我的数据头如下：
lat1 long1 state county lat2 long2 dist Depot
0 . . AK Aleutians West 11.0 23.0 121 0.0
1 . . AK Wade Hampton 33.0 11.0 12 0.0
2 . . AK North Slope 55.0 11.0 43 0.0
3 . . AK Kenai Peninsula 44.0 11.0 43 0.0
4 . . AK Anchorage 11.0 11.0 99 0.0
5 1 2 AK Anchorage NaN NaN 1e10 0.0
6 . . AK Anchorage 55.0 44.0 33 0.0
7 3 4 AK Anchorage NaN NaN 1e10 0.0
8 . . AK Anchorage 3.0 2.0 23 0.0
9 . . AK Anchorage 5.0 11.0 32 0.0
10 . . AK Anchorage 42.0 22.0 33 0.0
11 . . AK Anchorage 11.0 2.0 33 0.0
12 . . AK Anchorage 444.0 1.0 43 0.0
13 . . AK Anchorage 1.0 2.0 53 0.0
14 0 2 AK Anchorage NaN NaN 1e10 0.0
15 . . AK Anchorage 1.0 1.0 32 0.0
16 . . AK Anchorage 111.0 11.0 22 0.0
距离列指示相应的lat2/long2与lat1/long1中所有条目之间的最小距离。我的代码如下：
import pandas as pd
from haversine import haversine
import numpy as np
path = 'distance.xlsx'
df = pd.read_excel(path, parse_cols = [1,2,4,5,7,8])
df = df.assign(dist=pd.Series(np.zeros(27055)).values);
df = df.assign(Depot=pd.Series(np.zeros(27055)).values);
temp = 1e10
for i in range(0, len(df)):
for j in range(0, len(df)):
if df.iloc[j]['lat1'] is '.' and df.iloc[j]['long1'] is '.':
continue
else:
p1 = (df.iloc[j]['lat1'],df.iloc[j]['long1'])
p2 = (df.iloc[i]['lat2'],df.iloc[i]['long2'])
df.dist.iloc[i] = min(temp,haversine(p1, p2, miles=True))
temp = df.dist.iloc[i]
temp = 1e10
对于每个索引的最小距离，我想知道相应的p2 (lat1,long1)并将其存储在Depot列中。我知道这一定是一些索引命令，但是我正在努力寻找确切的形式。