OSM PBF Loader¶
OSMPbfLoader can really quickly parse full OSM extract in the form of *.osm.pbf file.
It can download and parse a lot of features much faster than the OSMOnlineLoader, but it's much more useful when a lot of different features are required at once (like when using predefined filters).
When only a single or few features are needed, OSMOnlineLoader might be a better choice, since OSMPbfLoader will use a full extract of all features in a given region and will have to iterate over all of them.
In [1]:
Copied!
import geopandas as gpd
from shapely.geometry import Point, box
from srai.constants import REGIONS_INDEX, WGS84_CRS
from srai.geometry import buffer_geometry
from srai.loaders.osm_loaders import OSMPbfLoader
from srai.loaders.osm_loaders.filters import GEOFABRIK_LAYERS, HEX2VEC_FILTER
from srai.loaders.osm_loaders.filters.popular import get_popular_tags
from srai.regionalizers import geocode_to_region_gdf
import geopandas as gpd
from shapely.geometry import Point, box
from srai.constants import REGIONS_INDEX, WGS84_CRS
from srai.geometry import buffer_geometry
from srai.loaders.osm_loaders import OSMPbfLoader
from srai.loaders.osm_loaders.filters import GEOFABRIK_LAYERS, HEX2VEC_FILTER
from srai.loaders.osm_loaders.filters.popular import get_popular_tags
from srai.regionalizers import geocode_to_region_gdf
Using OSMPbfLoader to download data for a specific area¶
Download all features from HEX2VEC_FILTER in Warsaw, Poland¶
In [2]:
Copied!
loader = OSMPbfLoader()
warsaw_gdf = geocode_to_region_gdf("Warsaw, Poland")
warsaw_features_gdf = loader.load(warsaw_gdf, HEX2VEC_FILTER)
warsaw_features_gdf
loader = OSMPbfLoader()
warsaw_gdf = geocode_to_region_gdf("Warsaw, Poland")
warsaw_features_gdf = loader.load(warsaw_gdf, HEX2VEC_FILTER)
warsaw_features_gdf
/opt/hostedtoolcache/Python/3.10.15/x64/lib/python3.10/site-packages/srai/loaders/osm_loaders/osm_pbf_loader.py:128: FutureWarning: Use `convert_geometry_to_geodataframe` instead. Deprecated since 0.8.1 version. features_gdf = pbf_reader.get_features_gdf_from_geometry(
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Finished operation in 0:02:03
Out[2]:
| geometry | aeroway | amenity | building | healthcare | historic | landuse | leisure | military | natural | office | shop | sport | tourism | water | waterway | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| feature_id | ||||||||||||||||
| node/33238753 | POINT (20.92711 52.33046) | None | ferry_terminal | None | None | None | None | None | None | None | None | None | None | None | None | None |
| node/38202104 | POINT (21.04682 52.12049) | None | None | None | None | None | None | None | None | None | None | None | None | attraction | None | None |
| node/38202108 | POINT (21.03313 52.12883) | None | None | None | None | memorial | None | None | None | None | None | None | None | None | None | None |
| node/38449976 | POINT (21.04432 52.13665) | None | None | None | None | None | None | None | None | None | None | None | None | viewpoint | None | None |
| node/38451821 | POINT (21.04178 52.11624) | None | shelter | None | None | None | None | None | None | None | None | None | None | None | None | None |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| relation/4428446 | POLYGON ((21.17515 52.21796, 21.17515 52.21798... | None | None | hospital | None | None | None | None | None | None | None | None | None | None | None | None |
| relation/5322563 | POLYGON ((20.98298 52.21378, 20.98300 52.21363... | None | None | yes | None | None | None | None | None | None | None | None | None | None | None | None |
| relation/4771561 | POLYGON ((21.01708 52.20066, 21.01710 52.20062... | None | None | None | None | None | None | track | None | None | None | None | running | None | None | None |
| relation/4428905 | POLYGON ((21.19104 52.20563, 21.19104 52.20565... | None | None | hospital | None | None | None | None | None | None | None | None | None | None | None | None |
| relation/5390392 | MULTIPOLYGON (((21.08702 52.21523, 21.08688 52... | None | None | None | None | None | forest | None | None | wood | None | None | None | None | None | None |
326330 rows × 16 columns
Plot features¶
Inspired by prettymaps
In [3]:
Copied!
