Question

我有以下两个数据框（缩短了）：

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，它需要一对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

我想对两个数据框进行处理：

从df1中获取每个lng / lat，并针对每个点，从rivergps_df的所有lng / lat范围内应用Haversine函数

返回在haversine函数中出现最小值的rivergps_df的索引

将此rivergps_df索引附加到df1

所以我的意思是对于df1中的第一个点-35.495479100000004，144.45295380000002，我想对此应用Haversine函数，如lon1，lat1与lon2，lat2，其中lon2，lat2是rivergps_df中存在的所有点。然后，我想查找haversine函数返回的最小值，将其附加到df1并移至df1中的下一个点。

我该怎么做？

Answer 1

一个主意：

定义一个在haversin_argmin(lat, lon, df)上迭代的函数df（例如for (lat2, lon2) df[['Lat', 'Lon']].iterrows():），并为argmin计算并返回haversine(lat, lon, lat2, lon2)。
然后定义另一个函数f，该函数接受一个row，获取lat和lon，并用haversin_argmin调用rivergps_df ，并返回row，并附加argmin作为新字段。
使用pandas.DataFrame.apply到apply f到df1。

阅读apply的文档，以更好地理解如何定义f以及传递给apply的选项。

遍历两个数据框以应用功能

1 个答案: