm:namedplace:21000002
3
True
False
5
1
True
False
63
13
<NA>
<NA>
<NA>
<NA>
<NA>
<NA>
<NA>
<NA>
Layer Id - indexed_locations
Python
admin_index = hmc.admin_index
Python
types_to_df(admin_index.object_types())
Data Class
Index by partition
Index by ID
Ref Types
Type
country
here.content.hmc2.admin_index.CountryTiles
False
True
None
location
here.content.hmc2.admin_index.LocationTiles
False
False
location
Python
country_partitions = ["FIN", "HND", "IRL"]
country_tiles = admin_index.get(country_partitions, "country")
country_tiles
tile_id
iso_country_code
FIN
[23648741, 23648743, 23648745, 23648752, 23648...
HND
[19956478, 19956479, 19956574, 19956575, 19956...
IRL
[20799693, 20799695, 20799704, 20799705, 20799...
Python
## You can always use the `explode` function to convert a list in multiple rows.
country_tiles.explode("tile_id")
tile_id
iso_country_code
FIN
23648741
FIN
23648743
FIN
23648745
FIN
23648752
FIN
23648754
...
...
IRL
20803192
IRL
20803193
IRL
20803338
IRL
20803360
IRL
20803361
11735 rows × 1 columns
Python
plot_here_tiles(country_tiles.loc["FIN"]["tile_id"])
Map(center=[np.float64(60.1611328125), np.float64(19.2919921875)], controls=(ZoomControl(options=['position', …
Python
plot_here_tiles(country_tiles.loc["IRL"]["tile_id"])
Map(center=[np.float64(51.5478515625), np.float64(-10.2392578125)], controls=(ZoomControl(options=['position',…
Python
df = admin_index.get_referencing(country_partitions, "location", "location")
df.head(2)
iso_country_code
tile_id
boundary_tile_id
ref_partition
ref_identifier
20241487
here:cm:namedplace-loc:20241487
FIN
[23648741, 23648743, 23648745, 23648752, 23648...
[23648741, 23648743, 23648745, 23648752, 23648...
here:cm:namedplace-loc:20422913
FIN
[23693371, 23693445, 23693453, 23693456, 23693...
[23693371, 23693445, 23693453, 23693456, 23693...
Layer Id - environmental_zones
Python
environmental_zones = hmc.environmental_zones
types_to_df(environmental_zones.object_types())
Data Class
Index by partition
Index by ID
Ref Types
Type
zone
here.content.hmc2.environmental_zones.Zone
False
True
location
Python
environmental_zones.ref_types()
{'zone': ['location']}
Python
types_to_df(environmental_zones.object_types())
Data Class
Index by partition
Index by ID
Ref Types
Type
zone
here.content.hmc2.environmental_zones.Zone
False
True
location
Python
env_zones = environmental_zones.get("all", "zone")
env_zones.head(2)
name
info.description
info.website.value
info.website.language
info.version_date
info.extent_date
info.country
vehicle_class
environmental_badge
location_ref
identifier
here:cm:envzone:1
[{'text': {'value': 'Augsburg Umweltzone', 'la...
[{'value': 'Die Umweltzone der Stadt Augsburg ...
https://www.augsburg.de/umwelt-soziales/umwelt...
2019-05-09
2019-01-01
GERMANY
[{'vehicle_attributes': {'category': 'AUTO', '...
[{'badge_type': 'DEU_GREEN_STICKER', 'zone_acc...
[{'partition': '23600504', 'identifier': 'here...
here:cm:envzone:10
[{'text': {'value': 'Essen Umweltzone', 'langu...
[{'value': 'Die Umweltzone der Stadt Essen ist...
https://www.essen.de/leben/umwelt/luft/umweltz...
2022-06-03
2019-01-01
GERMANY
[{'vehicle_attributes': {'category': 'AUTO', '...
[{'badge_type': 'DEU_GREEN_STICKER', 'zone_acc...
[{'partition': '23605461', 'identifier': 'here...
Python
### Construct a new Reference by giving partition and identifier.
location_ref = make_ref("23600686", "here:cm:carto-loc:1661293691")
Python
env_zones = environmental_zones.get_referencing("all", "zone", "location", location_ref)
env_zones
identifier
name
info.description
info.website.value
info.website.language
info.version_date
info.extent_date
info.country
vehicle_class
environmental_badge
location_ref
0
here:cm:envzone:304
[{'text': {'value': 'Lkw-Verbotszone Darmstadt...
[{'value': 'Permanent truck ban for environmen...
https://umwelt.hessen.de/sites/default/files/m...
2020-11-06
2020-09-18
GERMANY
[{'vehicle_attributes': {'category': 'TRUCK', ...
<NA>
[{'partition': '23600686', 'identifier': 'here...
Layer Id - topology-geometry
Python
topology_geometry = hmc.topology_geometry
types_to_df(topology_geometry.object_types())
Data Class
Index by partition
Index by ID
Ref Types
Type
node
here.content.hmc2.topology_geometry.Node
True
True
None
segment
here.content.hmc2.topology_geometry.Segment
True
True
None
Python
topology_geometry.ref_types()
{'node': [], 'segment': []}
Python
types_to_df(topology_geometry.object_types())
Data Class
Index by partition
Index by ID
Ref Types
Type
node
here.content.hmc2.topology_geometry.Node
True
True
None
segment
here.content.hmc2.topology_geometry.Segment
True
True
None
Python
nodes = topology_geometry.get(tiles, "node")
nodes.head(2)
segment_ref
geometry
z_level
partition_id
node_id
19318110
here:cm:node:19706971
[{'partition': '19318110', 'identifier': 'here...
POINT (-118.22421 34.0527)
0
here:cm:node:19706990
[{'partition': '19318110', 'identifier': 'here...
POINT (-118.21902 34.04041)
0
Python
segments = topology_geometry.get(tiles, "segment")
segments.head(2)
start_node_ref.partition
start_node_ref.identifier
end_node_ref.partition
end_node_ref.identifier
geometry
z_level
length
partition_id
segment_id
19318110
here:cm:segment:395921031
19318110
here:cm:node:49251578
19318110
here:cm:node:49251579
LINESTRING (-118.27758 34.03233, -118.27676 34...
[0, 0]
159.93573
here:cm:segment:395921122
19318110
here:cm:node:49256445
19318110
here:cm:node:49256415
LINESTRING (-118.2891 34.07896, -118.28967 34....