clipped_features_gdf = warsaw_features_gdf.clip(warsaw_gdf.geometry.unary_union)
clipped_features_gdf = warsaw_features_gdf.clip(warsaw_gdf.geometry.unary_union)
In [4]:
Copied!
ax = warsaw_gdf.plot(color="lavender", figsize=(16, 16))
# plot water
clipped_features_gdf.dropna(subset=["water", "waterway"], how="all").plot(
ax=ax, color="deepskyblue"
)
# plot greenery
clipped_features_gdf[
clipped_features_gdf["landuse"].isin(
["grass", "orchard", "flowerbed", "forest", "greenfield", "meadow"]
)
].plot(ax=ax, color="mediumseagreen")
# plot buildings
clipped_features_gdf.dropna(subset=["building"], how="all").plot(
ax=ax, color="dimgray", markersize=0.1
)
xmin, ymin, xmax, ymax = warsaw_gdf.total_bounds
ax.set_xlim(xmin, xmax)
ax.set_ylim(ymin, ymax)
ax.set_axis_off()
ax = warsaw_gdf.plot(color="lavender", figsize=(16, 16))
# plot water
clipped_features_gdf.dropna(subset=["water", "waterway"], how="all").plot(
ax=ax, color="deepskyblue"
)
# plot greenery
clipped_features_gdf[
clipped_features_gdf["landuse"].isin(
["grass", "orchard", "flowerbed", "forest", "greenfield", "meadow"]
)
].plot(ax=ax, color="mediumseagreen")
# plot buildings
clipped_features_gdf.dropna(subset=["building"], how="all").plot(
ax=ax, color="dimgray", markersize=0.1
)
xmin, ymin, xmax, ymax = warsaw_gdf.total_bounds
ax.set_xlim(xmin, xmax)
ax.set_ylim(ymin, ymax)
ax.set_axis_off()
Download all features from popular tags based on OSMTagInfo in Vienna, Austria¶
In [5]:
Copied!
popular_tags = get_popular_tags(in_wiki_only=True)
num_keys = len(popular_tags)
f"Unique keys: {num_keys}."
popular_tags = get_popular_tags(in_wiki_only=True)
num_keys = len(popular_tags)
f"Unique keys: {num_keys}."
Out[5]:
'Unique keys: 354.'
In [6]:
Copied!
{k: popular_tags[k] for k in list(popular_tags)[:10]}
{k: popular_tags[k] for k in list(popular_tags)[:10]}
Out[6]:
{'4wd_only': ['yes'],
'LandPro08:reviewed': ['no'],
'abandoned': ['yes'],
'abandoned:railway': ['rail'],
'abutters': ['residential'],
'access': ['agricultural',
'customers',
'delivery',
'designated',
'destination',
'forestry',
'no',
'permissive',
'permit',
'private',
'unknown',
'yes'],
'addr:TW:dataset': ['137998'],
'addr:country': ['CZ', 'DE', 'RU', 'US'],
'addr:state': ['AZ',
'CA',
'CO',
'CT',
'FL',
'IN',
'KY',
'MD',
'ME',
'NC',
'NJ',
'NY',
'PA',
'TX'],
'admin_level': ['10', '11', '2', '4', '5', '6', '7', '8', '9']}
In [7]:
Copied!
vienna_center_circle = buffer_geometry(Point(16.37009, 48.20931), meters=1000)
vienna_center_circle_gdf = gpd.GeoDataFrame(
geometry=[vienna_center_circle],
crs=WGS84_CRS,
index=gpd.pd.Index(data=["Vienna"], name=REGIONS_INDEX),
)
vienna_center_circle = buffer_geometry(Point(16.37009, 48.20931), meters=1000)
vienna_center_circle_gdf = gpd.GeoDataFrame(
geometry=[vienna_center_circle],
crs=WGS84_CRS,
index=gpd.pd.Index(data=["Vienna"], name=REGIONS_INDEX),
)
In [8]:
Copied!
