Practica calificada 5¶

Ejercicio 1¶

You will make two maps:

  1. Plot your country as the background. Use cx to plot some points (the cities, airports, etc.) below the centroid.
  2. Plot your country as the background. Select with cx all the first administrative divisions above the centroid. Then, use clip to show some lines (rivers, railroads, etc) that cross those divisions.

Parte 1¶

In [3]:
linkWorldMap="https://github.com/CRVCh-16/PC5/raw/refs/heads/main/canadaMaps_ESRI_102001.gpkg"
!pip install fiona

Requirement already satisfied: fiona in c:\users\admin\anaconda3\envs\dataespacial_31111\lib\site-packages (1.10.1)
Requirement already satisfied: attrs>=19.2.0 in c:\users\admin\anaconda3\envs\dataespacial_31111\lib\site-packages (from fiona) (24.3.0)
Requirement already satisfied: certifi in c:\users\admin\anaconda3\envs\dataespacial_31111\lib\site-packages (from fiona) (2025.4.26)
Requirement already satisfied: click~=8.0 in c:\users\admin\anaconda3\envs\dataespacial_31111\lib\site-packages (from fiona) (8.2.1)
Requirement already satisfied: click-plugins>=1.0 in c:\users\admin\anaconda3\envs\dataespacial_31111\lib\site-packages (from fiona) (1.1.1)
Requirement already satisfied: cligj>=0.5 in c:\users\admin\anaconda3\envs\dataespacial_31111\lib\site-packages (from fiona) (0.7.2)
Requirement already satisfied: colorama in c:\users\admin\anaconda3\envs\dataespacial_31111\lib\site-packages (from click~=8.0->fiona) (0.4.6)
In [4]:
import geopandas as gpd
from  fiona import listlayers
listlayers(linkWorldMap)
Out[4]:
['country',
 'cities',
 'rivers',
 'centroid',
 'airports',
 'border',
 'country_GADM',
 'provincias_GADM',
 'municipios_GADM',
 'menor_GADM',
 'indicators']
In [5]:
import os
In [6]:
countryCanada=gpd.read_file(os.path.join("canadaMaps_ESRI_102001.gpkg"),layer='country')
In [7]:
citiesCanada=gpd.read_file(os.path.join("canadaMaps_ESRI_102001.gpkg"),layer='cities')
In [8]:
riversCanada=gpd.read_file(os.path.join("canadaMaps_ESRI_102001.gpkg"),layer='rivers')
In [9]:
centroidCanada=gpd.read_file(os.path.join("canadaMaps_ESRI_102001.gpkg"),layer='centroid')
In [10]:
airportsCanada=gpd.read_file(os.path.join("canadaMaps_ESRI_102001.gpkg"),layer='airports')
In [11]:
borderCanada=gpd.read_file(os.path.join("canadaMaps_ESRI_102001.gpkg"),layer='border')
In [12]:
country_GADMCanada=gpd.read_file(os.path.join("canadaMaps_ESRI_102001.gpkg"),layer='country_GADM')
In [13]:
provincias_GADMCanada=gpd.read_file(os.path.join("canadaMaps_ESRI_102001.gpkg"),layer='provincias_GADM')
In [14]:
municipios_GADMCanada=gpd.read_file(os.path.join("canadaMaps_ESRI_102001.gpkg"),layer='municipios_GADM')
In [15]:
menor_GADMCanada=gpd.read_file(os.path.join("canadaMaps_ESRI_102001.gpkg"),layer='menor_GADM')
In [16]:
indicatorsCanada=gpd.read_file(os.path.join("canadaMaps_ESRI_102001.gpkg"),layer='indicators')
In [17]:
worldMapsLink="https://github.com/CienciaDeDatosEspacial/intro_geodataframe/raw/main/maps/worldMaps.gpkg"
In [18]:
countries=gpd.read_file(worldMapsLink,layer='countries')
rivers=gpd.read_file(worldMapsLink,layer='rivers')
cities=gpd.read_file(worldMapsLink,layer='cities')
indicators=gpd.read_file(linkWorldMap,layer='indicators')
In [19]:
canada=countries[countries.COUNTRY=='Canada']
In [20]:
citiesCanada_clipped = gpd.clip(gdf=cities, mask=canada)
riversCanada_clipped = gpd.clip(gdf=rivers, mask=canada)
In [21]:
canada_102001=canada.to_crs("ESRI:102001")
cities_102001=citiesCanada_clipped.to_crs("ESRI:102001")
rivers_102001=riversCanada_clipped.to_crs("ESRI:102001")
In [22]:
canada_102001.centroid
Out[22]:
35    POINT (-24206.312 2263307.35)
dtype: geometry
In [23]:
xCoordCentroid=canada_102001.centroid.iloc[0].x
xCoordCentroid
Out[23]:
-24206.31186623601
In [24]:
yCoordCentroid=canada_102001.centroid.iloc[0].y
yCoordCentroid
Out[24]:
2263307.349641779
In [25]:
canadaBase=canada_102001.plot(facecolor="green",edgecolor="black",figsize=(4,4))
No description has been provided for this image
In [26]:
citiesBelowCentroid=cities_102001.cx[:,:yCoordCentroid]
In [27]:
import matplotlib.pyplot as plt

fig, (ax1) = plt.subplots(ncols=1, sharex=False, sharey=False, figsize=(10,10))

canadaBase=canada_102001.plot(facecolor="#dcffa5",edgecolor="black",ax=ax1)
citiesBelowCentroid.plot(color="red",markersize=5,ax=canadaBase)
canada_102001.centroid.plot(color="#2657ff",markersize=20,ax=canadaBase)
Out[27]:
<Axes: >
No description has been provided for this image

Parte 2¶

In [28]:
 # provincias_GADMCanada.plot(facecolor="white",edgecolor="black")
canada_102001.centroid.plot(color="#2657ff",markersize=5,ax=provincias_GADMCanada.plot(facecolor="white",edgecolor="black",linewidth=0.2)  )
Out[28]:
<Axes: >
No description has been provided for this image
In [29]:
provinciasAboveCentroid=provincias_GADMCanada.cx[:,yCoordCentroid:]
In [30]:
riversCanadaAboveCentroid_clipped = gpd.clip(gdf=riversCanada_clipped.to_crs("ESRI:102001"), mask=provinciasAboveCentroid)
In [31]:
base0=provincias_GADMCanada.cx[:,yCoordCentroid:].plot(facecolor="#dcffa5",edgecolor="black",linewidth=0.5,figsize=(10,10))

canada_102001.centroid.plot(color="red",markersize=15,ax=base0)
riversCanadaAboveCentroid_clipped.plot(edgecolor="blue",ax=base0,linewidth=0.8)
Out[31]:
<Axes: >
No description has been provided for this image

Provincias enteramente sobre el centroide

In [32]:
ProvN_canada=provincias_GADMCanada.cx[:,yCoordCentroid:]
ProvS_canada=provincias_GADMCanada.cx[:,:yCoordCentroid]
ProvNS_canada=ProvN_canada.overlay(ProvS_canada, how="intersection",keep_geom_type=True)
provAboveCentroidNEW=provincias_GADMCanada.cx[:,yCoordCentroid:].overlay(ProvNS_canada, how='difference',keep_geom_type=True)
riversCanadaAboveCentroidNEW_clipped = gpd.clip(gdf=riversCanada_clipped.to_crs("ESRI:102001"), mask=provAboveCentroidNEW)
In [33]:
base10=provAboveCentroidNEW.plot(facecolor="#dcffa5",edgecolor="black",linewidth=0.5,figsize=(10,10))

canada_102001.centroid.plot(color="red",markersize=15,ax=base10)
riversCanadaAboveCentroidNEW_clipped.plot(edgecolor="blue",ax=base10,linewidth=0.8)
Out[33]:
<Axes: >
No description has been provided for this image

Ejercicio 2¶

  1. Create some subset of polygons with your country data at the municipal (or similar level). Use Unary UNION with those polygons, and create a geoDF with the result.
  2. Dissolve your municipalities by another higher level administrative level. Plot the result.
  3. If possible, color some areas of your country by aggregating; if not, plot the "median" values in the indicators map.

