我有以下两个数据帧(缩写):
df1
day Transmitter_ID Species Lat Lng Date
4 A69-1601-27466 Golden perch -35.495479100000004 144.45295380000002 13/08/2015
5 A69-1601-27466 Golden perch -35.495479100000004 144.45295380000002 14/08/2015
6 A69-1601-27466 Golden perch -35.495479100000004 144.45295380000002 15/08/2015
7 A69-1601-27466 Golden perch -35.495479100000004 144.45295380000002 16/08/2015
8 A69-1601-27466 Golden perch -35.5065473 144.4488804 17/08/2015
8 A69-1601-27466 Golden perch -35.495479100000004 144.45295380000002 17/08/2015
9 A69-1601-27466 Golden perch -35.5065473 144.4488804 18/08/2015
10 A69-1601-27466 Golden perch -35.5065473 144.4488804 19/08/2015
11 A69-1601-27466 Golden perch -35.5065473 144.4488804 20/08/2015
12 A69-1601-27466 Golden perch -35.5065473 144.4488804 21/08/2015
13 A69-1601-27466 Golden perch -35.5065473 144.4488804 22/08/2015
14 A69-1601-27466 Golden perch -35.5065473 144.4488804 23/08/2015
15 A69-1601-27466 Golden perch -35.5065473 144.4488804 24/08/2015
rivergps_df
Lng Lat River
151.7753278 -32.90526725 HUNTER RIVER
151.77526830000002 -32.90610052 HUNTER RIVER
151.77526830000002 -32.90752299 HUNTER RIVER
151.77526830000002 -32.90758849 HUNTER RIVER
151.775397 -32.90977754 HUNTER RIVER
151.7754468 -32.91062396 HUNTER RIVER
151.775578 -32.91202941 HUNTER RIVER
151.77578799999998 -32.9142797 HUNTER RIVER
151.7758178 -32.91459931 HUNTER RIVER
151.77586340000002 -32.91508789 HUNTER RIVER
151.7764116 -32.91645856 HUNTER RIVER
151.7765776 -32.91687345 HUNTER RIVER
151.77719040000002 -32.91861786 HUNTER RIVER我还有一个haversine函数,它接受一对lat,lng,并返回两对之间的距离
def haversine(lon1, lat1, lon2, lat2):
"""
Calculate the great circle distance between two points
on the earth (specified in decimal degrees)
"""
# convert decimal degrees to radians
lon1, lat1, lon2, lat2 = map(radians, [lon1, lat1, lon2, lat2])
# haversine formula
dlon = lon2 - lon1
dlat = lat2 - lat1
a = sin(dlat/2)**2 + cos(lat1) * cos(lat2) * sin(dlon/2)**2
c = 2 * asin(sqrt(a))
r = 6371 # Radius of earth in kilometers. Use 3956 for miles我想对这两个数据帧做的是:
从df1中获取每个lng / lat,并对每个点应用rivergps_df的整个lng / lat范围的半正弦函数
返回半正弦函数的最小值所在的rivergps_df的索引
将此rivergps_df索引追加到df1
所以我的意思是,对于df1 -35.495479100000004,144.45295380000002中的第一个点,我想把半正弦函数应用到这里,比如lon1,lat1,lon2,lat2,其中lon2,lat2是rivergps_df中存在的所有点。然后,我想找出半正弦函数返回的最小值,将其附加到df1,然后移动到df1中的下一个点。
我该怎么做呢?
发布于 2018-12-12 12:21:08
一个想法是:
haversin_argmin(lat, lon, df),该函数遍历df (例如for (lat2, lon2) df[['Lat', 'Lon']].iterrows():)并计算并返回haversine(lat, lon, lat2, lon2).argmin定义另一个函数f,该函数获取row,获取lat和D12,使用D14调用D13,然后返回作为新字段附加的D16的D15。H217 H118使用C19到D20 D21请阅读apply的文档,以更好地了解如何定义f以及传递给apply的选项。
https://stackoverflow.com/questions/53735582
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