import pandas as pd

housing = pd.read_csv("housing.csv")
housing.plot(kind="scatter", x="longitude", y="latitude", alpha=0.4, s=housing["population"]/100, label="population", figsize=(10,7),c="median_house_value", cmap=plt.get_cmap("jet"), colorbar=True,)
plt.legend()

housing.csv

 longitudelatitudehousing_median_agetotal_roomstotal_bedroomspopulationhouseholdsmedian_incomemedian_house_valueocean_proximity
2260-119.8436.7824324279527647731.338558800INLAND
15778-122.4137.7852153476315206141.4554375000NEAR BAY
12511-121.4338.5544351471415096562.7333100100INLAND
4595-118.2834.0531152573025106521.6355162500<1H OCEAN
13140-121.4138.3424160527719662503.0833162500INLAND
18189-122.0237.37856861489325013294.2782327700<1H OCEAN
19945-119.3636.211810822027932132.403260000INLAND
8132-118.1233.834517343317972934.8917222800<1H OCEAN
598-122.0637.73718933108213154.6005231600NEAR BAY
5923-117.7834.131877981161371012275.8819260500INLAND
17644-121.937.2620444766120626606.8088283300<1H OCEAN
12798-121.4538.6238241960516965031.486163100INLAND
1311-121.8437.9915238038512923884.6029142600INLAND
8097-118.2133.8145181639815243883.8586157900NEAR OCEAN
7595-118.2533.93812012237332063.3804105800<1H OCEAN
20231-119.2734.2623357875314556494.1898359100NEAR OCEAN
2616-124.0940.9518225048412484722.589399600NEAR OCEAN
16483-121.1438.1614259149713714793.5774113900INLAND
9499-123.5338.933817063555062112.5625165600NEAR OCEAN
1350-121.9538.0355526 320710124.0767143100INLAND
3466-118.4734.3213266451814685214.8988325200<1H OCEAN
13411-117.4634.0719315557224826422.9973113400INLAND
1772-122.3637.953810422897732482.7714104700NEAR BAY
4892-118.2534.01284811365961281.239690300<1H OCEAN
Logo

北京人形旗下天工造物具身智能开源社区,聚焦具身天工与慧思开物两大平台

更多推荐