[0, 0, 0, 0, 0]
157.52114
Python
geometries={"Nodes": nodes, "Segments": segments}
plot_multiple_geometry(geometries)
Map(center=[np.float64(34.0527), np.float64(-118.22421)], controls=(ZoomControl(options=['position', 'zoom_in_…
Layer Id - topology-attributes
Python
topology_attributes = hmc.topology_attributes
Python
types_to_df(topology_attributes.object_types())
Data Class
Index by partition
Index by ID
Ref Types
Type
access_permission
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
access_restriction
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
accessible_by
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
black_spot
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
construction_status
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
display_level
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
environmental_zone_condition
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
functional_class
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
gate
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
grade_category
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
intersection_category
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
iso_country_code
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
junction_divider
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
lane_category
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
local_road
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
low_mobility
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
low_speed_zone
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
motorcycle_restriction
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
overpass_underpass
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
overtaking_restriction
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
permitted_driving_manoeuvre
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
physical
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
physical_lane_count
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
political_view_action
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
protected_overtaking
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
railway_crossing
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
recreational_vehicle_restriction
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
restricted_driving_manoeuvre
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
road_class
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
road_divider
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
road_usage
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
scenic
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
short_construction_warning
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
special_explication
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
special_speed_situation
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
special_traffic_area_category
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
speed_category
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
speed_limit
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
supplemental_geometry
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
through_lane_count
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
through_route
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
toll_structure
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
traffic_message_channel_code
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
traffic_sign
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
traffic_signal
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
transport_protocol_expert_group
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
travel_direction
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
urban
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
usage_fee_required
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
variable_speed_limit
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
variable_speed_sign
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
vehicle_checkpoint
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
Python
topology_attributes.ref_types()
{'access_permission': ['first_segment', 'segment'],
'access_restriction': ['first_segment', 'segment'],
'accessible_by': ['first_segment', 'segment'],
'black_spot': ['first_segment', 'segment'],
'construction_status': ['first_segment', 'segment'],
'display_level': ['first_segment', 'segment'],
'environmental_zone_condition': ['first_segment', 'segment'],
'functional_class': ['first_segment', 'segment'],
'gate': ['first_segment', 'segment'],
'grade_category': ['first_segment', 'segment'],
'intersection_category': ['first_segment', 'segment'],
'iso_country_code': ['first_segment', 'segment'],
'junction_divider': ['first_segment', 'segment'],
'lane_category': ['first_segment', 'segment'],
'local_road': ['first_segment', 'segment'],
'low_mobility': ['first_segment', 'segment'],
'low_speed_zone': ['first_segment', 'segment'],
'motorcycle_restriction': ['first_segment', 'segment'],
'overpass_underpass': ['first_segment', 'segment'],
'overtaking_restriction': ['first_segment', 'segment'],
'permitted_driving_manoeuvre': ['first_segment', 'segment'],
'physical': ['first_segment', 'segment'],
'physical_lane_count': ['first_segment', 'segment'],
'political_view_action': ['first_segment', 'segment'],
'protected_overtaking': ['first_segment', 'segment'],
'railway_crossing': ['first_segment', 'segment'],
'recreational_vehicle_restriction': ['first_segment', 'segment'],
'restricted_driving_manoeuvre': ['first_segment', 'segment'],
'road_class': ['first_segment', 'segment'],
'road_divider': ['first_segment', 'segment'],
'road_usage': ['first_segment', 'segment'],
'scenic': ['first_segment', 'segment'],
'short_construction_warning': ['first_segment', 'segment'],
'special_explication': ['first_segment', 'segment'],
'special_speed_situation': ['first_segment', 'segment'],
'special_traffic_area_category': ['first_segment', 'segment'],
'speed_category': ['first_segment', 'segment'],
'speed_limit': ['first_segment', 'segment'],
'supplemental_geometry': ['first_segment', 'segment'],
'through_lane_count': ['first_segment', 'segment'],
'through_route': ['first_segment', 'segment'],
'toll_structure': ['first_segment', 'segment'],
'traffic_message_channel_code': ['first_segment', 'segment'],
'traffic_sign': ['first_segment', 'segment'],
'traffic_signal': ['first_segment', 'segment'],
'transport_protocol_expert_group': ['first_segment', 'segment'],
'travel_direction': ['first_segment', 'segment'],
'urban': ['first_segment', 'segment'],
'usage_fee_required': ['first_segment', 'segment'],
'variable_speed_limit': ['first_segment', 'segment'],
'variable_speed_sign': ['first_segment', 'segment'],
'vehicle_checkpoint': ['first_segment', 'segment']}
Python
types_to_df(topology_attributes.object_types())
Data Class
Index by partition
Index by ID
Ref Types
Type
access_permission
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
access_restriction
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
accessible_by
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
black_spot
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
construction_status
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
display_level
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
environmental_zone_condition
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
functional_class
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
gate
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
grade_category
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
intersection_category
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
iso_country_code
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
junction_divider
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
lane_category
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
local_road
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
low_mobility
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
low_speed_zone
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
motorcycle_restriction
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
overpass_underpass
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
overtaking_restriction
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
permitted_driving_manoeuvre
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
physical
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
physical_lane_count
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
political_view_action
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
protected_overtaking
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
railway_crossing
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
recreational_vehicle_restriction
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
restricted_driving_manoeuvre
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
road_class
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
road_divider
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
road_usage
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
scenic
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
short_construction_warning
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
special_explication
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
special_speed_situation
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
special_traffic_area_category
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
speed_category
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
speed_limit
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
supplemental_geometry
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
through_lane_count
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
through_route
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
toll_structure
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
traffic_message_channel_code
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
traffic_sign
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
traffic_signal
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
transport_protocol_expert_group
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
travel_direction
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
urban
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
usage_fee_required
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
variable_speed_limit
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
variable_speed_sign
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
vehicle_checkpoint
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
Python
tiles = [19318110]
df = topology_attributes.get(tiles, "functional_class")
df.head(2)
segments
forward
backward
attribute.functional_class
0
[{'ref': {'partition': '19318110', 'identifier...
True
True
FUNCTIONAL_CLASS_5
1
[{'ref': {'partition': '19318110', 'identifier...
True
True
FUNCTIONAL_CLASS_5
Python
df = topology_attributes.get_referencing(tiles, "functional_class", "segment")
df.head(2)
segments
forward
backward
attribute.functional_class
ref_partition
ref_identifier
19318110
here:cm:segment:395921031
[{'ref': {'partition': '19318110', 'identifier...
True
True
FUNCTIONAL_CLASS_5
here:cm:segment:396018522
[{'ref': {'partition': '19318110', 'identifier...
True
True
FUNCTIONAL_CLASS_5
Python
df = topology_attributes.get_referencing(tiles, "iso_country_code", "segment")
df.head(2)
segments
forward
backward
attribute.iso_country_code.official_country_code
ref_partition
ref_identifier
19318110
here:cm:segment:395921031
[{'ref': {'partition': '19318110', 'identifier...
True
True
USA
here:cm:segment:395921122
[{'ref': {'partition': '19318110', 'identifier...
True
True
USA
Python
df = topology_attributes.get(tiles, "speed_limit")
df.head(2)
segments
forward
backward
attribute.value
attribute.source
attribute.unlimited
attribute.sources
0
[{'ref': {'partition': '19318110', 'identifier...
True
False
40
DERIVED
False
[]
1
[{'ref': {'partition': '19318110', 'identifier...
False
True
40
DERIVED
False
[]
Python
df = topology_attributes.get(tiles, "traffic_message_channel_code")
df.head(2)
segments
forward
backward
attribute.location_code
attribute.location_disposition
attribute.location_table_number
attribute.ebu_country_code
0
[{'ref': {'partition': '19318110', 'identifier...
True
False
21457
INTERNAL_POSITIVE_DIRECTION
6
1
1
[{'ref': {'partition': '19318110', 'identifier...
False
True
21457
INTERNAL_POSITIVE_DIRECTION
6
1
Python
df = topology_attributes.get(tiles, "restricted_driving_manoeuvre")
df.head(2)
segments
forward
backward
attribute.applies_to.automobiles
attribute.applies_to.buses
attribute.applies_to.taxis
attribute.applies_to.carpools
attribute.applies_to.pedestrians
attribute.applies_to.trucks
attribute.applies_to.through_traffic
attribute.applies_to.deliveries
attribute.applies_to.emergency_vehicles
attribute.applies_to.motorcycles
attribute.applies_to.bicycles
attribute.restriction_type
attribute.applies_during
attribute.manoeuvre_type
0
[{'ref': {'partition': '19318110', 'identifier...
True
False
True
True
True
True
True
True
True
True
True
True
False
PHYSICAL
[]
MANOEUVRE_TYPE_UNKNOWN
1
[{'ref': {'partition': '19318110', 'identifier...
True
False
True
True
True
True
True
True
True
True
True
True
False
PHYSICAL
[]
MANOEUVRE_TYPE_UNKNOWN
Python
df = topology_attributes.get(tiles, "travel_direction")
df.head(2)
segments
forward
backward
0
[{'ref': {'partition': '19318110', 'identifier...
True
True
1
[{'ref': {'partition': '19318110', 'identifier...
True
False
Python
df = topology_attributes.get([18403672], "environmental_zone_condition")
df.head(2)
segments
forward
backward
attribute.applies_to.automobiles
attribute.applies_to.buses
attribute.applies_to.carpools
attribute.applies_to.through_traffic
attribute.applies_to.motorcycles
attribute.applies_to.taxis
attribute.applies_to.pedestrians
attribute.applies_to.trucks
attribute.applies_to.deliveries
attribute.applies_to.emergency_vehicles
attribute.applies_to.bicycles
attribute.environmental_zone_ref.partition_name
attribute.environmental_zone_ref.identifier
0
[{'ref': {'partition': '18403672', 'identifier...
True
True
True
True
True
True
True
False
False
False
False
False
False
all
here:cm:envzone:81
1
[{'ref': {'partition': '18403672', 'identifier...
True
True
True
True
True
True
True
False
False
False
False
False
False
all
here:cm:envzone:81
Python
df = topology_attributes.get_referencing(tiles, "restricted_driving_manoeuvre", "first_segment")
df.head(2)
segments
forward
backward
attribute.applies_to.automobiles
attribute.applies_to.buses
attribute.applies_to.taxis
attribute.applies_to.carpools
attribute.applies_to.pedestrians
attribute.applies_to.trucks
attribute.applies_to.through_traffic
attribute.applies_to.deliveries
attribute.applies_to.emergency_vehicles
attribute.applies_to.motorcycles
attribute.applies_to.bicycles
attribute.restriction_type
attribute.applies_during
attribute.manoeuvre_type
ref_partition
ref_identifier
19318110
here:cm:segment:396042113
[{'ref': {'partition': '19318110', 'identifier...
True
False
True
True
True
True
True
True
True
True
True
True
False
PHYSICAL
[]
MANOEUVRE_TYPE_UNKNOWN
here:cm:segment:396042113
[{'ref': {'partition': '19318110', 'identifier...
True
False
True
True
True
True
True
True
True
True
True
True
False
PHYSICAL
[]
MANOEUVRE_TYPE_UNKNOWN
Python
df = topology_attributes.get(tiles, "traffic_signal")
df.head(2)
segments
forward
backward
attribute.signal_location
0
[{'ref': {'partition': '19318110', 'identifier...
False
True
SIGN_LOCATION_UNKNOWN
1
[{'ref': {'partition': '19318110', 'identifier...
False
True
SIGN_LOCATION_UNKNOWN
Python
df = topology_attributes.get(tiles, "traffic_sign")
df.head(2)
segments
forward
backward
attribute.traffic_sign_type
attribute.traffic_sign_category
attribute.traffic_sign_subcategory
attribute.traffic_sign_value.value
attribute.traffic_sign_value.language
attribute.pre_warning.value
attribute.pre_warning.language
...
attribute.validity_time.value
attribute.validity_time.language
attribute.accessible_by.trucks
attribute.accessible_by.heavy_trucks
attribute.accessible_by.bus
attribute.accessible_by.auto_trailer
attribute.accessible_by.motorhome
attribute.accessible_by.motorcycle
attribute.general_warning_sign_type
attribute.weather_type
0
[{'ref': {'partition': '19318110', 'identifier...
False
True
STOP_SIGN
REGULATORY_SIGN
PRIORITY_SIGN
...
False
False
False
False
False
False
GENERAL_WARNING_SIGN_TYPE_UNKNOWN
WEATHER_TYPE_UNKNOWN
1
[{'ref': {'partition': '19318110', 'identifier...
False
True
STOP_SIGN
REGULATORY_SIGN
PRIORITY_SIGN
...
False
False
False
False
False
False
GENERAL_WARNING_SIGN_TYPE_UNKNOWN
WEATHER_TYPE_UNKNOWN
2 rows × 22 columns
Python
df = topology_attributes.get_referencing(tiles, "traffic_sign", "first_segment")
df.head(2)
segments
forward
backward
attribute.traffic_sign_type
attribute.traffic_sign_category
attribute.traffic_sign_subcategory
attribute.traffic_sign_value.value
attribute.traffic_sign_value.language
attribute.pre_warning.value
attribute.pre_warning.language
...
attribute.validity_time.value
attribute.validity_time.language
attribute.accessible_by.trucks
attribute.accessible_by.heavy_trucks
attribute.accessible_by.bus
attribute.accessible_by.auto_trailer
attribute.accessible_by.motorhome
attribute.accessible_by.motorcycle
attribute.general_warning_sign_type
attribute.weather_type
ref_partition
ref_identifier
19318110
here:cm:segment:395921031
[{'ref': {'partition': '19318110', 'identifier...
False
True
STOP_SIGN
REGULATORY_SIGN
PRIORITY_SIGN
...
False
False
False
False
False
False
GENERAL_WARNING_SIGN_TYPE_UNKNOWN
WEATHER_TYPE_UNKNOWN
here:cm:segment:395921031
[{'ref': {'partition': '19318110', 'identifier...
True
False
STOP_SIGN
REGULATORY_SIGN
PRIORITY_SIGN
...
False
False
False
False
False
False
GENERAL_WARNING_SIGN_TYPE_UNKNOWN
WEATHER_TYPE_UNKNOWN
2 rows × 22 columns
Python
df = topology_attributes.get(tiles, "railway_crossing")
df.head(2)
segments
forward
backward
attribute.crossing_type
0
[{'ref': {'partition': '19318110', 'identifier...
False
True
UNPROTECTED
1
[{'ref': {'partition': '19318110', 'identifier...
False
True
UNPROTECTED
Python
df = topology_attributes.get_referencing(tiles, "railway_crossing", "segment")
df.head(2)
segments
forward
backward
attribute.crossing_type
ref_partition
ref_identifier
19318110
here:cm:segment:411541476
[{'ref': {'partition': '19318110', 'identifier...
False
True
UNPROTECTED
here:cm:segment:425689374
[{'ref': {'partition': '19318110', 'identifier...
False
True
UNPROTECTED
Layer Id - bicycle-attributes
Python
bicycle_attributes = hmc.bicycle_attributes
types_to_df(bicycle_attributes.object_types())
Data Class
Index by partition
Index by ID
Ref Types
Type
bicycle_access_override
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
bicycle_protection_type
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
bicycle_travel_direction_override
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
dedicated_bicycle_path
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
bicycle_path
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
bicycle_access_verified
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
Python
bicycle_attributes.ref_types()
{'bicycle_access_override': ['first_segment', 'segment'],
'bicycle_protection_type': ['first_segment', 'segment'],
'bicycle_travel_direction_override': ['first_segment', 'segment'],
'dedicated_bicycle_path': ['first_segment', 'segment'],
'bicycle_path': ['first_segment', 'segment'],
'bicycle_access_verified': ['first_segment', 'segment']}
Python
types_to_df(bicycle_attributes.object_types())
Data Class
Index by partition
Index by ID
Ref Types
Type
bicycle_access_override
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
bicycle_protection_type
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
bicycle_travel_direction_override
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
dedicated_bicycle_path
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
bicycle_path
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
bicycle_access_verified
here.content.hmc2.base_attributes.Attribute
False
False
first_segment, segment
Python
tiles = [19318110]
df = bicycle_attributes.get_referencing(tiles, "bicycle_path", "segment")
df.head(2)
segments
forward
backward
attribute.separately_digitized
attribute.dedicated_bicycle_path
attribute.surface_type
ref_partition
ref_identifier
19318110
here:cm:segment:399602652
[{'ref': {'partition': '19318110', 'identifier...
True
True
True
SIDE_UNKNOWN
SURFACE_TYPE_UNKNOWN
here:cm:segment:420339828
[{'ref': {'partition': '19318110', 'identifier...