loader = OSMPbfLoader()
vienna_features_gdf = loader.load(vienna_center_circle_gdf, popular_tags)
vienna_features_gdf
loader = OSMPbfLoader()
vienna_features_gdf = loader.load(vienna_center_circle_gdf, popular_tags)
vienna_features_gdf
/opt/hostedtoolcache/Python/3.10.15/x64/lib/python3.10/site-packages/srai/loaders/osm_loaders/osm_pbf_loader.py:128: FutureWarning: Use `convert_geometry_to_geodataframe` instead. Deprecated since 0.8.1 version. features_gdf = pbf_reader.get_features_gdf_from_geometry(
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/opt/hostedtoolcache/Python/3.10.15/x64/lib/python3.10/site-packages/quackosm/pbf_file_reader.py:2432: UserWarning: Select clause contains more than 100 columns (found 354 columns). Query might fail with insufficient memory resources. Consider applying more restrictive OsmTagsFilter for parsing. warnings.warn(
Finished operation in 0:05:28
Out[8]:
| geometry | abandoned | access | admin_level | advertising | amenity | area:highway | artwork_type | atm | barrier | ... | tunnel | type | usage | vehicle | vending | waste | water | water_source | waterway | wheelchair | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| feature_id | |||||||||||||||||||||
| node/685038 | POINT (16.37080 48.21754) | None | None | None | None | None | None | None | None | None | ... | None | None | None | None | None | None | None | None | None | None |
| node/685044 | POINT (16.37657 48.21228) | None | None | None | None | None | None | None | None | None | ... | None | None | None | None | None | None | None | None | None | None |
| node/685045 | POINT (16.37838 48.21172) | None | None | None | None | None | None | None | None | None | ... | None | None | None | None | None | None | None | None | None | yes |
| node/685048 | POINT (16.38287 48.21137) | None | None | None | None | None | None | None | None | None | ... | None | None | None | None | None | None | None | None | None | None |
| node/293170161 | POINT (16.37311 48.21172) | None | yes | None | None | parking | None | None | None | None | ... | None | None | None | None | None | None | None | None | None | no |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| relation/9273246 | POLYGON ((16.36425 48.20775, 16.36429 48.20777... | None | None | None | None | None | None | None | None | None | ... | None | multipolygon | None | None | None | None | None | None | None | None |
| relation/9273247 | POLYGON ((16.36425 48.21200, 16.36424 48.21208... | None | None | None | None | None | None | None | None | None | ... | None | multipolygon | None | None | None | None | None | None | None | None |
| relation/13626346 | POLYGON ((16.38033 48.21257, 16.38028 48.21266... | None | None | None | None | None | None | None | None | None | ... | None | multipolygon | None | None | None | None | None | None | None | None |
| relation/13872064 | POLYGON ((16.36302 48.21025, 16.36298 48.21024... | None | None | None | None | None | None | None | None | None | ... | None | multipolygon | None | None | None | None | None | None | None | None |
| relation/13872065 | POLYGON ((16.36263 48.21043, 16.36264 48.21043... | None | None | None | None | None | None | None | None | None | ... | None | multipolygon | None | None | None | None | None | None | None | None |
22650 rows × 189 columns
Plot features¶
Uses default preset colours from prettymaps
In [9]:
Copied!
clipped_vienna_features_gdf = vienna_features_gdf.clip(vienna_center_circle)
clipped_vienna_features_gdf = vienna_features_gdf.clip(vienna_center_circle)
In [10]:
Copied!