Parte 1¶

In [34]:
# 1 haacer regiones a partir de distritos
# 2, pero con dissolve
# 3, hacer el dissolve con aggregate
In [35]:
municipios_GADMCanada[municipios_GADMCanada.NAME_1=='Alberta'].plot()
Out[35]:
<Axes: >
No description has been provided for this image
In [36]:
municipios_GADMCanada[municipios_GADMCanada.NAME_1=='Alberta'].union_all()
Out[36]:
No description has been provided for this image
In [37]:
alberta_union=municipios_GADMCanada[municipios_GADMCanada.NAME_1=='Alberta'].union_all()
In [38]:
gpd.GeoDataFrame(index=[0],data={'ADM':'Alberta'}, crs=municipios_GADMCanada.crs, geometry=[alberta_union])
Out[38]:
ADM geometry
0 Alberta POLYGON ((-1191696.513 1131094.24, -1193580.69...

Parte 2¶

In [39]:
alberta_dissolve=municipios_GADMCanada[municipios_GADMCanada.NAME_1=='Alberta'].dissolve()
In [40]:
alberta_dissolve
Out[40]:
geometry GID_2 GID_0 COUNTRY GID_1 NAME_1 NL_NAME_1 NAME_2 VARNAME_2 NL_NAME_2 TYPE_2 ENGTYPE_2 CC_2 HASC_2
0 POLYGON ((-1191696.513 1131094.24, -1193580.69... CAN.1.11_1 CAN Canada CAN.1_1 Alberta NA Division No. 1 NA NA Census Division Census Division 01 CA.AB.ON
In [41]:
alberta_dissolve.drop(columns=['GID_2','NAME_2','VARNAME_2','NL_NAME_2','TYPE_2','ENGTYPE_2','CC_2','HASC_2'],inplace=True)
alberta_dissolve
Out[41]:
geometry GID_0 COUNTRY GID_1 NAME_1 NL_NAME_1
0 POLYGON ((-1191696.513 1131094.24, -1193580.69... CAN Canada CAN.1_1 Alberta NA
In [42]:
municipios_GADMCanada.head(3)
Out[42]:
GID_2 GID_0 COUNTRY GID_1 NAME_1 NL_NAME_1 NAME_2 VARNAME_2 NL_NAME_2 TYPE_2 ENGTYPE_2 CC_2 HASC_2 geometry
0 CAN.1.11_1 CAN Canada CAN.1_1 Alberta NA Division No. 1 NA NA Census Division Census Division 01 CA.AB.ON MULTIPOLYGON (((-1072474.656 1102938.917, -107...
1 CAN.1.1_1 CAN Canada CAN.1_1 Alberta NA Division No. 10 NA NA Census Division Census Division 10 CA.AB.TE MULTIPOLYGON (((-1077505.317 1564290.622, -107...
2 CAN.1.2_1 CAN Canada CAN.1_1 Alberta NA Division No. 11 NA NA Census Division Census Division 11 CA.AB.EL MULTIPOLYGON (((-1129359.754 1589249.184, -112...
In [43]:
municipios_GADMCanada.dissolve(by='NAME_1').plot(facecolor='#feffe0', edgecolor='black',linewidth=0.2) # disuelve por la columna NAME_1
Out[43]:
<Axes: >
No description has been provided for this image
In [44]:
canada_name1_diss=municipios_GADMCanada.dissolve(by='NAME_1')

Parte 3¶

In [45]:
indicatorsCanada.head(3)
Out[45]:
COUNTRY Officialstatename InternetccTLD iso2 iso3 fragility co2 region ForestRev_gdp fragility_Qt ... forestRev_gdp_Qt co2_Qt_jc5 co2_Qt_jc5_cat forestRev_gdp_Qt_jc5 forestRev_gdp_Qt_jc5_cat Energy_consumption_per_capita_BtuPerPerson energy_Qt energy_Qt_jc5 energy_Qt_jc5_cat geometry
0 ANTIGUA AND BARBUDA Antigua and Barbuda .ag AG ATG 54.4 729000.0 CENTRAL AMERICA AND THE CARIBBEAN 0.0 -0.559624 ... -5.199338 0 0_Great 0 0_Great 110114000 0.859799 3 3_Bad MULTIPOLYGON (((-61.73889 17.54055, -61.75195 ...
1 AFGHANISTAN The Islamic Republic of Afghanistan .af AF AFG 105.0 7893000.0 SOUTH ASIA 0.2 1.824703 ... -0.076809 2 2_Middle 2 2_Middle 3380000 -1.279661 0 0_Great MULTIPOLYGON (((61.27656 35.60725, 61.29638 35...
2 ALGERIA The People's Democratic Republic of Algeria .dz DZ DZA 75.4 151633000.0 AFRICA 0.1 0.281088 ... -0.338888 3 3_Bad 1 1_Good 61843000 0.230568 2 2_Middle MULTIPOLYGON (((-5.15213 30.18047, -5.13917 30...