True
True
True
SIDE_UNKNOWN
SURFACE_TYPE_UNKNOWN
Python
df = bicycle_attributes.get_referencing(tiles, "dedicated_bicycle_path", "segment")
df.head(2)
Layer Id - places-metadata
Python
places_metadata = hmc.places_metadata
types_to_df(places_metadata.object_types())
Data Class
Index by partition
Index by ID
Ref Types
Type
category_system
here.content.hmc2.metadata.CategorySystem
False
True
None
category
here.content.hmc2.metadata.Category
False
True
None
Python
places_metadata.get("all", "category_system")
name.text.value
name.text.language
name.name_type
name.representation
name.exonym
description
identifier
here:pds:chain_families:chain_families
chain_families
NAME_TYPE_UNKNOWN
[]
False
<NA>
here:pds:chains:chains
chains
NAME_TYPE_UNKNOWN
[]
False
<NA>
here:pds:izumi:izumi
izumi
NAME_TYPE_UNKNOWN
[]
False
<NA>
here:pds:lcms-foodtype:lcms-foodtype
lcms-foodtype
NAME_TYPE_UNKNOWN
[]
False
<NA>
here:pds:navteq-lcms:navteq-lcms
navteq-lcms
NAME_TYPE_UNKNOWN
[]
False
<NA>
here:pds:nokia-foodtype:nokia-foodtype
nokia-foodtype
NAME_TYPE_UNKNOWN
[]
False
<NA>
Python
df = places_metadata.get("all", "category")
df.head(2)
name.text.value
name.text.language
name.name_type
name.representation
name.exonym
description
category_system
description.text.value
description.text.language
description.name_type
description.representation
description.exonym
identifier
here:pds:chain_families:10001
BMW
en
NAME_TYPE_UNKNOWN
[]
False
<NA>
here:pds:chain_families:chain_families
NaN
NaN
NaN
NaN
NaN
here:pds:chain_families:10002
FIAT
en
NAME_TYPE_UNKNOWN
[]
False
<NA>
here:pds:chain_families:chain_families
NaN
NaN
NaN
NaN
NaN
Layer Id - building-metadata
Python
building_metadata = hmc.building_metadata
types_to_df(building_metadata.object_types())
Data Class
Index by partition
Index by ID
Ref Types
Type
category_system
here.content.hmc2.metadata.CategorySystem
False
True
None
category
here.content.hmc2.metadata.Category
False
True
None
Python
building_metadata.get("all", "category_system")
name.text.value
name.text.language
name.name_type
name.representation
name.exonym
description.text.value
description.text.language
description.name_type
description.representation
description.exonym
identifier
here:cm:building-category:1999217009
FEATSTP
NAME_TYPE_UNKNOWN
[]
False
Feature Sub-Types
NAME_TYPE_UNKNOWN
[]
False
here:cm:building-category:1999021584
FEATURE
NAME_TYPE_UNKNOWN
[]
False
Feature Type
NAME_TYPE_UNKNOWN
[]
False
here:cm:building-category:7979404116
JPN_CARTOFEATURE_TYPES
NAME_TYPE_UNKNOWN
[]
False
Cartofeatures that are unique to Japan
NAME_TYPE_UNKNOWN
[]
False
here:cm:building-category:7979406126
JPN_FEATSTP
NAME_TYPE_UNKNOWN
[]
False
Japan specific building types
NAME_TYPE_UNKNOWN
[]
False
Python
df = building_metadata.get("all", "category")
df.head(2)
name.text.value
name.text.language
name.name_type
name.representation
name.exonym
description
category_system
identifier
here:cm:building-category:2005000
BUSINESS/COMMERCE BUILDING/LANDMARK
NAME_TYPE_UNKNOWN
[]
False
<NA>
here:cm:building-category:1999217009
here:cm:building-category:2005000
Business/Commerce Building/Landmark
NAME_TYPE_UNKNOWN
[]
False
<NA>
here:cm:building-category:1999021584
Layer Id - cartography-metadata
Python
cartography_metadata = hmc.cartography_metadata
types_to_df(places_metadata.object_types())
Data Class
Index by partition
Index by ID
Ref Types
Type
category_system
here.content.hmc2.metadata.CategorySystem
False
True
None
category
here.content.hmc2.metadata.Category
False
True
None
Python
cartography_metadata.get("all", "category_system")
name.text.value
name.text.language
name.name_type
name.representation
name.exonym
description.text.value
description.text.language
description.name_type
description.representation
description.exonym
identifier
here:cm:carto-category:1999893136
CLS_PUBLISHED_FEATURES
NAME_TYPE_UNKNOWN
[]
False
CLS_PUBLISHED_FEATURES
NAME_TYPE_UNKNOWN
[]
False
here:cm:carto-category:1999021599
DISPCLAS
NAME_TYPE_UNKNOWN
[]
False
Display Class
NAME_TYPE_UNKNOWN
[]
False
here:cm:carto-category:1999021584
FEATURE
NAME_TYPE_UNKNOWN
[]
False
Feature Type
NAME_TYPE_UNKNOWN
[]
False
here:cm:carto-category:7979866573
HMC_CARTO
NAME_TYPE_UNKNOWN
[]
False
Carto features used by global HMC
NAME_TYPE_UNKNOWN
[]
False
here:cm:carto-category:7979404116
JPN_CARTOFEATURE_TYPES
NAME_TYPE_UNKNOWN
[]
False
Cartofeatures that are unique to Japan
NAME_TYPE_UNKNOWN
[]
False
here:cm:carto-category:7979406126
JPN_FEATSTP
NAME_TYPE_UNKNOWN
[]
False
Japan specific building types
NAME_TYPE_UNKNOWN
[]
False
here:cm:carto-category:1999918379
LANDCOVER_CLASS
NAME_TYPE_UNKNOWN
[]
False
LANDCOVER_CLASS
NAME_TYPE_UNKNOWN
[]
False
Python
df = cartography_metadata.get("all", "category")
df.head(2)
name.text.value
name.text.language
name.name_type
name.representation
name.exonym
description
category_system
identifier
here:cm:carto-category:
NOT APPLICABLE
NAME_TYPE_UNKNOWN
[]
False
<NA>
here:cm:carto-category:1999021599
here:cm:carto-category:1
FIRST CLASS
NAME_TYPE_UNKNOWN
[]
False
<NA>
here:cm:carto-category:1999021599
Python
here_places = hmc.here_places
types_to_df(here_places.object_types())
Data Class
Index by partition
Index by ID
Ref Types
Type
supplier
here.content.hmc2.models.Supplier
True
True
None
author
here.content.hmc2.models.Author
True
False
None
place
here.content.hmc2.models.Place
True
True
None
external_identifier
here.content.hmc2.models.ExternalIdentifier
True
True
None
contact_information
here.content.hmc2.models.ContactInformation
True
False
None
operating_time
here.content.hmc2.models.OperatingTime
True
False
None
feedback
here.content.hmc2.models.Feedback
True
False
None
payment
here.content.hmc2.models.Payment
True
False
None
relationship_attribute
here.content.hmc2.models.RelationshipAttribute
True
False
None
capacity_attribute
here.content.hmc2.models.CapacityAttribute
True
False
None
internet_connection_attribute
here.content.hmc2.models.InternetConnectionAtt...
True
False
None
price_range
here.content.hmc2.models.PriceRange
True
False
None
spoken_language
here.content.hmc2.models.SpokenLanguage
True
False
None
qr_code_attribute
here.content.hmc2.models.QrCodeAttribute
True
False
None
verification_attribute
here.content.hmc2.models.VerificationAttribute
True
False
None
media_reference_attribute
here.content.hmc2.models.MediaReferenceAttribute
True
False
None
quality_score
here.content.hmc2.models.QualityScore
True
False
None
place_access_attribute
here.content.hmc2.models.PlaceAccessAttribute
True
False
None
amenities_attribute
here.content.hmc2.models.AmenitiesAttribute
True
False
None
alcohol_service_attribute
here.content.hmc2.models.AlcoholServiceAttribute
True
False
None
basic_info_attribute
here.content.hmc2.models.BasicInfoAttribute
True
False
None
other_information
here.content.hmc2.models.OtherInformation
True
False
None
electric_charge_attribute
here.content.hmc2.models.ElectricChargeAttribute
True
False
None
hotel_attribute
here.content.hmc2.models.HotelAttribute
True
False
None
location_information
here.content.hmc2.models.LocationInformation
True
False
None
parking_attribute
here.content.hmc2.models.ParkingAttribute
True
False
None
restaurant_attribute
here.content.hmc2.models.RestaurantAttribute
True
False
None
transit_attribute
here.content.hmc2.models.TransitAttribute
True
False
None
vehicle_services_attribute
here.content.hmc2.models.VehicleServicesAttribute
True
False
None
address
here.content.hmc2.models.Address
True
False
None
location
here.content.hmc2.models.Location
True
True
None
truck_attribute
here.content.hmc2.models.TruckAttribute
True
False
None
fuel_type_attribute
here.content.hmc2.models.FuelTypeAttribute
True
False
None
social_signal
here.content.hmc2.models.SocialSignal
True
False
None
port_attribute
here.content.hmc2.models.PortAttribute
True
False
None
safety_camera
here.content.hmc2.models.SafetyCamera
True
False
None
black_spot
here.content.hmc2.models.BlackSpot
True
False
None
match_level_attribute
here.content.hmc2.models.MatchLevelAttribute
True
False
None
affiliation_attribute
here.content.hmc2.models.AffiliationAttribute
True
False
None
office_type_attribute
here.content.hmc2.models.OfficeTypeAttribute
True
False
None
note_type_attribute
here.content.hmc2.models.NoteTypeAttribute
True
False
None
place_category_confidence_attribute
here.content.hmc2.models.PlaceCategoryConfiden...
