italy-geopop 0.6.2

A python package that provides instant access to italian geospatial and population data.

🗺️ 🇮🇹 Italy-geopop

• 🗺️ 🇮🇹 Italy-geopop
  • 🧐 What is it?
  • 🚀 Main features
  • 🏪 Where to get it
  • 🔌 Example of use
  • 📖 License
  • 🔎 Full docs reference
  • 👩‍💻 Contributes
  • 🐛 Bugs and issues

🧐 What is it?

Italy-geopop is a python library that provides instant access to italian geospatial and population data.

🚀 Main features

• Easy access to italian geospatial and population data
• Easy geospatial plot made possible by the usage of geopandas
• Multiple years of population and geospatial data available (2022, 2023)
• Population data available by age and sex with customable age ranges
• Easy linkage of italy-geopop data with your data made possible by using pandas and the registration of italy-geopop as pandas accessor

You only need a list of municipalities (or municipality ISTAT codes), provinces (or province ISTAT codes or province abbreviations (e.g. Torino -> TO)) and regions (or region ISTAT codes). ISTAT codes can be found here or here.

🏪 Where to get it

PyPi

pip install italy-geopop, as simple as that.

GitHub - specific version (e.g. 0.1.1)

pip install git+https://github.com/zenodallavalle/italy-geopop.git@v0.1.1

GitHub - latest (main branch)

pip install git+https://github.com/zenodallavalle/italy-geopop.git@main

GitHub - development branch

pip install git+https://github.com/zenodallavalle/italy-geopop.git@dev

🔌 Example of use

>>> from italy_geopop.pandas_extension import pandas_activate
>>> pandas_activate(include_geometry=False, data_year=2022)

>>> pd.Series(["Torino", "Agliè", "Airasca"]).italy_geopop.from_municipality(population_limits='total')

	municipality_code	municipality	province_code	province	province_short	region	region_code	cadastral_code	geometry	population_F	population_M	population
0	1272	Torino	1	Torino	TO	Piemonte	1	L219	MULTIPOLYGON	441686.0	407062.0	848748.0
1	1001	Agliè	1	Torino	TO	Piemonte	1	A074	MULTIPOLYGON	1347.0	1215.0	2562.0
2	1002	Airasca	1	Torino	TO	Piemonte	1	A109	MULTIPOLYGON	1793.0	1867.0	3660.0

>>> pd.Series(["Torino", "Milano", "Venezia"]).italy_geopop.from_province(population_limits=[50], population_labels=['below_50', 'above_equal_50'])

	province_code	province	province_short	municipalities	region	region_code	geometry	below_50_F	above_equal_50_F	below_50_M	above_equal_50_M	below_50	above_equal_50
0	1	Torino	TO	[{'cadastral_code': 'A074'	Piemonte	1	POLYGON	550793.0	586366.0	572143.0	499068.0	1122936.0	1085434.0
1	15	Milano	MI	[{'cadastral_code': 'A010'	Lombardia	3	MULTIPOLYGON	857481.0	792711.0	898004.0	666434.0	1755485.0	1459145.0
2	27	Venezia	VE	[{'cadastral_code': 'A302'	Veneto	5	POLYGON	205100.0	224401.0	214116.0	193299.0	419216.0	417700.0

> > > pd.Series(["Piemonte", "Lombardia", "Veneto"]).italy_geopop.from_region()

	region_code	region	provinces	geometry	<3_F	3-11_F	11-19_F	19-25_F	25-50_F	50-65_F	65-75_F	>=75_F	<3_M	3-11_M	11-19_M	19-25_M	25-50_M	50-65_M	65-75_M	>=75_M	<3	3-11	11-19	19-25	25-50	50-65	65-75	>=75
0	1	Piemonte	[{'municipalities': array	POLYGON	40122.0	131269.0	149768.0	112474.0	614252.0	506764.0	279224.0	348632.0	42361.0	138788.0	159618.0	123911.0	629878.0	490464.0	251918.0	236907.0	82483.0	270057.0	309386.0	236385.0	1244130.0	997228.0	531142.0	585539.0
1	3	Lombardia	[{'municipalities': array	MULTIPOLYGON	103867.0	336353.0	378153.0	274455.0	1520576.0	1144338.0	586818.0	716916.0	109087.0	356547.0	403719.0	303888.0	1572013.0	1135834.0	524720.0	475720.0	212954.0	692900.0	781872.0	578343.0	3092589.0	2280172.0	1111538.0	1192636.0
2	5	Veneto	[{'municipalities': array	POLYGON	48285.0	157284.0	182441.0	136850.0	718105.0	578543.0	291166.0	354328.0	51390.0	166176.0	194064.0	149055.0	737009.0	573454.0	267403.0	242192.0	99675.0	323460.0	376505.0	285905.0	1455114.0	1151997.0	558569.0	596520.0

> > > pd.Series(["Regione Lombardia", "Regione del Veneto", "Veneto o Lombardia", 15]).italy_geopop.smart_from_region()

	region_code	region	provinces	geometry	<3_F	3-11_F	11-19_F	19-25_F	25-50_F	50-65_F	65-75_F	>=75_F	<3_M	3-11_M	11-19_M	19-25_M	25-50_M	50-65_M	65-75_M	>=75_M	<3	3-11	11-19	19-25	25-50	50-65	65-75	>=75
0	3.0	Lombardia	[{'municipalities': array	MULTIPOLYGON	103867.0	336353.0	378153.0	274455.0	1520576.0	1144338.0	586818.0	716916.0	109087.0	356547.0	403719.0	303888.0	1572013.0	1135834.0	524720.0	475720.0	212954.0	692900.0	781872.0	578343.0	3092589.0	2280172.0	1111538.0	1192636.0
1	5.0	Veneto	[{'municipalities': array	POLYGON	48285.0	157284.0	182441.0	136850.0	718105.0	578543.0	291166.0	354328.0	51390.0	166176.0	194064.0	149055.0	737009.0	573454.0	267403.0	242192.0	99675.0	323460.0	376505.0	285905.0	1455114.0	1151997.0	558569.0	596520.0
2	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan
3	15.0	Campania	[{'municipalities': array	MULTIPOLYGON	65798.0	201345.0	239653.0	185798.0	909861.0	641838.0	320637.0	311913.0	69298.0	213525.0	253444.0	200452.0	907541.0	602405.0	288497.0	212415.0	135096.0	414870.0	493097.0	386250.0	1817402.0	1244243.0	609134.0	524328.0

📖 License

Italy-geopop is distributed under Creative Commons license (CC-BY-4.0). Full license can be read at LICENSE.

Italy-geopop includes data from:

• openpolis/geojson-italy, at the dime of writing distributed under Creative Commons license (CC-BY-4.0)
• ISTAT data, at the time of writing distributed under Creative Commons license (CC-BY-3.0), more info here

🔎 Full docs reference

You can find full docs on italy-geopop.readthedocs.io.

👩‍💻 Contributes

• Zeno Dalla Valle - creator and mantainer

🐛 Bugs and issues

If you experience an issue using this library first check the FAQ, you may find an immediate solution to your problem.

If your problem is not listed or the proposed solution did not worked for you, please report bugs via GitHub issues here providing also a minimum reproducible example.