我正在运行以下测试代码,以通过“NearVicinity”和“MidVicinity”将违规行为映射到附近的buildingID。结果出乎意料,我不确定我的代码中缺少什么。
所以我得到的结果似乎已正确更新'TicketIssuedDT'和'NearVicinity','MidVicinity'然后'BuildingID'和'X'列只能正确映射到结果['X'] [0]和结果[ 'BuildingID'] [0]。剩余的999行对于'BuildingID'和'X'都有0。
result = pd.DataFrame(np.zeros((1000, 5)),columns=['BuildingID', 'TicketIssuedDT', 'NearVicinity', 'MidVicinity','X'])
z = 0
for i in range(0,10):
#for i, j in dataframe2.iterrows():
dataframe2Lat = dataframe2['Latitude'][i]
dataframe2Long = dataframe2['Longitude'][i]
for x in range(0,11102):
#for x, y in dataframe1.iterrows():
dist = (math.fabs(dataframe2Long - dataframe1['Longitude'][x]) + math.fabs(dataframe2Lat - dataframe1['Latitude'][x]))
if dist < .02:
result['X'][z] = x
result['BuildingID'][z] = dataframe1['BuildingID'][x]
result['TicketIssuedDT'][z] = dataframe2['TicketIssuedDT'][i]
result['MidVicinity'][z] = 1
if dist < .007:
result['NearVicinity'][z] = 1
else:
result['NearVicinity'][z] = 0
z += 1
print(i)