True
False
None
popularity_attribute
here.content.hmc2.models.PopularityAttribute
True
False
None
vendor_url_attribute
here.content.hmc2.models.VendorUrlAttribute
True
False
None
Python
df = here_places.get("19319399", "external_identifier")
df.head(2)
places
supplier.partition_id
supplier.id
supplier.names
supplier.category.partition
supplier.category.identifier
inactive
category.partition
category.identifier
type
partition_id
id
19319399
-0Mrmlbum_Eii7fo8POhQQ
[{'partition_id': '19319399', 'id': 'here:pds:...
19319399
here:pds:placesupplier:yelp
[{'text': {'value': 'yelp', 'language': ''}, '...
all
here:pds:navteq-lcms:900-9300-0221
False
SUPPLIER_POIID
-2VLIpgTdqoWMckVAS1b7Q
[{'partition_id': '19319399', 'id': 'here:pds:...
19319399
here:pds:placesupplier:yelp
[{'text': {'value': 'yelp', 'language': ''}, '...
all
here:pds:navteq-lcms:900-9300-0221
False
SUPPLIER_POIID
This binding associates segment with administrative boundary.
Layer Ids - administrative-places , administrative-locations
Python
segment_admin_boundary = hmc.segment_admin_boundary
types_to_df(segment_admin_boundary.object_types())
Data Class
Index by partition
Index by ID
Ref Types
Type
segment_admin_boundary
here.content.hmc2.segment_admin_boundary.Segme...
True
False
segment, place
Python
df = segment_admin_boundary.get(17302684, "segment_admin_boundary")
df.head(2)
segments
forward
backward
place_ref.partition
place_ref.identifier
place_name
admin_category
location.partition_id
location.location_id
location.location_type
...
location.segment_anchor.oriented_segment_ref
location.segment_anchor.attribute_orientation
location.segment_anchor_side
location.accessors
location.political_geometry
location.alternate_geometry
location.within_location_ref.partition_name
location.within_location_ref.identifier
location.bounding_box
location.level_info
partition_id
17302684
[{'ref': {'partition': '17302684', 'identifier...
True
True
23060936-27869540-27869541
here:cm:namedplace:27869542
[{'text': {'value': 'Chatham Islands', 'langua...
city
23060936-27869540-27869541
here:cm:namedplace-loc:27869542
AREA
...
[]
RELATIVE_DIRECTION_UNKNOWN
SIDE_UNKNOWN
<NA>
[]
[]
17302684
[{'ref': {'partition': '17302684', 'identifier...
True
True
23060936-27869540-27869541
here:cm:namedplace:27869549
[{'text': {'value': '8016', 'language': ''}, '...
postal_code
23060936-27869540-27869541
here:cm:namedplace-loc:27869549
AREA
...
[]
RELATIVE_DIRECTION_UNKNOWN
SIDE_UNKNOWN
<NA>
[]
[]
2 rows × 24 columns
Python
df = segment_admin_boundary.get(17302684, "segment_admin_boundary")
df.head(2)
segments
forward
backward
place_ref.partition
place_ref.identifier
place_name
admin_category
location.partition_id
location.location_id
location.location_type
...
location.segment_anchor.oriented_segment_ref
location.segment_anchor.attribute_orientation
location.segment_anchor_side
location.accessors
location.political_geometry
location.alternate_geometry
location.within_location_ref.partition_name
location.within_location_ref.identifier
location.bounding_box
location.level_info
partition_id
17302684
[{'ref': {'partition': '17302684', 'identifier...
True
True
23060936-27869540-27869541
here:cm:namedplace:27869542
[{'text': {'value': 'Chatham Islands', 'langua...
city
23060936-27869540-27869541
here:cm:namedplace-loc:27869542
AREA
...
[]
RELATIVE_DIRECTION_UNKNOWN
SIDE_UNKNOWN
<NA>
[]
[]
17302684
[{'ref': {'partition': '17302684', 'identifier...
True
True
23060936-27869540-27869541
here:cm:namedplace:27869549
[{'text': {'value': '8016', 'language': ''}, '...
postal_code
23060936-27869540-27869541
here:cm:namedplace-loc:27869549
AREA
...
[]
RELATIVE_DIRECTION_UNKNOWN
SIDE_UNKNOWN
<NA>
[]
[]
2 rows × 24 columns
Python
### Construct a new Reference by giving partition and identifier.
segment_ref = make_ref("17302684", "here:cm:segment:499005300")
Python
segment_admin_boundary_atts = segment_admin_boundary.get_referencing("17302684", "segment_admin_boundary",
"segment", segment_ref)
segment_admin_boundary_atts.head(2)
partition_id
segments
forward
backward
place_ref.partition
place_ref.identifier
place_name
admin_category
location.partition_id
location.location_id
...
location.segment_anchor.oriented_segment_ref
location.segment_anchor.attribute_orientation
location.segment_anchor_side
location.accessors
location.political_geometry
location.alternate_geometry
location.within_location_ref.partition_name
location.within_location_ref.identifier
location.bounding_box
location.level_info
0
17302684
[{'ref': {'partition': '17302684', 'identifier...
True
True
23060936-27869540-27869541
here:cm:namedplace:27869542
[{'text': {'value': 'Chatham Islands', 'langua...
city
23060936-27869540-27869541
here:cm:namedplace-loc:27869542
...
[]
RELATIVE_DIRECTION_UNKNOWN
SIDE_UNKNOWN
<NA>
[]
[]
1
17302684
[{'ref': {'partition': '17302684', 'identifier...
True
True
23060936-27869540-27869541
here:cm:namedplace:27869549
[{'text': {'value': '8016', 'language': ''}, '...
postal_code
23060936-27869540-27869541
here:cm:namedplace-loc:27869549
...
[]
RELATIVE_DIRECTION_UNKNOWN
SIDE_UNKNOWN
<NA>
[]
[]
2 rows × 25 columns
Python
### Construct a new Reference by giving partition and identifier.
place_ref = make_ref("23060936", "here:cm:namedplace:23060936")
Python
place_admin_boundary_atts = segment_admin_boundary.get_referencing("17302684", "segment_admin_boundary",
"place", place_ref)
place_admin_boundary_atts
partition_id
segments
forward
backward
place_ref.partition
place_ref.identifier
place_name
admin_category
location.partition_id
location.location_id
...
location.segment_anchor.oriented_segment_ref
location.segment_anchor.attribute_orientation
location.segment_anchor_side
location.accessors
location.political_geometry
location.alternate_geometry
location.within_location_ref.partition_name
location.within_location_ref.identifier
location.bounding_box
location.level_info
0
17302684
[{'ref': {'partition': '17302684', 'identifier...
True
True
23060936
here:cm:namedplace:23060936
[{'text': {'value': 'New Zealand', 'language':...
country
23060936
here:cm:namedplace-loc:23060936
...
[]
RELATIVE_DIRECTION_UNKNOWN
SIDE_UNKNOWN
<NA>
[]
[]
1 rows × 25 columns
This binding associates segment with environmental zones.
Layer Ids - environmental_zones , navigation-attributes
Python
ezc = hmc.environmental_zone_conditions
display(ezc)
<here.content.hmc2.environmental_zone_conditions.EnvironmentalZoneConditions at 0x7f8d2e53b640>
Python
types_to_df(ezc.object_types())
Data Class
Index by partition
Index by ID
Ref Types
Type
segment_to_environmental_zone
here.content.hmc2.environmental_zone_condition...
True
False
location, segment
Python
data_ezc = ezc.get(partition = 23618402, object_type = 'segment_to_environmental_zone')
data_ezc.head(2)
segment_ref.ref.partition
segment_ref.ref.identifier
segment_ref.inverted
segment_ref.offset.start
segment_ref.offset.end
forward
backward
applies_to.automobiles
applies_to.buses
applies_to.taxis
...
zone.name
zone.info.description
zone.info.website.value
zone.info.website.language
zone.info.version_date
zone.info.extent_date
zone.info.country
zone.vehicle_class
zone.environmental_badge
zone.location_ref
partition_id
23618402
23618402
here:cm:segment:100005273
False
<NA>
<NA>
True
True
True
True
True
...
