Create shapefiles

Merge LSOAs to create shapefiles for:

• IVT catchment areas

• Ambulance trusts

1 Import libraries and set file paths

from dataclasses import dataclass
import geopandas as gpd
import os
import pandas as pd

# Define file paths
@dataclass(frozen=True)
class Paths:
    '''Singleton object for storing paths to data and database.'''

    data = './data'
    collated = 'collated_data_amb.csv'

    shapefiles = 'shapefiles'
    ivt_catchment = 'ivt_catchment.shp'
    amb_catchment = 'amb_catchment.shp'
    lsoa_shp = ('Lower_layer_super_output_areas_(E+W)_2011_Boundaries_' +
                '(Generalised_Clipped)_V2.zip')


paths = Paths()

2 Load data

2.1 Load data with closest IVT and ambulance trust per LSOA

df_lsoa = pd.read_csv(os.path.join(paths.data, paths.collated))
df_lsoa.head()

	LSOA	admissions	closest_ivt_unit	closest_ivt_unit_time	closest_mt_unit	closest_mt_unit_time	closest_mt_transfer	closest_mt_transfer_time	total_mt_time	ivt_rate	...	age_band_males_65	age_band_males_70	age_band_males_75	age_band_males_80	age_band_males_85	age_band_males_90	ambulance_service	local_authority_district_22	LAD22NM	country
0	Welwyn Hatfield 010F	0.666667	SG14AB	18.7	NW12BU	36.9	CB20QQ	39.1	57.8	6.8	...	33	28	26	14	5	3	East of England	Welwyn Hatfield	Welwyn Hatfield	England
1	Welwyn Hatfield 012A	4.000000	SG14AB	19.8	NW12BU	36.9	CB20QQ	39.1	58.9	6.8	...	24	18	21	12	5	4	East of England	Welwyn Hatfield	Welwyn Hatfield	England
2	Welwyn Hatfield 002F	2.000000	SG14AB	18.7	NW12BU	38.0	CB20QQ	39.1	57.8	6.8	...	33	28	7	5	9	2	East of England	Welwyn Hatfield	Welwyn Hatfield	England
3	Welwyn Hatfield 002E	0.666667	SG14AB	18.7	NW12BU	36.9	CB20QQ	39.1	57.8	6.8	...	24	17	15	16	9	1	East of England	Welwyn Hatfield	Welwyn Hatfield	England
4	Welwyn Hatfield 010A	3.333333	SG14AB	18.7	NW12BU	36.9	CB20QQ	39.1	57.8	6.8	...	33	28	28	13	10	3	East of England	Welwyn Hatfield	Welwyn Hatfield	England

5 rows × 115 columns

2.2 Load LSOA shape file

The following will load the shape file of the England and Wales LSOA (Lower Super Output Areas) into a GeoPandas DataFrame. Note that we can set the crs (Coordinate Reference System) when loading a GeoPandas DataFrame. EPSG:27700 is the crs to use when geography is in BNG (British National Grid Eastings and Northings).

Other crs to consider for other data projections:

• EPSG:27700 OSGB 1936 / British National Grid – United Kingdom Ordnance Survey. Co-ordinates are in Eastings (X) and Northings (Y).

• EPSG:4326 WGS 84 – WGS84 - World Geodetic System 1984. Co-ordinates are in Longitude (X) and Latitude (Y).

• EPSG:3857 - projection for displaying lat/long as a flat map

gdf_lsoa = gpd.read_file(os.path.join(
    paths.data, paths.shapefiles, paths.lsoa_shp),
    crs='EPSG:27700')
gdf_lsoa.head()

	LSOA11CD	LSOA11NM	LSOA11NMW	geometry
0	E01000001	City of London 001A	City of London 001A	POLYGON ((532105.092 182011.230, 532162.491 18...
1	E01000002	City of London 001B	City of London 001B	POLYGON ((532746.813 181786.891, 532671.688 18...
2	E01000003	City of London 001C	City of London 001C	POLYGON ((532135.145 182198.119, 532158.250 18...
3	E01000005	City of London 001E	City of London 001E	POLYGON ((533807.946 180767.770, 533649.063 18...
4	E01000006	Barking and Dagenham 016A	Barking and Dagenham 016A	POLYGON ((545122.049 184314.931, 545271.917 18...

