Mumakore achangopfuura, mamepu echoropleth ave achinyanya kufarirwa, sezvo achipa nyore-ku-kunzwisisa kumiririrwa kwe data yakaoma nenzira yakajeka uye yakapfupika. Mepu yechoropleth imhando yemepu ine thematic ine nzvimbo dzine mavara kana mapatani zvichienderana nekukosha kweimwe vhezheni. Rimwe rematambudziko mukugadzira mamepu aya kukosha kwekuwedzera mavara, ayo anogona kubatsira vashandisi kunzwisisa ruzivo rwuri kumiririrwa. Muchikamu chino, tichaongorora mhinduro yekuwedzera mavara kune choropleth mepu uchishandisa Python.
Kuwedzera mavara kune choropleth mepu uchishandisa Python
Raibhurari yakajairika yekugadzira choropleth mepu muPython ndeye GeoPandas, iyo inobvumira vashandisi kugadzira uye kushandura geospatial data. GeoPandas inowedzera yakakurumbira pandas library nekupa zvimiro zve data zvakagadzirirwa chaizvo kushanda negeographic data. Kuwedzera mavara kune choropleth mepu yakagadzirwa neGeoPandas, unogona kushandisa iyo kkburemu raibhurari, raibhurari yekuona data yakashandiswa zvakanyanya muPython.
Nhanho-ne-nhanho gwara rekuwedzera mavara kune choropleth mepu muPython
Muchikamu chino, tichafamba kuburikidza nemaitiro ekuwedzera mavara kune choropleth mepu tichishandisa Python neGeoPandas uye matplotlib maraibhurari. Tevera matanho aya:
1. Kutanga, pinza mumaraibhurari anodiwa:
import geopandas as gpd import matplotlib.pyplot as plt
2. Verenga chimiro chefaira iyo ine geographic miganhu yaunoda kushandisa muchoropleth mepu:
data = gpd.read_file('path/to/your/shapefile.shp')
3. Gadzira a choropleth mepu uchishandisa iyo `chirongwa` nzira kubva kuGeoPandas:
ax = data.plot(column='variable', cmap='coolwarm', legend=True)
Ipo `'variable'` inomiririra koramu kubva kune yako data yaunoda kumiririra muchoropleth mepu, uye `'coolwarm'` ndiyo pendi yeruvara. Iwe unogona kugadzirisa palette yemavara nekusarudza dzimwe sarudzo kubva ku matplotlib color schemes.
4. Wedzera mavara kumepu yechoropleth uchishandisa iyo `annotate` basa kubva matplotlib:
for x, y, label in zip(data.geometry.centroid.x, data.geometry.centroid.y, data['variable']):
ax.annotate(label, xy=(x, y), xytext=(x, y), color='black', fontsize=8)
Pano, isu tiri kudzokorora kuburikidza necentroid yepolygon yega yega muGeoDataFrame uye nekuwedzera iyo label (kukosha kwekusiyana) panzvimbo iyoyo.
5. Pakupedzisira, ratidza mepu yechoropleth ine mavara:
plt.show()
Kunzwisisa GeoPandas uye matplotlib
- GeoPandas: GeoPandas iraibhurari ine simba inoita kuti kushanda negeospatial data muPython kuve nyore uye kwakanaka. Inopa zvimiro zvedata zvinoshanda uye maalgorithms ekushanda nedata yenzvimbo, kusanganisira kugona kuverenga nekunyora mafomati akasiyana, kuita mashandiro enzvimbo, uye kupa yepamusoro spatial indexing.
- matplotlib: matplotlib ndeimwe yeanonyanya kufarirwa data kuona maraibhurari muPython, inopa akasiyana siyana ekuronga sarudzo. Yayo yakakura yekusarudzika sarudzo inobvumira vashandisi kugadzira yakaoma uye yakanyanya kurongeka zviono. Muchinyorwa chino, takashandisa matplotlib takabatana neGeoPandas kuwedzera mavara kumepu yedu yechoropleth.
Mukupedzisa, kuwedzera mavara kune choropleth mepu uchishandisa Python zvinogoneka nerubatsiro rweGeoPandas uye matplotlib maraibhurari. Nezvishandiso izvi, iwe unogona kugadzira inodzidzisa uye yakajeka inomiririra inomiririra data yakaoma, zvichiita kuti zvive nyore kune vashandisi kunzwisisa nekududzira ruzivo rwunopihwa.