[{'text': {'value': 'Berlin Umweltzone', 'lang...
[{'value': 'Die Umweltzone der Stadt Berlin is...
https://www.berlin.de/senuvk/umwelt/luftqualit...
2019-05-09
2019-01-01
GERMANY
[{'vehicle_attributes': {'category': 'AUTO', '...
[{'badge_type': 'DEU_GREEN_STICKER', 'zone_acc...
[{'partition': '23618400', 'identifier': 'here...
23618402
23618402
here:cm:segment:100005286
False
<NA>
<NA>
True
True
True
True
True
...
[{'text': {'value': 'Berlin Umweltzone', 'lang...
[{'value': 'Die Umweltzone der Stadt Berlin is...
https://www.berlin.de/senuvk/umwelt/luftqualit...
2019-05-09
2019-01-01
GERMANY
[{'vehicle_attributes': {'category': 'AUTO', '...
[{'badge_type': 'DEU_GREEN_STICKER', 'zone_acc...
[{'partition': '23618400', 'identifier': 'here...
2 rows × 29 columns
Python
data_ezc.iloc[0]['zone.location_ref']
[{'partition': '23618400', 'identifier': 'here:cm:carto-loc:1415962522'}]
Python
### Construct a new Reference by giving partition and identifier.
ref = make_ref(23618402, "here:cm:segment:92642459")
Python
data = ezc.get_referencing(partition = 23618402,
object_type = 'segment_to_environmental_zone',
ref_type='segment',
referenced_obj=ref)
data
partition_id
segment_ref.ref.partition
segment_ref.ref.identifier
segment_ref.inverted
segment_ref.offset.start
segment_ref.offset.end
forward
backward
applies_to.automobiles
applies_to.buses
...
zone.name
zone.info.description
zone.info.website.value
zone.info.website.language
zone.info.version_date
zone.info.extent_date
zone.info.country
zone.vehicle_class
zone.environmental_badge
zone.location_ref
0
23618402
23618402
here:cm:segment:92642459
False
<NA>
0.512538
True
True
True
True
...
[{'text': {'value': 'Berlin Umweltzone', 'lang...
[{'value': 'Die Umweltzone der Stadt Berlin is...
https://www.berlin.de/senuvk/umwelt/luftqualit...
2019-05-09
2019-01-01
GERMANY
[{'vehicle_attributes': {'category': 'AUTO', '...
[{'badge_type': 'DEU_GREEN_STICKER', 'zone_acc...
[{'partition': '23618400', 'identifier': 'here...
1
23618402
23618402
here:cm:segment:92642459
False
0.512538
<NA>
True
True
True
True
...
[{'text': {'value': 'Berlin Umweltzone', 'lang...
[{'value': 'Die Umweltzone der Stadt Berlin is...
https://www.berlin.de/senuvk/umwelt/luftqualit...
2019-05-09
2019-01-01
GERMANY
[{'vehicle_attributes': {'category': 'AUTO', '...
[{'badge_type': 'DEU_GREEN_STICKER', 'zone_acc...
[{'partition': '23618400', 'identifier': 'here...
2 rows × 30 columns
Python
### Construct a new Reference by giving partition and identifier.
ref = make_ref(23618400, "here:cm:carto-loc:1415962522")
Python
data = ezc.get_referencing(partition = 23618402,
object_type = 'segment_to_environmental_zone',
ref_type='location',
referenced_obj=ref)
data.head(2)
partition_id
segment_ref.ref.partition
segment_ref.ref.identifier
segment_ref.inverted
segment_ref.offset.start
segment_ref.offset.end
forward
backward
applies_to.automobiles
applies_to.buses
...
zone.name
zone.info.description
zone.info.website.value
zone.info.website.language
zone.info.version_date
zone.info.extent_date
zone.info.country
zone.vehicle_class
zone.environmental_badge
zone.location_ref
0
23618402
23618402
here:cm:segment:100005273
False
<NA>
<NA>
True
True
True
True
...
[{'text': {'value': 'Berlin Umweltzone', 'lang...
[{'value': 'Die Umweltzone der Stadt Berlin is...
https://www.berlin.de/senuvk/umwelt/luftqualit...
2019-05-09
2019-01-01
GERMANY
[{'vehicle_attributes': {'category': 'AUTO', '...
[{'badge_type': 'DEU_GREEN_STICKER', 'zone_acc...
[{'partition': '23618400', 'identifier': 'here...
1
23618402
23618402
here:cm:segment:100005286
False
<NA>
<NA>
True
True
True
True
...
[{'text': {'value': 'Berlin Umweltzone', 'lang...
[{'value': 'Die Umweltzone der Stadt Berlin is...
https://www.berlin.de/senuvk/umwelt/luftqualit...
2019-05-09
2019-01-01
GERMANY
[{'vehicle_attributes': {'category': 'AUTO', '...
[{'badge_type': 'DEU_GREEN_STICKER', 'zone_acc...
[{'partition': '23618400', 'identifier': 'here...
2 rows × 30 columns
segment_ref.ref.partition 23618402
segment_ref.ref.identifier here:cm:segment:100005273
segment_ref.inverted False
segment_ref.offset.start <NA>
segment_ref.offset.end <NA>
forward True
backward True
applies_to.automobiles True
applies_to.buses True
applies_to.taxis True
applies_to.carpools True
applies_to.trucks True
applies_to.through_traffic True
applies_to.deliveries True
applies_to.pedestrians False
applies_to.emergency_vehicles False
applies_to.motorcycles False
applies_to.bicycles False
zone.identifier here:cm:envzone:2
zone.name [{'text': {'value': 'Berlin Umweltzone', 'lang...
zone.info.description [{'value': 'Die Umweltzone der Stadt Berlin is...
zone.info.website.value https://www.berlin.de/senuvk/umwelt/luftqualit...
zone.info.website.language
zone.info.version_date 2019-05-09
zone.info.extent_date 2019-01-01
zone.info.country GERMANY
zone.vehicle_class [{'vehicle_attributes': {'category': 'AUTO', '...
zone.environmental_badge [{'badge_type': 'DEU_GREEN_STICKER', 'zone_acc...
zone.location_ref [{'partition': '23618400', 'identifier': 'here...
Name: 23618402, dtype: object
This binding associates segment with administrative boundary.
Layer Id - address-attributes , street-names
Python
segment_street_names = hmc.segment_street_names
Python
segment_street = segment_street_names.get(["20371958","17434043"], "street_section")
segment_street.head(2)
segments
forward
backward
attribute.side
attribute.property
attribute.street_section
0
[{'ref': {'partition': '20371958', 'identifier...
True
True
BOTH_SIDES
[EXPLICATABLE, NAME_ON_ROADSIGN]
StreetSection(partition_id='20317122-23489553'...
1
[{'ref': {'partition': '20371958', 'identifier...
True
True
BOTH_SIDES
[EXPLICATABLE, NAME_ON_ROADSIGN]
StreetSection(partition_id='20317122-23489553'...
Python
segment_street = segment_street_names.get(["20371958","17434043"], "address_range")
segment_street.head(2)
segments
forward
backward
attribute.address_range_type
attribute.format
attribute.side
attribute.postal_mapping
attribute.address_type
attribute.scheme
attribute.first_house_number
attribute.last_house_number
attribute.street_section
0
[{'ref': {'partition': '20371958', 'identifier...
True
True
LOGICAL
UNADDRESSED
LEFT_SIDE
[{'match_category': 'ADDRESS_RANGE_MATCH', 'fi...
BASE
ADDRESS_SCHEME_UNKNOWN
[StreetSection(partition_id='20317122-23489553...
1
[{'ref': {'partition': '20371958', 'identifier...
True
True
LOGICAL
UNADDRESSED
LEFT_SIDE
[{'match_category': 'ADDRESS_RANGE_MATCH', 'fi...
BASE
ADDRESS_SCHEME_UNKNOWN
[StreetSection(partition_id='20317122-23489553...