ax = vienna_center_circle_gdf.plot(color="#F2F4CB", figsize=(16, 16))
# plot water
clipped_vienna_features_gdf.dropna(subset=["water", "waterway"], how="all").plot(
ax=ax, color="#a8e1e6"
)
# plot streets
clipped_vienna_features_gdf.dropna(subset=["highway"], how="all").plot(
ax=ax, color="#475657", markersize=0.1
)
# plot buildings
clipped_vienna_features_gdf.dropna(subset=["building"], how="all").plot(ax=ax, color="#FF5E5B")
# plot parkings
clipped_vienna_features_gdf[
(clipped_vienna_features_gdf["amenity"] == "parking")
| (clipped_vienna_features_gdf["highway"] == "pedestrian")
].plot(ax=ax, color="#2F3737", markersize=0.1)
# plot greenery
clipped_vienna_features_gdf[
clipped_vienna_features_gdf["landuse"].isin(
["grass", "orchard", "flowerbed", "forest", "greenfield", "meadow"]
)
].plot(ax=ax, color="#8BB174")
xmin, ymin, xmax, ymax = vienna_center_circle_gdf.total_bounds
ax.set_xlim(xmin, xmax)
ax.set_ylim(ymin, ymax)
ax.set_axis_off()
ax = vienna_center_circle_gdf.plot(color="#F2F4CB", figsize=(16, 16))
# plot water
clipped_vienna_features_gdf.dropna(subset=["water", "waterway"], how="all").plot(
ax=ax, color="#a8e1e6"
)
# plot streets
clipped_vienna_features_gdf.dropna(subset=["highway"], how="all").plot(
ax=ax, color="#475657", markersize=0.1
)
# plot buildings
clipped_vienna_features_gdf.dropna(subset=["building"], how="all").plot(ax=ax, color="#FF5E5B")
# plot parkings
clipped_vienna_features_gdf[
(clipped_vienna_features_gdf["amenity"] == "parking")
| (clipped_vienna_features_gdf["highway"] == "pedestrian")
].plot(ax=ax, color="#2F3737", markersize=0.1)
# plot greenery
clipped_vienna_features_gdf[
clipped_vienna_features_gdf["landuse"].isin(
["grass", "orchard", "flowerbed", "forest", "greenfield", "meadow"]
)
].plot(ax=ax, color="#8BB174")
xmin, ymin, xmax, ymax = vienna_center_circle_gdf.total_bounds
ax.set_xlim(xmin, xmax)
ax.set_ylim(ymin, ymax)
ax.set_axis_off()
Download all grouped features based on Geofabrik layers in New York, USA¶
In [11]:
Copied!
manhattan_bbox = box(-73.994551, 40.762396, -73.936872, 40.804239)
manhattan_bbox_gdf = gpd.GeoDataFrame(
geometry=[manhattan_bbox],
crs=WGS84_CRS,
index=gpd.pd.Index(data=["New York"], name=REGIONS_INDEX),
)
manhattan_bbox = box(-73.994551, 40.762396, -73.936872, 40.804239)
manhattan_bbox_gdf = gpd.GeoDataFrame(
geometry=[manhattan_bbox],
crs=WGS84_CRS,
index=gpd.pd.Index(data=["New York"], name=REGIONS_INDEX),
)
In [12]:
Copied!
loader = OSMPbfLoader()
new_york_features_gdf = loader.load(manhattan_bbox_gdf, GEOFABRIK_LAYERS)
new_york_features_gdf
loader = OSMPbfLoader()
new_york_features_gdf = loader.load(manhattan_bbox_gdf, GEOFABRIK_LAYERS)
new_york_features_gdf
/opt/hostedtoolcache/Python/3.10.15/x64/lib/python3.10/site-packages/srai/loaders/osm_loaders/osm_pbf_loader.py:128: FutureWarning: Use `convert_geometry_to_geodataframe` instead. Deprecated since 0.8.1 version. features_gdf = pbf_reader.get_features_gdf_from_geometry( /opt/hostedtoolcache/Python/3.10.15/x64/lib/python3.10/site-packages/quackosm/osm_extracts/__init__.py:592: GeometryNotCoveredWarning: Skipping extract because of low IoU value (geofabrik_north-america_us_us_new-jersey, 4.23e-05). warnings.warn(
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Out[12]:
| geometry | accommodation | buildings | catering | education | fuel_parking | health | highway_links | landuse | leisure | ... | public | railways | shopping | tourism | traffic | transport | very_small_roads | water | water_traffic | waterways | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| feature_id | |||||||||||||||||||||
| node/419359782 | POINT (-73.96752 40.80338) | None | None | None | None | amenity=bicycle_parking | None | None | None | None | ... | None | None | None | None | None | None | None | None | None | None |
| node/419359792 | POINT (-73.95336 40.77864) | None | None | None | None | amenity=bicycle_parking | None | None | None | None | ... | None | None | None | None | None | None | None | None | None | None |
