我正在尝试对整个列执行操作,但是遇到类型错误,我想创建一个包含Shapely Point的列:
crime_df = crime_df[crime_df['Latitude'].notna()]
crime_df = crime_df[crime_df['Longitude'].notna()]
crime_df['Longitude'] = crime_df['Longitude'].astype(float)
crime_df['Latitude'] = crime_df['Latitude'].astype(float)
print (crime_df['Longitude'])
print (crime_df['Latitude'])
crime_df['point'] = Point(crime_df['Longitude'], crime_df['Latitude'])
输出:
18626 -87.647379
Name: Longitude, Length: 222, dtype: float64
18626 41.781100
Name: Latitude, Length: 222, dtype: float64
TypeError: cannot convert the series to <class 'float'>
我认为您需要分别处理每个点,因此需要具有lambda函数的DataFrame.apply
:
DataFrame.apply
或感谢@N。乌达:
crime_df['point'] = crime_df.apply(lambda x: Point(x['Longitude'], x['Latitude'], axis=1)
或列表理解替代为:
crime_df["point"] = crime_df[["Longitude", "Latitude"]].apply(Point, axis=1)
编辑:我认为矢量化方式可以使用crime_df['point'] = [Point(lon, lat)
for lon, lat in crime_df[['Longitude','Latitude']].values]
,如:
geopandas.points_from_xy