This binding associates Topology Geometry with ADAS layer.
Layer Id - ADAS Attributes
Python
adas_attributes = hmc.adas_attributes
partition_id = ['18508594','18608750']
types_to_df(adas_attributes.object_types())
Data Class
Index by partition
Index by ID
Ref Types
Type
curvature_heading
here.content.hmc2.adas_attributes.CurvatureHea...
True
False
None
elevation
here.content.hmc2.adas_attributes.Elevation
True
False
None
slope
here.content.hmc2.adas_attributes.Slope
True
False
None
link_accuracy
here.content.hmc2.adas_attributes.LinkAccuracy
True
False
None
built_up_area_road
here.content.hmc2.adas_attributes.BuiltupAreaRoad
True
False
None
Python
curvature_heading_attribute = adas_attributes.get(partition_id, 'curvature_heading')
curvature_heading_attribute.head(2)
Python
slope_attribute = adas_attributes.get(partition_id, 'slope')
slope_attribute.head(2)
segment_anchors
slope
accuracy
partition_id
18508594
[SegmentAnchor(partition_id='18508594', orient...
-21000
BASIC
18508594
[SegmentAnchor(partition_id='18508594', orient...
-20994
BASIC
Python
elevation_attribute = adas_attributes.get(partition_id, 'elevation')
elevation_attribute.head(2)
segment_anchors
elevation
accuracy
signed_elevation
node_anchors
partition_id
18508594
<NA>
2335
BASIC
2335
[Node(partition_id='18508594', node_id='here:c...
18508594
[SegmentAnchor(partition_id='18508594', orient...
2343
BASIC
2343
<NA>
Python
link_accuracy_attribute = adas_attributes.get(partition_id, 'link_accuracy')
link_accuracy_attribute.head(2)
segment_anchors
link_accuracy
partition_id
18508594
[SegmentAnchor(partition_id='18508594', orient...
2
18508594
[SegmentAnchor(partition_id='18508594', orient...
4
Python
built_up_area_road_attribute = adas_attributes.get(partition_id, 'built_up_area_road')
built_up_area_road_attribute.head(2)
This binding associates Composite Road Attribute with ADAS layer.
Layer Id - Composite Road Attributes
Python
composite_road_attributes = hmc.composite_road_attributes
partition_id = ['23195507','23462802','23462789']
types_to_df(composite_road_attributes.object_types())
Data Class
Index by partition
Index by ID
Ref Types
Type
complex_road_attribute
here.content.hmc2.composite_road_attributes.Co...
True
True
None
complex_intersection_attribute
here.content.hmc2.composite_road_attributes.Co...
True
True
None
complex_object_attribute
here.content.hmc2.composite_road_attributes.Co...
True
True
None
Python
complex_object_attribute = composite_road_attributes.get(partition_id, 'complex_object_attribute')
complex_object_attribute
node_anchors
segment_anchors
name
valid_unnamed
anchor_point.latitude
anchor_point.longitude
anchor_point.z_level
anchor_point.elevation
partition_id
complex_object_id
23195507
here:cm:crf:1493708652
<NA>
[SegmentAnchor(partition_id='23195507', orient...
<NA>
True
21.58096
39.16535
0
0.0
here:cm:crf:1497800168
<NA>
[SegmentAnchor(partition_id='23195507', orient...
<NA>
True
21.59759
39.15982
0
0.0
here:cm:crf:1499287692
<NA>
[SegmentAnchor(partition_id='23195507', orient...
<NA>
True
21.56455
39.17078
0
0.0
here:cm:crf:1504000399
<NA>
[SegmentAnchor(partition_id='23195507', orient...
<NA>
True
21.54156
39.15534
0
0.0
here:cm:crf:1504006567
<NA>
[SegmentAnchor(partition_id='23195507', orient...
<NA>
True
21.57577
39.17977
0
0.0
here:cm:crf:1519617199
<NA>
[SegmentAnchor(partition_id='23195507', orient...
<NA>
True
21.61966
39.16551
0
0.0
here:cm:crf:1650073602
<NA>
[SegmentAnchor(partition_id='23195507', orient...
<NA>
True
21.57973
39.19850
0
0.0
here:cm:crf:1650125112
<NA>
[SegmentAnchor(partition_id='23195507', orient...
<NA>
True
21.56808
39.18278
0
0.0
here:cm:crf:1650131595
<NA>
[SegmentAnchor(partition_id='23195507', orient...
<NA>
True
21.61969
39.18584
0
0.0
here:cm:crf:1650133452
<NA>
[SegmentAnchor(partition_id='23195507', orient...
<NA>
True
21.59982
39.19228
0
0.0
here:cm:crf:1650144410
<NA>
[SegmentAnchor(partition_id='23195507', orient...
<NA>
True
21.55941
39.18735
0
0.0
here:cm:crf:1667168619
<NA>
[SegmentAnchor(partition_id='23195507', orient...
<NA>
True
21.58440
39.17726
0
0.0
here:cm:crf:1677169493
<NA>
[SegmentAnchor(partition_id='23195507', orient...
<NA>
True
21.61388
39.15552
0
0.0
here:cm:crf:1684284225
<NA>
[SegmentAnchor(partition_id='23195507', orient...
<NA>
True
21.56041
39.19229
0
0.0
here:cm:crf:1722897456
<NA>
[SegmentAnchor(partition_id='23195507', orient...
<NA>
True
21.55587
39.17373
0
0.0
here:cm:crf:1722897457
<NA>
[SegmentAnchor(partition_id='23195507', orient...
<NA>
True
21.58945
39.17534
0
0.0
here:cm:crf:544894463
<NA>
[SegmentAnchor(partition_id='23195507', orient...
<NA>
True
21.54407
39.14448
0
0.0
here:cm:crf:722159622
<NA>
[SegmentAnchor(partition_id='23195507', orient...
<NA>
True
21.57475
39.14330
0
0.0
here:cm:crf:722562744
<NA>
[SegmentAnchor(partition_id='23195507', orient...
<NA>
True
21.61806
39.17726
0
0.0
here:cm:crf:725863472
<NA>
[SegmentAnchor(partition_id='23195507', orient...
<NA>
True
21.60112
39.17159
0
0.0
here:cm:crf:725904596
<NA>
[SegmentAnchor(partition_id='23195507', orient...
<NA>
True
21.54449
39.19048
0
0.0
23462802
here:cm:crf:1578840808
<NA>
[SegmentAnchor(partition_id='23462802', orient...
<NA>
True
24.76493
46.84140
0
0.0
here:cm:crf:1681059910
<NA>
[SegmentAnchor(partition_id='23462802', orient...
<NA>
True
24.77620
46.77654
0
0.0
here:cm:crf:1720328913
<NA>
[SegmentAnchor(partition_id='23462802', orient...
<NA>
True
24.77734
46.83228
0
0.0
here:cm:crf:544892244
<NA>
[SegmentAnchor(partition_id='23462802', orient...
[text {\n value: "Demashq Square"\n}\nname_ty...
False
24.71451
46.76177
0
0.0
here:cm:crf:736990579
<NA>
[SegmentAnchor(partition_id='23462802', orient...
<NA>
True
24.72163
46.77325
0
0.0
here:cm:crf:737020957
<NA>
[SegmentAnchor(partition_id='23462802', orient...
<NA>
True
24.73022
46.78705
0
0.0
here:cm:crf:737090233
<NA>
[SegmentAnchor(partition_id='23462802', orient...
<NA>
True
24.73816
46.79983
0
0.0
23462789
here:cm:crf:1481339727
<NA>
[SegmentAnchor(partition_id='23462789', orient...
<NA>
True
24.62703
46.69214
0
0.0
here:cm:crf:1500104605
<NA>
[SegmentAnchor(partition_id='23462789', orient...
<NA>
True
24.67550
46.70346
0
0.0
here:cm:crf:1501861080
<NA>
[SegmentAnchor(partition_id='23462789', orient...
<NA>
True
24.65659
46.67867
0
0.0
here:cm:crf:1503889262
<NA>
[SegmentAnchor(partition_id='23462789', orient...
<NA>
True
24.63702
46.69261
0
0.0
here:cm:crf:1503889263
<NA>
[SegmentAnchor(partition_id='23462789', orient...