| node/419359798 | POINT (-73.98258 40.77492) | None | None | None | None | amenity=bicycle_parking | None | None | None | None | ... | None | None | None | None | None | None | None | None | None | None |
| node/419359826 | POINT (-73.96511 40.76325) | None | None | None | None | amenity=bicycle_parking | None | None | None | None | ... | None | None | None | None | None | None | None | None | None | None |
| node/419359878 | POINT (-73.98453 40.76252) | None | None | None | None | amenity=bicycle_parking | None | None | None | None | ... | None | None | None | None | None | None | None | None | None | None |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| way/1291196630 | LINESTRING (-73.95834 40.80412, -73.95830 40.8... | None | None | None | None | None | None | None | None | None | ... | None | None | None | None | None | None | None | None | None | None |
| way/1291227846 | LINESTRING (-73.95674 40.80241, -73.95671 40.8... | None | None | None | None | None | None | None | None | None | ... | None | None | None | None | None | None | None | None | None | None |
| way/1291227847 | LINESTRING (-73.95671 40.80239, -73.95670 40.8... | None | None | None | None | None | None | None | None | None | ... | None | None | None | None | None | None | None | None | None | None |
| way/1291227848 | LINESTRING (-73.95664 40.80248, -73.95663 40.8... | None | None | None | None | None | None | None | None | None | ... | None | None | None | None | None | None | None | None | None | None |
| way/1291227849 | LINESTRING (-73.95663 40.80250, -73.95666 40.8... | None | None | None | None | None | None | None | None | None | ... | None | None | None | None | None | None | None | None | None | None |
49303 rows × 27 columns
Plot features¶
Inspired by https://snazzymaps.com/style/14889/flat-pale
In [13]:
Copied!
ax = manhattan_bbox_gdf.plot(color="#e7e7df", figsize=(16, 16))
# plot greenery
new_york_features_gdf[new_york_features_gdf["leisure"] == "leisure=park"].plot(
ax=ax, color="#bae5ce"
)
# plot water
new_york_features_gdf.dropna(subset=["water", "waterways"], how="all").plot(ax=ax, color="#c7eced")
# plot streets
new_york_features_gdf.dropna(subset=["paths_unsuitable_for_cars"], how="all").plot(
ax=ax, color="#e7e7df", linewidth=1
)
new_york_features_gdf.dropna(
subset=["very_small_roads", "highway_links", "minor_roads"], how="all"
).plot(ax=ax, color="#fff", linewidth=2)
new_york_features_gdf.dropna(subset=["major_roads"], how="all").plot(
ax=ax, color="#fac9a9", linewidth=3
)
# plot buildings
new_york_features_gdf.dropna(subset=["buildings"], how="all").plot(ax=ax, color="#cecebd")
xmin, ymin, xmax, ymax = manhattan_bbox_gdf.total_bounds
ax.set_xlim(xmin, xmax)
ax.set_ylim(ymin, ymax)
ax.set_axis_off()
ax = manhattan_bbox_gdf.plot(color="#e7e7df", figsize=(16, 16))
# plot greenery
new_york_features_gdf[new_york_features_gdf["leisure"] == "leisure=park"].plot(
ax=ax, color="#bae5ce"
)
# plot water
new_york_features_gdf.dropna(subset=["water", "waterways"], how="all").plot(ax=ax, color="#c7eced")
# plot streets
new_york_features_gdf.dropna(subset=["paths_unsuitable_for_cars"], how="all").plot(
ax=ax, color="#e7e7df", linewidth=1
)
new_york_features_gdf.dropna(
subset=["very_small_roads", "highway_links", "minor_roads"], how="all"
).plot(ax=ax, color="#fff", linewidth=2)
new_york_features_gdf.dropna(subset=["major_roads"], how="all").plot(
ax=ax, color="#fac9a9", linewidth=3
)
# plot buildings
new_york_features_gdf.dropna(subset=["buildings"], how="all").plot(ax=ax, color="#cecebd")
xmin, ymin, xmax, ymax = manhattan_bbox_gdf.total_bounds
ax.set_xlim(xmin, xmax)
ax.set_ylim(ymin, ymax)
ax.set_axis_off()
Using OSMPbfLoader to download data for a specific area and transforming it to GeoParquet file¶
Download all grouped features based on Geofabrik layers in Reykjavík, Iceland¶
In [14]:
Copied!
