python – 使用geopy pandas坐标的新列
作者：互联网
我有一个df：
import pandas as pd
import numpy as np
import datetime as DT
import hmac
from geopy.geocoders import Nominatim
from geopy.distance import vincenty
df
city_name state_name county_name
0 WASHINGTON DC DIST OF COLUMBIA
1 WASHINGTON DC DIST OF COLUMBIA
2 WASHINGTON DC DIST OF COLUMBIA
3 WASHINGTON DC DIST OF COLUMBIA
4 WASHINGTON DC DIST OF COLUMBIA
5 WASHINGTON DC DIST OF COLUMBIA
6 WASHINGTON DC DIST OF COLUMBIA
7 WASHINGTON DC DIST OF COLUMBIA
8 WASHINGTON DC DIST OF COLUMBIA
9 WASHINGTON DC DIST OF COLUMBIA
我想得到下面数据框中任何一列的纬度和经度坐标.在处理各个位置的文档时,文档(http://geopy.readthedocs.org/en/latest/#data)非常简单.
>>> from geopy.geocoders import Nominatim
>>> geolocator = Nominatim()
>>> location = geolocator.geocode("175 5th Avenue NYC")
>>> print(location.address)
Flatiron Building, 175, 5th Avenue, Flatiron, New York, NYC, New York, ...
>>> print((location.latitude, location.longitude))
(40.7410861, -73.9896297241625)
>>> print(location.raw)
{'place_id': '9167009604', 'type': 'attraction', ...}
但是我想将函数应用于df中的每一行并创建一个新列.我尝试了以下内容
df['city_coord'] = geolocator.geocode(lambda row: 'state_name' (row))
但我想我的代码中缺少一些东西,因为我得到以下内容：
city_name state_name county_name coordinates
0 WASHINGTON DC DIST OF COLUMBIA None
1 WASHINGTON DC DIST OF COLUMBIA None
2 WASHINGTON DC DIST OF COLUMBIA None
3 WASHINGTON DC DIST OF COLUMBIA None
4 WASHINGTON DC DIST OF COLUMBIA None
5 WASHINGTON DC DIST OF COLUMBIA None
6 WASHINGTON DC DIST OF COLUMBIA None
7 WASHINGTON DC DIST OF COLUMBIA None
8 WASHINGTON DC DIST OF COLUMBIA None
9 WASHINGTON DC DIST OF COLUMBIA None
希望使用Lambda函数我希望这样的东西：
city_name state_name county_name city_coord
0 WASHINGTON DC DIST OF COLUMBIA 38.8949549, -77.0366456
1 WASHINGTON DC DIST OF COLUMBIA 38.8949549, -77.0366456
2 WASHINGTON DC DIST OF COLUMBIA 38.8949549, -77.0366456
3 WASHINGTON DC DIST OF COLUMBIA 38.8949549, -77.0366456
4 WASHINGTON DC DIST OF COLUMBIA 38.8949549, -77.0366456
5 WASHINGTON DC DIST OF COLUMBIA 38.8949549, -77.0366456
6 WASHINGTON DC DIST OF COLUMBIA 38.8949549, -77.0366456
7 WASHINGTON DC DIST OF COLUMBIA 38.8949549, -77.0366456
8 WASHINGTON DC DIST OF COLUMBIA 38.8949549, -77.0366456
9 WASHINGTON DC DIST OF COLUMBIA 38.8949549, -77.0366456
10 GLYNCO GA GLYNN 31.2224512, -81.5101023
我感谢任何帮助.在我得到坐标后,我想要映射它们.任何推荐的映射坐标资源也非常受欢迎.谢谢
解决方法:
您可以调用apply并在每行上传递要执行的函数,如下所示：
In [9]:
geolocator = Nominatim()
df['city_coord'] = df['state_name'].apply(geolocator.geocode)
df
Out[9]:
city_name state_name county_name \
0 WASHINGTON DC DIST OF COLUMBIA
1 WASHINGTON DC DIST OF COLUMBIA
city_coord
0 (District of Columbia, United States of Americ...
1 (District of Columbia, United States of Americ...
然后,您可以访问纬度和经度属性：
In [16]:
df['city_coord'] = df['city_coord'].apply(lambda x: (x.latitude, x.longitude))
df
Out[16]:
city_name state_name county_name city_coord
0 WASHINGTON DC DIST OF COLUMBIA (38.8937154, -76.9877934586326)
1 WASHINGTON DC DIST OF COLUMBIA (38.8937154, -76.9877934586326)
或者通过两次调用申请单行：
In [17]:
df['city_coord'] = df['state_name'].apply(geolocator.geocode).apply(lambda x: (x.latitude, x.longitude))
df
Out[17]:
city_name state_name county_name city_coord
0 WASHINGTON DC DIST OF COLUMBIA (38.8937154, -76.9877934586326)
1 WASHINGTON DC DIST OF COLUMBIA (38.8937154, -76.9877934586326)
你的尝试geolocator.geocode(lambda row：’state_name'(row))也没有做任何事情因此为什么你有一个满了None值的列
编辑
@leb在这里提出了一个有趣的观点,如果你有许多重复值,那么对每个唯一值进行地理编码会更加高效,然后添加：
In [38]:
states = df['state_name'].unique()
d = dict(zip(states, pd.Series(states).apply(geolocator.geocode).apply(lambda x: (x.latitude, x.longitude))))
d
Out[38]:
{'DC': (38.8937154, -76.9877934586326)}
In [40]:
df['city_coord'] = df['state_name'].map(d)
df
Out[40]:
city_name state_name county_name city_coord
0 WASHINGTON DC DIST OF COLUMBIA (38.8937154, -76.9877934586326)
1 WASHINGTON DC DIST OF COLUMBIA (38.8937154, -76.9877934586326)
所以上面使用unique来获取所有唯一值,从它们构造一个dict,然后调用map来执行查找并添加coords,这比尝试按行进行地理编码更有效
标签：geopy,python,pandas 来源： https://codeday.me/bug/20191003/1851242.html