View a simple map of this data.

gdf_lsoa.plot(figsize=(8,8));

3 Merge LSOAs together to create shapefiles

3.1 Define function for creating shapefiles

The method used is explained with the example of creating a shapefile of IVT catchment areas:

1. Add column to geopandas dataframe - using LSOA as common value, add field ‘closest_ivt_unit’. Match gdf_lsoa[‘LSOA11NMW’] with df_lsoa[‘LSOA’] and add df_lsoa[‘closest_ivt_unit’] to gdf_lsoa[‘closest_ivt_unit’] - see here for stackoverflow explanation

2. Ensure no inner lines from original polygons using buffer(0.0001) - see here for stackoverflow explanation

3. Merge LSOA polygons that are in same IVT unit catchment area using dissolve() - see here for geopandas tutorial on aggregation with dissolve

def create_shapefile(col, file_path, gdf=gdf_lsoa, df=df_lsoa):
    '''
    Merges LSOAs together based on specified column to create a shapefile
    Inputs:
    - col - string, column to group LSOAs based on
    - file_path - string, file path to save shapefile to
    - gdf - geopandas dataframe, created from LSOA shapefile
    - df - dataframe, information for each LSOA
    '''
    # Add column to geopandas LSOA dataframe
    gdf = gdf.merge(
        df[[col, 'LSOA']], left_on='LSOA11NM', right_on='LSOA', how='left')
    gdf = gdf.drop('LSOA', axis=1)

    # Shortern column to first 10 characters (since that's what it will be
    # renamed to for the shapefile) (else get warning message)
    shp_col = col[:10]
    gdf = gdf.rename(columns={col: shp_col})

    # Ensure no inner lines (from the original polygons)
    gdf['geometry'] = gdf['geometry'].buffer(0.0001)

    # Now merge LSOA on specified column
    gdf_catchment = gdf.dissolve(by=shp_col)

    # Save to shapefile
    gdf_catchment.to_file(file_path)

    # Show save location
    display(f'Saved to {file_path}')

    # Display head of dataframe
    display(gdf_catchment.head())

    # Plot shapefile
    gdf_catchment.plot(figsize=(8,8));

3.2 Create IVT catchment shapefile

create_shapefile(
    'closest_ivt_unit',
    os.path.join(paths.data, paths.shapefiles, paths.ivt_catchment))

'Saved to ./data/shapefiles/ivt_catchment.shp'

	geometry	LSOA11CD	LSOA11NM	LSOA11NMW
closest_iv
B152TH	MULTIPOLYGON (((403011.723 266679.152, 402597....	E01008881	Birmingham 067A	Birmingham 067A
B714HJ	MULTIPOLYGON (((395950.714 272162.470, 395950....	E01008899	Birmingham 037A	Birmingham 037A
BA13NG	POLYGON ((354665.594 144552.500, 354665.594 14...	E01014370	Bath and North East Somerset 007A	Bath and North East Somerset 007A
BA214AT	MULTIPOLYGON (((330365.588 98427.209, 330281.9...	E01019886	East Devon 005A	East Devon 005A
BB23HH	POLYGON ((369965.000 416593.000, 370071.000 41...	E01004803	Bolton 001B	Bolton 001B

3.3 Create ambulance trust shapefile

create_shapefile(
    'ambulance_service',
    os.path.join(paths.data, paths.shapefiles, paths.amb_catchment))

'Saved to ./data/shapefiles/amb_catchment.shp'

	geometry	LSOA11CD	LSOA11NM	LSOA11NMW
ambulance_
East Midlands	MULTIPOLYGON (((433631.972 296489.554, 433631....	E01013128	North East Lincolnshire 010A	North East Lincolnshire 010A
East of England	MULTIPOLYGON (((503939.688 193345.500, 503939....	E01015589	Peterborough 004A	Peterborough 004A
Isle of Wight	MULTIPOLYGON (((451071.500 75523.100, 451071.5...	E01017282	Isle of Wight 006A	Isle of Wight 006A
London	MULTIPOLYGON (((510971.125 170480.219, 510971....	E01000001	City of London 001A	City of London 001A
North East	MULTIPOLYGON (((418029.261 516224.682, 418029....	E01008162	Gateshead 027A	Gateshead 027A