A Python library to easily visualize geospatial data of Morocco.
Project description
Welcome to geomaroc
A Python library to make working with geospatial data of Morocco easier.
- GitHub repo: https://github.com/AmineAndam04/geomaroc
- PyPI: https://pypi.org/project/geomaroc/
- Raw data: https://github.com/AmineAndam04/geomaroc-Raw-data
- R version: https://github.com/AmineAndam04/R-geomaroc
- CRAN: https://CRAN.R-project.org/package=geomaroc
Introduction
People who work in data science are seeing increased need to work with geospatial data, especially for visualization purposes (e.g. during the covid-19 pandemic).Geopandas is a very popular geospatial library in python that extends Pandas to allow spatial operations on geometrics types.
Working with geopands requires having access to coordinates of the items of our map (polygon coordinates), but having accesss to those coordinates is not an easy task.In fact, we often need the shapefiles in order to plot a map. Trying to find those shapefiles can be a long journey, especailly for someone with zero experience with geospatial data. Moreover, for someone interested in the geospatial data of Morocco, the majority of shapefiles available online are either of very poor quality, or they don't provide province-level,prefectue-level or district-level coordinates.Even if we manage to find the appropriate shapefiles, they usually come without the southern regions of Morocco.
Geomaroc helps the user get those coordinates easly.This library aims to fix these problem by:
1. providing methods to automatically get the boundary coordinates to plot maps of Morocco **without having acces to shapefiles.**
2. providing access to the coordinates of low-level administrative subdivisions (e.g. province, prefecture, districs).
3. providing access to the complete map of Morocco (including the southern regions of Morocco)
illustration:
To generate those plots go to Gallery
Requirements
geomaroc library needs the following packages :pandas, geopandas, shapely, json and importlib.
Install
pip install geomaroc
import geomaroc
Usage
- getRegion() :Helps to plot the shape of each region.
import geomaroc
## working with n_region
gp=geomaroc.getRegion("Casablanca-Settat")
gp.plot()
## working with id_region
gp=geomaroc.getRegion(id_region=6) # Attention!! don't write geomaroc.getRegion(6)
gp.plot()
- getMultiRegion() :Helps to plot the shape of multiple regions.
import geomaroc
## working with n_region
gp=geomaroc.getMultiRegion(["Casablanca-Settat",Draa-Tafilalet])
gp.plot()
## working with id_region
gp=geomaroc.getMultiRegion(id_region=[6,8])
gp.plot()
- getProvince() :Helps to plot the shape of provinces within a region.
import geomaroc
## working with n_region
gp=geomaroc.getProvince("Casablanca-Settat")
gp.plot()
## working with id_region
gp=geomaroc.getProvince(id_region=6)
gp.plot()
- getMultiProvince(): Helps to plot the shape of provinces in multiple regions.
import geomaroc
## working with n_region
gp=geomaroc.getMultiProvince(["Casablanca-Settat",Draa-Tafilalet])
gp.plot()
## working with id_region
gp=geomaroc.getMultiProvince(id_region=[6,8])
gp.plot()
- getDistrict(): Helps to plot the shape of districts within a province.
import geomaroc
## working with n_province
geomaroc.getDistrict("Tetouan")
gp.plot()
## working with id_province
gp=geomaroc.getProvince(id_region=571)
gp.plot()
- getMultiDistrict(): Helps to plot the shape of districts in multiple provinces.
import geomaroc
## working with n_province
gp=geomaroc.gp=geomaroc.getMultiDistrict(["Tetouan","Tanger-Assilah","Al-Hoceima"])
gp.plot()
## working with id_province
gp=geomaroc.geomaroc.getProvince(id_region=[571,51,511])
gp.plot()
- Regions() & Provinces() : Hepls to respect the notation and to get the id of each region and province
Notation
We adpoted this methode to work with names and id of regions,provinces and districts :
- replace "é" with "e"
- replace "è" with "e"
- replace " " with "-"
- replace "â" with "a"
So "Tanger-Tétouan-Al Hoceima" becomes "Tanger-Tetouan-Al-Hoceima" and "Drâa-Tafilalet" becomes "Drâa-Tafilalet"
Use geomaroc.Regions() and geomaroc.Provinces() to check the notations:
region=geomaroc.Regions()
region
{'Beni-Mellal-Khenifra': 5,
'Casablanca-Settat': 6,
'Draa-Tafilalet': 8,
'Eddakhla-Oued-Eddahab': 12,
'Fes-Meknes': 3,
'Guelmim-Oued-Noun': 10,
'Laayoune-Sakia-El-Hamra': 11,
'Marrakech-Safi': 7,
'Oriental': 2,
'Rabat-Sale-Kenitra': 4,
'Souss-Massa': 9,
'Tanger-Tetouan-Al-Hoceima': 1}
import pandas as pd
provinces=geomaroc.Provinces()
province=pd.DataFrame(columns=["Region","Id_region","Province","Id_province"])
for i in range(len(provinces.keys())):
for j in range(len(provinces[list(provinces.keys())[i]])):
reg=list(provinces.keys())[i]
prov=list(provinces[reg].keys())[j]
province=province.append({"Region":reg,"Id_region":region[reg],"Province":prov,"Id_province":provinces[reg][prov]},ignore_index=True)
province
Region Id_region Province Id_province
0 Beni-Mellal-Khenifra 5 Khouribga 311
1 Beni-Mellal-Khenifra 5 Khenifra 301
2 Beni-Mellal-Khenifra 5 Azilal 81
3 Beni-Mellal-Khenifra 5 Beni-Mellal 91
4 Beni-Mellal-Khenifra 5 Fquih-Ben-Salah 255
... ... ... ... ...
70 Tanger-Tetouan-Al-Hoceima 1 Mdiq-Fnidq 573
71 Tanger-Tetouan-Al-Hoceima 1 Ouezzane 405
72 Tanger-Tetouan-Al-Hoceima 1 Tanger-Assilah 511
73 Tanger-Tetouan-Al-Hoceima 1 Tetouan 571
74 Tanger-Tetouan-Al-Hoceima 1 Al-Hoceima 51
Raw data
Visit geomaroc raw data
gallery
Project details
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