<NA>
True
24.64139
46.69289
0
0.0
here:cm:crf:1573974308
<NA>
[SegmentAnchor(partition_id='23462789', orient...
<NA>
True
24.62201
46.74738
0
0.0
here:cm:crf:1623389228
<NA>
[SegmentAnchor(partition_id='23462789', orient...
<NA>
True
24.65028
46.70229
0
0.0
here:cm:crf:1659713397
<NA>
[SegmentAnchor(partition_id='23462789', orient...
<NA>
True
24.64065
46.75989
0
0.0
here:cm:crf:1672958913
<NA>
[SegmentAnchor(partition_id='23462789', orient...
<NA>
True
24.69360
46.72322
0
0.0
here:cm:crf:38870755
<NA>
[SegmentAnchor(partition_id='23462789', orient...
<NA>
True
24.65039
46.69375
0
0.0
here:cm:crf:38882882
<NA>
[SegmentAnchor(partition_id='23462789', orient...
<NA>
True
24.65003
46.68995
0
0.0
here:cm:crf:544886286
<NA>
[SegmentAnchor(partition_id='23462789', orient...
<NA>
True
24.69506
46.68057
0
0.0
here:cm:crf:544886620
<NA>
[SegmentAnchor(partition_id='23462789', orient...
<NA>
True
24.67872
46.68881
0
0.0
here:cm:crf:544886680
<NA>
[SegmentAnchor(partition_id='23462789', orient...
<NA>
True
24.63101
46.70473
0
0.0
here:cm:crf:544886681
<NA>
[SegmentAnchor(partition_id='23462789', orient...
<NA>
True
24.62886
46.70501
0
0.0
here:cm:crf:544892561
<NA>
[SegmentAnchor(partition_id='23462789', orient...
[text {\n value: "ميدان النقل"\n}\nname_type:...
False
24.68823
46.71257
0
0.0
here:cm:crf:544892572
<NA>
[SegmentAnchor(partition_id='23462789', orient...
<NA>
True
24.68336
46.69967
0
0.0
here:cm:crf:544892576
<NA>
[SegmentAnchor(partition_id='23462789', orient...
<NA>
True
24.68016
46.69202
0
0.0
here:cm:crf:551627028
<NA>
[SegmentAnchor(partition_id='23462789', orient...
[text {\n value: "Al Amal Square"\n}\nname_ty...
False
24.64722
46.73287
0
0.0
here:cm:crf:551627932
<NA>
[SegmentAnchor(partition_id='23462789', orient...
<NA>
True
24.64657
46.68772
0
0.0
here:cm:crf:710121064
<NA>
[SegmentAnchor(partition_id='23462789', orient...
<NA>
True
24.66694
46.71817
0
0.0
here:cm:crf:710121148
<NA>
[SegmentAnchor(partition_id='23462789', orient...
<NA>
True
24.61106
46.67182
0
0.0
here:cm:crf:710175213
<NA>
[SegmentAnchor(partition_id='23462789', orient...
<NA>
True
24.65596
46.71717
0
0.0
here:cm:crf:710175338
<NA>
[SegmentAnchor(partition_id='23462789', orient...
<NA>
True
24.68626
46.70660
0
0.0
here:cm:crf:710183532
<NA>
[SegmentAnchor(partition_id='23462789', orient...
[text {\n value: "ميدان مقديشو"\n}\nname_type...
False
24.63959
46.73664
0
0.0
here:cm:crf:710190559
<NA>
[SegmentAnchor(partition_id='23462789', orient...
<NA>
True
24.66818
46.69582
0
0.0
here:cm:crf:736822102
<NA>
[SegmentAnchor(partition_id='23462789', orient...
<NA>
True
24.66088
46.68495
0
0.0
here:cm:crf:736944566
<NA>
[SegmentAnchor(partition_id='23462789', orient...
<NA>
True
24.67539
46.67818
0
0.0
here:cm:crf:737212476
<NA>
[SegmentAnchor(partition_id='23462789', orient...
<NA>
True
24.68831
46.75429
0
0.0
here:cm:crf:739486354
<NA>
[SegmentAnchor(partition_id='23462789', orient...
<NA>
True
24.63000
46.71737
0
0.0
here:cm:crf:739486355
<NA>
[SegmentAnchor(partition_id='23462789', orient...
<NA>
True
24.63796
46.71781
0
0.0
here:cm:crf:739495774
<NA>
[SegmentAnchor(partition_id='23462789', orient...
<NA>
True
24.64483
46.70301
0
0.0
Python
complex_intersection_attribute = composite_road_attributes.get(partition_id, 'complex_intersection_attribute')
complex_intersection_attribute
node_anchors
segment_anchors
partition_id
complex_intersection_id
23195507
here:cm:crf:1410280611
[Node(partition_id='23195507', node_id='here:c...
[SegmentAnchor(partition_id='23195507', orient...
here:cm:crf:1410310487
[Node(partition_id='23195507', node_id='here:c...
[SegmentAnchor(partition_id='23195507', orient...
here:cm:crf:1418600386
<NA>
[SegmentAnchor(partition_id='23195507', orient...
here:cm:crf:1457805913
<NA>
[SegmentAnchor(partition_id='23195507', orient...
here:cm:crf:1457807146
[Node(partition_id='23195507', node_id='here:c...
[SegmentAnchor(partition_id='23195507', orient...
...
...
...
...
23462789
here:cm:crf:740764272
[Node(partition_id='23462789', node_id='here:c...
<NA>
here:cm:crf:740764273
<NA>
[SegmentAnchor(partition_id='23462789', orient...
here:cm:crf:740764274
<NA>
[SegmentAnchor(partition_id='23462789', orient...
here:cm:crf:740764275
<NA>
[SegmentAnchor(partition_id='23462789', orient...
here:cm:crf:741489237
<NA>
[SegmentAnchor(partition_id='23462789', orient...
9343 rows × 2 columns
Python
complex_road_attribute = composite_road_attributes.get(partition_id,'complex_road_attribute')
complex_road_attribute
segment_anchors
start_complex_intersection_ref.identifier
start_complex_intersection_ref.partition_name
end_complex_intersection_ref.identifier
end_complex_intersection_ref.partition_name
partition_id
complex_road_id
23195507
here:cm:crf:1410280612
[SegmentAnchor(partition_id='23195507', orient...
here:cm:crf:704229234
here:cm:crf:1410280611
here:cm:crf:1457805915
[SegmentAnchor(partition_id='23195507', orient...
here:cm:crf:1457805913
here:cm:crf:544887755
here:cm:crf:1457807153
[SegmentAnchor(partition_id='23195507', orient...
here:cm:crf:1457807146
here:cm:crf:734900193
here:cm:crf:1457807154
[SegmentAnchor(partition_id='23195507', orient...
here:cm:crf:1497853257
here:cm:crf:1457807146
here:cm:crf:1457807155
[SegmentAnchor(partition_id='23195507', orient...
here:cm:crf:1457807148
here:cm:crf:544894522
...
...
...
...
...
...
...
23462789
here:cm:crf:740764278
[SegmentAnchor(partition_id='23462789', orient...
here:cm:crf:740764271
here:cm:crf:740764274
here:cm:crf:740764279
[SegmentAnchor(partition_id='23462789', orient...
here:cm:crf:740764272
here:cm:crf:740764275
here:cm:crf:741489238
[SegmentAnchor(partition_id='23462789', orient...
here:cm:crf:741489237
here:cm:crf:544869158
here:cm:crf:741489239
[SegmentAnchor(partition_id='23462789', orient...
here:cm:crf:544869165
here:cm:crf:741489237
here:cm:crf:743367541
[SegmentAnchor(partition_id='23462789', orient...
here:cm:crf:1672893600
here:cm:crf:544884808
9424 rows × 5 columns
To run the notebook on your local machine, please refer to link below.
Python
url = os.path.abspath("")
notebook_name = 'hmc.ipynb'
notebook = FileLink(f"{url}/{notebook_name}", result_html_prefix="Click here to download: ")
display(notebook)
Click here to download: /builds/sdk/pysdk-nagini/dev_guide/notebooks/hmc.ipynb