3 rows × 23 columns

In [46]:
indicatorsByRegion=indicatorsCanada.dissolve(
     by="region",
     aggfunc={
         "COUNTRY": "count",
         "fragility": ["median"],
         "co2": ["median"],
         "ForestRev_gdp": ["median"]
     },as_index=False,
 )
In [47]:
indicatorsByRegion
Out[47]:
region geometry (COUNTRY, count) (fragility, median) (co2, median) (ForestRev_gdp, median)
0 AFRICA MULTIPOLYGON (((-2.92813 5.10022, -2.93222 5.1... 50 87.10 4331000.0 2.360
1 AUSTRALIA AND OCEANIA MULTIPOLYGON (((-176.51779 -43.90778, -176.532... 6 64.20 1023000.0 0.385
2 CENTRAL AMERICA AND THE CARIBBEAN MULTIPOLYGON (((-81.71556 7.44681, -81.71362 7... 15 61.20 7632000.0 0.150
3 CENTRAL ASIA MULTIPOLYGON (((50.03472 45.04833, 50.0425 45.... 6 75.20 106001000.0 0.005
4 EAST AND SOUTHEAST ASIA MULTIPOLYGON (((105.26361 -6.54472, 105.26138 ... 14 68.25 244456000.0 0.260
5 EUROPE MULTIPOLYGON (((-18.13223 27.77264, -18.1132 2... 36 40.75 40367500.0 0.140
6 MIDDLE EAST MULTIPOLYGON (((42.76819 14.06653, 42.7868 14.... 16 72.60 68706500.0 0.000
7 NORTH AMERICA MULTIPOLYGON (((-155.211 20.00166, -155.18335 ... 3 38.00 612084000.0 0.080
8 SOUTH AMERICA MULTIPOLYGON (((-74.93431 -51.85501, -74.93251... 11 68.20 36051000.0 0.490
9 SOUTH ASIA MULTIPOLYGON (((73.10193 -0.58431, 73.09915 -0... 8 84.35 15916000.0 0.120
In [48]:
!pip install mapclassify

Requirement already satisfied: mapclassify in c:\users\admin\anaconda3\envs\dataespacial_31111\lib\site-packages (2.8.1)
Requirement already satisfied: networkx>=2.7 in c:\users\admin\anaconda3\envs\dataespacial_31111\lib\site-packages (from mapclassify) (3.4.2)
Requirement already satisfied: numpy>=1.23 in c:\users\admin\anaconda3\envs\dataespacial_31111\lib\site-packages (from mapclassify) (2.1.3)
Requirement already satisfied: pandas!=1.5.0,>=1.4 in c:\users\admin\anaconda3\envs\dataespacial_31111\lib\site-packages (from mapclassify) (2.2.3)
Requirement already satisfied: scikit-learn>=1.0 in c:\users\admin\anaconda3\envs\dataespacial_31111\lib\site-packages (from mapclassify) (1.6.1)
Requirement already satisfied: scipy>=1.8 in c:\users\admin\anaconda3\envs\dataespacial_31111\lib\site-packages (from mapclassify) (1.15.2)
Requirement already satisfied: python-dateutil>=2.8.2 in c:\users\admin\anaconda3\envs\dataespacial_31111\lib\site-packages (from pandas!=1.5.0,>=1.4->mapclassify) (2.9.0.post0)
Requirement already satisfied: pytz>=2020.1 in c:\users\admin\anaconda3\envs\dataespacial_31111\lib\site-packages (from pandas!=1.5.0,>=1.4->mapclassify) (2024.1)
Requirement already satisfied: tzdata>=2022.7 in c:\users\admin\anaconda3\envs\dataespacial_31111\lib\site-packages (from pandas!=1.5.0,>=1.4->mapclassify) (2023.3)
Requirement already satisfied: joblib>=1.2.0 in c:\users\admin\anaconda3\envs\dataespacial_31111\lib\site-packages (from scikit-learn>=1.0->mapclassify) (1.4.2)
Requirement already satisfied: threadpoolctl>=3.1.0 in c:\users\admin\anaconda3\envs\dataespacial_31111\lib\site-packages (from scikit-learn>=1.0->mapclassify) (3.6.0)
Requirement already satisfied: six>=1.5 in c:\users\admin\anaconda3\envs\dataespacial_31111\lib\site-packages (from python-dateutil>=2.8.2->pandas!=1.5.0,>=1.4->mapclassify) (1.16.0)
In [49]:
indicatorsByRegion.plot(column =('fragility', 'median'),scheme='quantiles', cmap='OrRd',
                        legend=True,
                        legend_kwds={"title": "Fragility",'loc': 'lower left'},
                        edgecolor='black',linewidth=0.2,
                        figsize=(15, 10))
Out[49]:
<Axes: >
No description has been provided for this image

Ejercicio 3¶

  1. Select some points from your maps.
  2. Create the convex hull for those points.
  3. Turn the hull into a GDF.
  4. Plot the hull on top of the country.

Parte 1¶

In [50]:
airportsCanada.head()
Out[50]:
name kind latitude_deg longitude_deg elevation_ft region_name municipality geometry
0 Lac-des-Loups Airport closed 46.982201 -76.482498 NaN Quebec Lac-des-Loups POINT (1475490.966 977440.662)
1 Pourvoirie Joncas Airstrip small_airport 47.105400 -77.631104 NaN Quebec Saint-Lazare POINT (1387233.147 966022.396)
2 RCAF Station Buttress closed 50.236099 -105.547997 NaN Saskatchewan Moose Jaw POINT (-678527.039 1170461.817)
3 RCAF Station Aylmer closed 42.805901 -80.944199 NaN Ontario Aylmer POINT (1246453.428 444135.701)
4 RCAF Station Lincoln Park closed 51.009399 -114.133003 NaN Alberta Calgary POINT (-1254351.163 1378637.231)
In [51]:
large_airport=airportsCanada[airportsCanada.kind=='large_airport']
large_airport.union_all()
Out[51]:
No description has been provided for this image

Parte 2¶

In [52]:
large_airport.union_all().convex_hull
Out[52]:
No description has been provided for this image

Parte 3¶

In [53]:
LargeAirport_hull= gpd.GeoDataFrame(index=[0], crs=large_airport.crs, geometry=[large_airport.union_all().convex_hull])
LargeAirport_hull['name']='large airports hull'

LargeAirport_hull
Out[53]:
geometry name
0 POLYGON ((1330217.176 561723.572, -1931482.214... large airports hull

Parte 4¶

In [54]:
base1=countryCanada.plot(facecolor='#e3ffbb')
large_airport.plot(ax=base1)
LargeAirport_hull.plot(ax=base1,facecolor='green',
                       edgecolor='white',alpha=0.4,
                       hatch='X')
Out[54]:
<Axes: >
No description has been provided for this image

Ejercicio 4¶

Apply two spatial overlays to your maps. If possible. If not, try the codes below.

Intersection¶

In [55]:
municipios_GADMCanada.plot(facecolor="white",edgecolor="black")
Out[55]:
<Axes: >
No description has been provided for this image
In [56]:
# the north
MunisN_canada=municipios_GADMCanada.cx[:,yCoordCentroid:]
# the south
MunisS_canada=municipios_GADMCanada.cx[:,:yCoordCentroid]
# the west
MunisW_canada=municipios_GADMCanada.cx[:xCoordCentroid,:]
# the east
MunisE_canada=municipios_GADMCanada.cx[xCoordCentroid:,:]
In [57]:
base2=MunisN_canada.plot(facecolor='yellow', edgecolor='black',linewidth=0.2, alpha=0.6)
MunisS_canada.plot(facecolor='grey', edgecolor='black',linewidth=0.2,ax=base2, alpha=0.4)
Out[57]:
<Axes: >
No description has been provided for this image
In [58]:
base3=MunisE_canada.plot(facecolor='yellow', edgecolor='black',linewidth=0.2, alpha=0.6)
MunisW_canada.plot(facecolor='grey', edgecolor='black',linewidth=0.2,ax=base3, alpha=0.4)
Out[58]:
<Axes: >
No description has been provided for this image
In [59]:
MunisNS_canada=MunisN_canada.overlay(MunisS_canada, how="intersection",keep_geom_type=True)
MunisNS_canada.plot()
Out[59]:
<Axes: >
No description has been provided for this image
In [60]:
# keeping the overlay
MunisWE_canada=MunisW_canada.overlay(MunisE_canada, how="intersection",keep_geom_type=True)
MunisWE_canada.plot(edgecolor='white',linewidth=0.1)
Out[60]:
<Axes: >
No description has been provided for this image

