我一直试图绕过这一段时间。我试图获取一个csv文件，提取所有行，连接2个值，取这两个值来计算距离csv的第三个值的距离，用csv存储距离和正确的数据，最后我需要找到最短的距离，并返回一个我尚未使用的所有值的字典。
with open(filename,'r') as csvfile:
reader = csv.DictReader(csvfile)
#create a multi-dimensional dictionary with the store name as keyword
new_dict = {}
try:
for row in reader:
new_dict[row['name']] ={}
new_dict[row['name']]['name'] = row['name']
new_dict[row['name']]['dist'] = {}
new_dict[row['name']]['address'] = row['address']
new_dict[row['name']]['city'] = row['city']
new_dict[row['name']]['state'] = row['state']
new_dict[row['name']]['zip'] = row['zip']
latt = str(row['latitude'])
longi = str(row['longitude'])
#concantenate latt and longi for use in grate_circle distance calculation
pharm_loc = latt + ','+ longi
#add distance from usr_loc for each store to dict for each store
new_dict[row['name']]['dist'] = str(calc_dist(usr_loc, store_loc))
我终于修复了这个部分，现在我需要帮助过滤掉除了最接近的结果以外的所有结果......我出于某种原因似乎无法理解这一点。任何帮助将不胜感激。
--- --- EDIT 现在正在运行的更新代码。这产生了一个多维字典如下...... {＆＃39; CONTINENTAL＆＃39;：{＆＃39; city＆＃39;：＆＃39; TOPEKA＆＃39;＆＃39; dist＆＃39;：＆＃39; 50.3131329882＆＃39;，＆ ＃39;姓名＆＃39;：＆＃39; CONTINENTAL PHARMACY LLC＆＃39;＆＃39; zip＆＃39;：＆＃39; 66603＆＃39;，＆＃39; state＆＃39;：＆＃39; KS＆＃39;，＆＃39;地址＆＃39;：＆＃39; 821 SW 6TH AVE＆＃39;}，＆＃39; DILLON＆＃39;：{＆＃39; city＆＃39;：＆＃39; ; TOPEKA＆＃39;＆＃39; dist＆＃39;：＆＃39; 48.3573823197＆＃39;，＆＃39; name＆＃39 ;:＆＃39; DILLON PHARMACY＆＃39;，＆＃39; zip＆＃ 39;：＆＃39; 66605＆＃39;，＆＃39;州＆＃39;：＆＃39; KS＆＃39;，＆＃39;地址＆＃39;：＆＃39; 2010 SE 29TH ST＆＃39; }}
dict中有更多条目，我只需要过滤到最近的位置并仅返回该位置的值。