loader = OSMPbfLoader()
reykjavik_gdf = geocode_to_region_gdf("Reykjavík, IS")
reykjavik_features_gpq = loader.load_to_geoparquet(reykjavik_gdf, GEOFABRIK_LAYERS)
reykjavik_features_gpq
loader = OSMPbfLoader()
reykjavik_gdf = geocode_to_region_gdf("Reykjavík, IS")
reykjavik_features_gpq = loader.load_to_geoparquet(reykjavik_gdf, GEOFABRIK_LAYERS)
reykjavik_features_gpq
/opt/hostedtoolcache/Python/3.10.15/x64/lib/python3.10/site-packages/srai/loaders/osm_loaders/osm_pbf_loader.py:191: FutureWarning: Use `convert_geometry_to_parquet` instead. Deprecated since 0.8.1 version. geoparquet_file_path = pbf_reader.convert_geometry_filter_to_gpq(
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Finished operation in 0:00:22
Out[14]:
PosixPath('files/3b68f6ecc515eba6f588efa104d7eee92b450cf9c7e54f445afae421e604cf3f_098931824b94bfe02e01bc4987422a39ec47bd3f6924e5325ddae0846badafba_exploded.parquet')
Read those features using DuckDB¶
In [15]:
Copied!
import duckdb
connection = duckdb.connect()
connection.load_extension("parquet")
connection.load_extension("spatial")
features_relation = connection.read_parquet(str(reykjavik_features_gpq))
features_relation
import duckdb
connection = duckdb.connect()
connection.load_extension("parquet")
connection.load_extension("spatial")
features_relation = connection.read_parquet(str(reykjavik_features_gpq))
features_relation
Out[15]:
┌─────────────────┬───────────────┬─────────────┬───────────┬──────────┬───────────┬──────────────┬─────────┬───────────────┬─────────┬─────────┬─────────────┬─────────────┬─────────┬─────────┬─────────┬───────────────────────────┬─────────┬─────────┬──────────┬──────────┬─────────┬───────────────────────────┬───────────┬──────────────────┬─────────┬───────────────┬───────────┬────────────────────────────────┐ │ feature_id │ accommodation │ air_traffic │ buildings │ catering │ education │ fuel_parking │ health │ highway_links │ landuse │ leisure │ major_roads │ minor_roads │ miscpoi │ money │ natural │ paths_unsuitable_for_cars │ pofw │ public │ railways │ shopping │ tourism │ traffic │ transport │ very_small_roads │ water │ water_traffic │ waterways │ geometry │ │ varchar │ varchar │ varchar │ varchar │ varchar │ varchar │ varchar │ varchar │ varchar │ varchar │ varchar │ varchar │ varchar │ varchar │ varchar │ varchar │ varchar │ varchar │ varchar │ varchar │ varchar │ varchar │ varchar │ varchar │ varchar │ varchar │ varchar │ varchar │ geometry │ ├─────────────────┼───────────────┼─────────────┼───────────┼──────────┼───────────┼──────────────┼─────────┼───────────────┼─────────┼─────────┼─────────────┼─────────────┼─────────┼─────────┼─────────┼───────────────────────────┼─────────┼─────────┼──────────┼──────────┼─────────┼───────────────────────────┼───────────┼──────────────────┼─────────┼───────────────┼───────────┼────────────────────────────────┤ │ node/13472516 │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ highway=motorway_junction │ NULL │ NULL │ NULL │ NULL │ NULL │ POINT (-21.7847679 64.1235709) │ │ node/13489663 │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ highway=motorway_junction │ NULL │ NULL │ NULL │ NULL │ NULL │ POINT (-21.8324909 64.1237812) │ │ node/14586972 │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ highway=motorway_junction │ NULL │ NULL │ NULL │ NULL │ NULL │ POINT (-21.7644946 64.1320481) │ │ node/16570604 │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ highway=motorway_junction │ NULL │ NULL │ NULL │ NULL │ NULL │ POINT (-21.7909159 64.1243715) │ │ node/253700479 │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ highway=crossing │ NULL │ NULL │ NULL │ NULL │ NULL │ POINT (-21.7879721 64.1527899) │ │ node/253700482 │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ highway=turning_circle │ NULL │ NULL │ NULL │ NULL │ NULL │ POINT (-21.7901713 64.1536876) │ │ node/253700508 │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ highway=crossing │ NULL │ NULL │ NULL │ NULL │ NULL │ POINT (-21.7859819 64.1531647) │ │ node/253700511 │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ highway=crossing │ NULL │ NULL │ NULL │ NULL │ NULL │ POINT (-21.7851932 64.154238) │ │ node/253700618 │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ highway=turning_circle │ NULL │ NULL │ NULL │ NULL │ NULL │ POINT (-21.7873176 64.1544839) │ │ node/253700622 │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ highway=turning_circle │ NULL │ NULL │ NULL │ NULL │ NULL │ POINT (-21.783905 64.1537817) │ │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ · │ │ node/2004287433 │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ highway=street_lamp │ NULL │ NULL │ NULL │ NULL │ NULL │ POINT (-21.9635084 64.1490928) │ │ node/2004287434 │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ highway=street_lamp │ NULL │ NULL │ NULL │ NULL │ NULL │ POINT (-21.9712541 64.1490991) │ │ node/2004287435 │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ highway=street_lamp │ NULL │ NULL │ NULL │ NULL │ NULL │ POINT (-21.9297104 64.1490995) │ │ node/2004287436 │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ highway=street_lamp │ NULL │ NULL │ NULL │ NULL │ NULL │ POINT (-21.9663431 64.1491028) │ │ node/2004287437 │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ highway=street_lamp │ NULL │ NULL │ NULL │ NULL │ NULL │ POINT (-21.9608255 64.149104) │ │ node/2004287438 │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ highway=street_lamp │ NULL │ NULL │ NULL │ NULL │ NULL │ POINT (-21.9748666 64.1491096) │ │ node/2004287439 │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ highway=street_lamp │ NULL │ NULL │ NULL │ NULL │ NULL │ POINT (-21.9616024 64.1491163) │ │ node/2004287440 │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ highway=street_lamp │ NULL │ NULL │ NULL │ NULL │ NULL │ POINT (-21.9497616 64.1491179) │ │ node/2004287441 │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ highway=street_lamp │ NULL │ NULL │ NULL │ NULL │ NULL │ POINT (-21.96669 64.1491188) │ │ node/2004287442 │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ NULL │ highway=street_lamp │ NULL │ NULL │ NULL │ NULL │ NULL │ POINT (-21.9513505 64.1491192) │ ├─────────────────┴───────────────┴─────────────┴───────────┴──────────┴───────────┴──────────────┴─────────┴───────────────┴─────────┴─────────┴─────────────┴─────────────┴─────────┴─────────┴─────────┴───────────────────────────┴─────────┴─────────┴──────────┴──────────┴─────────┴───────────────────────────┴───────────┴──────────────────┴─────────┴───────────────┴───────────┴────────────────────────────────┤ │ ? rows (>9999 rows, 20 shown) 29 columns │ └───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘
Count all buildings¶
In [16]:
Copied!
features_relation.filter("buildings IS NOT NULL").count("feature_id")
features_relation.filter("buildings IS NOT NULL").count("feature_id")
Out[16]:
┌───────────────────┐ │ count(feature_id) │ │ int64 │ ├───────────────────┤ │ 25359 │ └───────────────────┘
You can see more examples of how to use PbfFileReader from the QuackOSM library in the docs: https://kraina-ai.github.io/quackosm/latest/examples/pbf_file_reader/