Union¶

In [61]:
MunisNS_canada.columns
Out[61]:
Index(['GID_2_1', 'GID_0_1', 'COUNTRY_1', 'GID_1_1', 'NAME_1_1', 'NL_NAME_1_1',
       'NAME_2_1', 'VARNAME_2_1', 'NL_NAME_2_1', 'TYPE_2_1', 'ENGTYPE_2_1',
       'CC_2_1', 'HASC_2_1', 'GID_2_2', 'GID_0_2', 'COUNTRY_2', 'GID_1_2',
       'NAME_1_2', 'NL_NAME_1_2', 'NAME_2_2', 'VARNAME_2_2', 'NL_NAME_2_2',
       'TYPE_2_2', 'ENGTYPE_2_2', 'CC_2_2', 'HASC_2_2', 'geometry'],
      dtype='object')
In [62]:
MunisWE_canada.columns
Out[62]:
Index(['GID_2_1', 'GID_0_1', 'COUNTRY_1', 'GID_1_1', 'NAME_1_1', 'NL_NAME_1_1',
       'NAME_2_1', 'VARNAME_2_1', 'NL_NAME_2_1', 'TYPE_2_1', 'ENGTYPE_2_1',
       'CC_2_1', 'HASC_2_1', 'GID_2_2', 'GID_0_2', 'COUNTRY_2', 'GID_1_2',
       'NAME_1_2', 'NL_NAME_1_2', 'NAME_2_2', 'VARNAME_2_2', 'NL_NAME_2_2',
       'TYPE_2_2', 'ENGTYPE_2_2', 'CC_2_2', 'HASC_2_2', 'geometry'],
      dtype='object')
In [63]:
MunisNS_canada.head()
Out[63]:
GID_2_1 GID_0_1 COUNTRY_1 GID_1_1 NAME_1_1 NL_NAME_1_1 NAME_2_1 VARNAME_2_1 NL_NAME_2_1 TYPE_2_1 ... NAME_1_2 NL_NAME_1_2 NAME_2_2 VARNAME_2_2 NL_NAME_2_2 TYPE_2_2 ENGTYPE_2_2 CC_2_2 HASC_2_2 geometry
0 CAN.1.7_1 CAN Canada CAN.1_1 Alberta NA Division No. 16 NA NA Census Division ... Alberta NA Division No. 16 NA NA Census Division Census Division 16 CA.AB.ST POLYGON ((-876147.827 1784440.101, -878663.163...
1 CAN.1.8_1 CAN Canada CAN.1_1 Alberta NA Division No. 17 NA NA Census Division ... Alberta NA Division No. 17 NA NA Census Division Census Division 17 CA.AB.SN POLYGON ((-1089738.295 1789849.461, -1089762.4...
2 CAN.2.15_1 CAN Canada CAN.2_1 British Columbia NA Kitimat-Stikine NA NA Regional District ... British Columbia NA Kitimat-Stikine NA NA Regional District Regional District 49 CA.BC.KS MULTIPOLYGON (((-2129845.346 1898535.118, -212...
3 CAN.2.20_1 CAN Canada CAN.2_1 British Columbia NA Northern Rockies NA NA Regional District ... British Columbia NA Northern Rockies NA NA Regional District Regional District 59 CA.BC.NR POLYGON ((-1294939.496 2443124.579, -1295425.2...
4 CAN.2.22_1 CAN Canada CAN.2_1 British Columbia NA Peace River NA NA Regional District ... British Columbia NA Peace River NA NA Regional District Regional District 55 CA.BC.PC POLYGON ((-1531754.065 1808723.434, -1531947.1...

