datapunt_processing.transform.geospatial package

Submodules

datapunt_processing.transform.geospatial.addres_to_latlon_in_df module

datapunt_processing.transform.geospatial.addres_to_latlon_in_df.adress_to_latlon(df)

This function adds the lattitude and longtitude to a pandas df based on an adress.

input: pandas df met tenminste de volgende variabelen:

  • Straat: String met de naam van de straat
  • Huisnr: String met huisnummer

output: pandas df waaraan de volgende variabelen zijn toegevoegd:

  • lon: longtitude behorend bij adres
  • lat: lattitude behorend bij adres

datapunt_processing.transform.geospatial.api_clean_BAG_address_NED module

datapunt_processing.transform.geospatial.api_clean_BAG_address_NED.main()
datapunt_processing.transform.geospatial.api_clean_BAG_address_NED.parser()

Parser function to run arguments from commandline and to add description to sphinx docs. To see possible styling options: https://pythonhosted.org/an_example_pypi_project/sphinx.html

datapunt_processing.transform.geospatial.api_get_areacodes_from_latlon module

datapunt_processing.transform.geospatial.api_get_areacodes_from_latlon.getAreaCodes(item, lat, lon)
Get specific information like area codes based radius to nearest address based on lat/lon value
ex: https://api.data.amsterdam.nl/geosearch/search/?item=verblijfsobject&lat=52.3731750&lon=4.8924655&radius=50

It currently is coded to work to get: - “buurt” - “buurtcombinatie” - “stadsdeel”

datapunt_processing.transform.geospatial.api_get_areacodes_from_latlon.getAreaCodesforDataFrame(df, item)

Get specific information like area codes based radius to nearest address based on lat/lon value for each row in pandas DF. Args:

df with column “lon” and “lat” item, which is “buurt”, “buurtcombinatie” or “stadsdeel”
Returns:
df with two new columns that describe name and code of the item “
datapunt_processing.transform.geospatial.api_get_areacodes_from_latlon.getJson(url)

Get a json from an url

Args:

url: give an api url:

https://api.data.amsterdam.nl/bag/gebieden/stadsdeel
Returns:
a parsed json result or an error message

datapunt_processing.transform.geospatial.api_get_nearest_address_from_latlon module

datapunt_processing.transform.geospatial.api_get_nearest_address_from_latlon.get_address_near_point(lat, lon, radius)

Get nearest addres and housenumber based on location.

get_address_near_point(52.3729378, 4.8937806, 50)

Args:
  1. lat: 52.3729378
  2. lon: 4.8937806
  3. radius: 50
Returns:
Dictionary of the first found address with openbareruimte, huisnummer, postcode, etc…
datapunt_processing.transform.geospatial.api_get_nearest_address_from_latlon.get_openbareruimte(lat, lon)

Get the name the street location where it coordinate resides on.

Args:
  1. lat: 52.3729378
  2. lon: 4.8937806
Result:
Returns dictionary of the openbare ruimte object

datapunt_processing.transform.geospatial.csv_get_centroid_of_street module

datapunt_processing.transform.geospatial.csv_get_centroid_of_street.get_centroid_street(filename, street_column, city_name)

Get the X,Y centroid of an address.

Args:
  1. street_column: Dam 1
  2. city_name: Amsterdam
Returns:
Origional CSV file with coordinates and BAG corrected naming.
datapunt_processing.transform.geospatial.csv_get_centroid_of_street.main()
datapunt_processing.transform.geospatial.csv_get_centroid_of_street.parser()

datapunt_processing.transform.geospatial.divide_bbox_amsterdam_in_quadrants module

datapunt_processing.transform.geospatial.divide_bbox_amsterdam_in_quadrants.calculation(number_of_boxes, bbox)

Divide the BBOX of the City of Amsterdam in x number of quadrants/rectangles for use in limiting WFS/geo queries.

Args:
  1. number_of_boxes: in multiples of 2, 8 works well for most cases.
  2. bbox: [110200,476772,134030,493900]
Returns:
list of quadrants [[x1,y1,x2,y2],[..]]

datapunt_processing.transform.geospatial.geocode_xls_to_csv module

datapunt_processing.transform.geospatial.geocode_xls_to_csv.main()
datapunt_processing.transform.geospatial.geocode_xls_to_csv.parser()

Parser function to run arguments from commandline and to add description to sphinx docs. To see possible styling options: https://pythonhosted.org/an_example_pypi_project/sphinx.html

datapunt_processing.transform.geospatial.get_bag_address_from_geojson_points module

datapunt_processing.transform.geospatial.get_bag_address_from_geojson_points.add_location_data(location)
datapunt_processing.transform.geospatial.get_bag_address_from_geojson_points.cleanup_properties(location)
datapunt_processing.transform.geospatial.get_bag_address_from_geojson_points.get_address_near_point(lat, lon, radius)

Get nearest addres and housenumber based on location.

get_address_near_point(52.3729378, 4.8937806, 50)

Args:
  1. lat: 52.3729378
  2. lon: 4.8937806
  3. radius: 50
Returns:
Dictionary of the first found address with openbareruimte, huisnummer, postcode, etc…
datapunt_processing.transform.geospatial.get_bag_address_from_geojson_points.get_elements(div_content, element_type)
datapunt_processing.transform.geospatial.get_bag_address_from_geojson_points.get_filename(url)
datapunt_processing.transform.geospatial.get_bag_address_from_geojson_points.get_location_information(uri)

Get html page, find the header and values by h4 and p and return as a list with 2 values

datapunt_processing.transform.geospatial.get_bag_address_from_geojson_points.get_pand(lat, lon, radius)

Get the name the street location where it coordinate resides on.

Args:
  1. lat: 52.3729378
  2. lon: 4.8937806
Result:
Returns dictionary of the pand object
datapunt_processing.transform.geospatial.get_bag_address_from_geojson_points.main()
datapunt_processing.transform.geospatial.get_bag_address_from_geojson_points.remove_html_elements(text)

datapunt_processing.transform.geospatial.postgres_add_areas_from_coordinates module

datapunt_processing.transform.geospatial.postgres_add_areas_from_coordinates.executeScriptsFromFile(pg_str, filename)

WIP does not work yet

datapunt_processing.transform.geospatial.postgres_add_areas_from_coordinates.main()
datapunt_processing.transform.geospatial.postgres_add_areas_from_coordinates.parser()

datapunt_processing.transform.geospatial.rd_to_wgs84 module

datapunt_processing.transform.geospatial.rd_to_wgs84.rd_to_wgs84(X, Y)

Quick reprojection method, does result in 1m max offset difference. Use Postgres ST_Transform method if you want a better reprojection. Example downloaded from http://forum.geocaching.nl/index.php?showtopic=7886

Module contents