为什么此python函数返回重复列表？

如何解决为什么此python函数返回重复列表？

我正在尝试编写一个代码块，该代码块作用于两组地理坐标（在这种情况下为邻里和暴力犯罪）。它计算每个街区500m半径内的犯罪数量，将这些数字添加到列表中，然后将该列表与街区数据集合并。

#For each neighbourhood in city find all crimes committed within a 500m radius

from geopy import distance

def Crime_in_Hood(crimes):
#counts number of crimes in 500m radius of neighbourhood
   crime_count = 0
   
   for index,crime in crimes.iterrows():
       test_point = [{crime['Latitude'],crime['Longitude']}]
       radius = 0.5# in km

       center_point_tuple = tuple(center_point)
       test_point_tuple = tuple(test_point)

       dis = distance.distance(center_point_tuple,test_point_tuple).km

       if dis <= radius:
           crime_count = crime_count + 1
           
   return crime_count


def Crime_in_City(crimes,hoods):
#returns number of crimes for each neighbourhood in city
   
#instantiate crime tally
   violent_crimes = []
   
   for index,hood in hoods.iterrows():
       center_point = [{hood['Latitude'],hood['Longitude']}]
       crime_count = Crime_in_Hood(crimes,hoods)
       violent_crimes.append(crime_count)
       
   return violent_crimes

       
def Crime_Counter(crimes,hoods):

#Add the number of crimes committed to dataframe for each neighbourhood in city
   violent_crimes = Crime_in_City(crimes,hoods)

   #Add violent_crimes to hoods
   hoods["Violent Crimes"] = violent_crimes
   return hoods 


ny_hoods = Crime_Counter(ny_c,ny_hoods)
ny_hoods.head()  

问题是它返回一个数据框，其中“暴力犯罪”列中的每个值都相同。

我用不同的值测试了Crime_in_Hood函数，它可以按预期工作。但是，Crime_in_City返回一个列表，该列表的最后一个Crime_count值会一遍又一遍地重复。所以现在我的问题就在这里，而不是如何解决。据我所知，Crime_in_Hood应该为Crime_in_City的每次迭代返回不同的值，并将其附加到violent_crimes，但这不是。

有什么想法吗？

解决方法

Crime_in_Hood（crimes）仅具有一个已定义的参数，但是您在此处使用2个参数来调用它：Crime_count = Crime_in_Hood（crimes，敞篷）。这就是您的代码的外观（如下）。 ny_c和ny_hoods都应该是带有float64值的“纬度”和“经度”列的pandas DataFrame。除此之外，我不确定在以下方面有关geopy的工作方式：{Latitude，Longitude}表示法。

#For each neighbourhood in city find all crimes committed within a 500m radius

from geopy import distance

def Crime_in_Hood(crimes,center_point):
#counts number of crimes in 500m radius of neighbourhood
   crime_count = 0
   
   for index,crime in crimes.iterrows():
       test_point = [{crime['Latitude'],crime['Longitude']}]
       radius = 0.5# in km

       center_point_tuple = tuple(center_point)
       test_point_tuple = tuple(test_point)

       dis = distance.distance(center_point_tuple,test_point_tuple).km

       if dis <= radius:
           crime_count = crime_count + 1
           
   return crime_count


def Crime_in_City(crimes,hoods):
#returns number of crimes for each neighbourhood in city
   
#instantiate crime tally
   violent_crimes = []
   
   for index,hood in hoods.iterrows():
       center_point = [{hood['Latitude'],hood['Longitude']}]
       crime_count = Crime_in_Hood(crimes,center_point)
       violent_crimes.append(crime_count)
       
   return violent_crimes


def Crime_Counter(crimes,hoods):

#Add the number of crimes committed to dataframe for each neighbourhood in city
   violent_crimes = Crime_in_City(crimes,hoods)

   #Add violent_crimes to hoods
   hoods["Violent Crimes"] = violent_crimes
   return hoods 


ny_hoods = Crime_Counter(ny_c,ny_hoods)
ny_hoods.head()