5 rows × 27 columns

In [64]:
keep=['COUNTRY_1','NAME_1_1','NAME_2_1','geometry']
MunisNS_canada=MunisNS_canada.loc[:,keep]
MunisWE_canada=MunisWE_canada.loc[:,keep]
In [65]:
# now
MunisNS_canada.overlay(MunisWE_canada,how="union",keep_geom_type=True)
Out[65]:
COUNTRY_1_1 NAME_1_1_1 NAME_2_1_1 COUNTRY_1_2 NAME_1_1_2 NAME_2_1_2 geometry
0 Canada Nunavut Baffin Canada Nunavut Baffin MULTIPOLYGON (((1009456.723 1957149.413, 10094...
1 Canada Nunavut Keewatin Canada Nunavut Keewatin MULTIPOLYGON (((66147.242 2222412.329, 66059.8...
2 Canada Alberta Division No. 16 NaN NaN NaN POLYGON ((-876147.827 1784440.101, -878663.163...
3 Canada Alberta Division No. 17 NaN NaN NaN POLYGON ((-1089738.295 1789849.461, -1089762.4...
4 Canada British Columbia Kitimat-Stikine NaN NaN NaN MULTIPOLYGON (((-2129845.346 1898535.118, -212...
5 Canada British Columbia Northern Rockies NaN NaN NaN POLYGON ((-1294939.496 2443124.579, -1295425.2...
6 Canada British Columbia Peace River NaN NaN NaN POLYGON ((-1531754.065 1808723.434, -1531947.1...
7 Canada British Columbia Stikine NaN NaN NaN POLYGON ((-1709497.208 2136717.838, -1710803.5...
8 Canada Newfoundland and Labrador Division No. 10 NaN NaN NaN MULTIPOLYGON (((2587482.903 2129780.867, 25874...
9 Canada Newfoundland and Labrador Division No. 11 NaN NaN NaN MULTIPOLYGON (((2296029.442 2157856.905, 22959...
10 Canada Northwest Territories Fort Smith NaN NaN NaN POLYGON ((-862595.484 2321392.142, -862620.461...
11 Canada Québec Nord-du-Québec NaN NaN NaN MULTIPOLYGON (((1176401.019 1388745.91, 117640...
12 Canada Saskatchewan Division No. 18 NaN NaN NaN POLYGON ((-633643.973 1586424.759, -633963.859...
13 NaN NaN NaN Canada Manitoba Division No. 1 POLYGON ((50899.64 985073.581, 50207.421 98506...
14 NaN NaN NaN Canada Manitoba Division No. 18 POLYGON ((-67650.837 1151062.721, -67656.755 1...
15 NaN NaN NaN Canada Manitoba Division No. 19 POLYGON ((-22091.706 1157517.047, -23309.103 1...
16 NaN NaN NaN Canada Manitoba Division No. 22 POLYGON ((113321.005 1474487.223, 112526.575 1...
17 NaN NaN NaN Canada Manitoba Division No. 23 MULTIPOLYGON (((384832.145 1893128.254, 384833...
18 NaN NaN NaN Canada Nunavut Kitikmeot MULTIPOLYGON (((-518030.217 3026589.385, -5180...
In [66]:
MunisNS_canada.overlay(MunisWE_canada,how="union",keep_geom_type=True).dissolve().plot()
Out[66]:
<Axes: >
No description has been provided for this image
In [67]:
muniMidCanada=MunisNS_canada.overlay(MunisWE_canada,how="union",keep_geom_type=True).dissolve()
In [68]:
muniMidCanada
Out[68]:
geometry COUNTRY_1_1 NAME_1_1_1 NAME_2_1_1 COUNTRY_1_2 NAME_1_1_2 NAME_2_1_2
0 MULTIPOLYGON (((-2135867.393 1877360.263, -213... Canada Nunavut Baffin Canada Nunavut Baffin
In [69]:
# some cleaning

muniMidCanada['zone']='middles'
muniMidCanada=muniMidCanada.loc[:,['COUNTRY_1_1','zone','geometry']]
muniMidCanada
Out[69]:
COUNTRY_1_1 zone geometry
0 Canada middles MULTIPOLYGON (((-2135867.393 1877360.263, -213...