Я написал код, который преобразует физические адреса в географические местоположения → Широта и Долгота, но код, показывающий эту ошибку
ValueError: Несоответствие длины: ожидаемая ось имеет 7 элементов, новые значения имеют 4элементы
File "<ipython-input-261-0135aa76d655>", line 1, in <module>
runfile('C:/Users/xxx/.spyder-py3/eso.py', wdir='C:/Users/xxx/.spyder-py3')
File "C:\Users\xxx\AppData\Local\Continuum\anaconda3\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 827, in runfile
execfile(filename, namespace)
File "C:\Users\xxx\AppData\Local\Continuum\anaconda3\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 110, in execfile
exec(compile(f.read(), filename, 'exec'), namespace)
File "C:/Users/xxx/.spyder-py3/eso.py", line 192, in <module>
write_data(results, i + start_index + 1)
File "C:/Users/xxx/.spyder-py3/eso.py", line 127, in write_data
done.columns = ['Full_Address', 'Lat', 'Long', 'Provider']
File "C:\Users\xxx\AppData\Local\Continuum\anaconda3\lib\site-packages\pandas\core\generic.py", line 5080, in __setattr__
return object.__setattr__(self, name, value)
File "pandas/_libs/properties.pyx", line 69, in pandas._libs.properties.AxisProperty.__set__
File "C:\Users\xxx\AppData\Local\Continuum\anaconda3\lib\site-packages\pandas\core\generic.py", line 638, in _set_axis
self._data.set_axis(axis, labels)
File "C:\Users\xxx\AppData\Local\Continuum\anaconda3\lib\site-packages\pandas\core\internals\managers.py", line 155, in set_axis
'values have {new} elements'.format(old=old_len, new=new_len))
ValueError: Length mismatch: Expected axis has 7 elements, new values have 4 elements
Токовый выход
токовый выход сохраняет результаты в списке, как показано на прилагаемом изображении 
ожидаемый результат:
Сохранение результатов в DataFrame вместо списка , где DataFrame состоит из 6 столбцов («Client_ID», «Client_Name», «Site_ID», «Full_Address», «Latitude», «Longitude») и затем записывает DataFrame в файл CSV в том жепорядок.
Код нуждается в нескольких модификациях.
Пока я написал этот скрипт.
import geocoder
import requests
import time
import glob
import pandas as pd
# ----------------------------- CONFIGURATION -----------------------------#
path = r'D:\SWAM\ERP_Data' # Path of Data
all_files = glob.glob(path + "/*.csv")
li = []
for filename in all_files:
df = pd.read_csv(filename,sep=';', index_col=None, header=0,encoding='latin-1')
#df = pd.read_csv(filename, sep='\t', index_col=None, header=0)
li.append(df)
ERP_Data = pd.concat(li, axis=0, ignore_index=True)
# rename the columns name
ERP_Data.columns = ['Client_ID', 'Client_Name', 'FORME_JURIDIQUE_CLIENT', 'CODE_ACTIVITE_CLIENT', 'LIB_ACTIVITE_CLIENT', 'NACE',
'Company_Type', 'Number_of_Collected_Bins', 'STATUT_TI', 'TYPE_TI', 'HEURE_PASSAGE_SOUHAITE', 'FAMILLE_AFFAIRE',
'CODE_AFFAIRE_MOUVEMENT', 'TYPE_MOUVEMENT_PIECE', 'Freq_Collection', 'Waste_Type', 'CDNO', 'CDQTE',
'BLNO', 'Collection_Date', 'Weight_Ton', 'Bin_Capacity', 'REF_SS_REF_CONTENANT_BL', 'REF_DECHET_PREVU_TI',
'Site_ID', 'Site_Name', 'Street', 'ADRCPL1_SITE', 'ADRCPL2_SITE', 'Post_Code',
'City', 'Country','ZONE_POLYGONE_SITE' ,'OBSERVATION_SITE', 'OBSERVATION1_SITE', 'HEURE_DEBUT_INTER_MATIN_SITE',
'HEURE_FIN_INTER_MATIN_SITE', 'HEURE_DEBUT_INTER_APREM_SITE', 'HEURE_DEBUT_INTER_APREM_SITE', 'JOUR_PASSAGE_INTERDIT', 'PERIODE_PASSAGE_INTERDIT', 'JOUR_PASSAGE_IMPERATIF',
'PERIODE_PASSAGE_IMPERATIF']
# extract specfic columns into a new dataframe
Address_Table= ERP_Data[['Client_ID', 'Client_Name','Site_ID','Street','Post_Code','City','Country']].copy()
# Clean existing whitespace from the ends of the strings
Address_Table=Address_Table.apply(lambda x: x.str.strip(), axis=1)
Address_Table['Site_ID'] =ERP_Data['Site_ID']
# Adding a new column called (Full_Address) that concatenate address columns into one
# for example Karlaplan 13,115 20,STOCKHOLM,Stockholms län, Sweden
Address_Table['Full_Address'] = Address_Table[Address_Table.columns[3:]].apply(lambda x: ','.join(x.dropna().astype(str)), axis=1)
# remove duplicate values in order to minimize the number of gps requests
Temp=Address_Table.drop_duplicates(subset=["Client_ID", "Site_ID", "Client_Name" , "Full_Address"]) # df
addresses=Temp["Full_Address"]
Temp1=Temp.reset_index()
#Temp1=Temp1.drop(['index'], axis=1) # remove the first column 'Address1'
# ----------------------------- CONFIGURATION -----------------------------#
# Set the input and output files
#input_file_path = "input.csv"
input_file_path = "input.csv"
output_file_path = "output" # appends "####.csv" to the file name when it writes the file.
# Where the program starts processing the addresses in the input file
# This is useful in case the computer crashes so you can resume the program where it left off or so you can run multiple
# instances of the program starting at different spots in the input file
start_index = 0
# How often the program prints the status of the running program
status_rate = 100
# How often the program saves a backup file
write_data_rate = 1000
# How many times the program tries to geocode an address before it gives up
attempts_to_geocode = 3
# Time it delays each time it does not find an address
# Note that this is added to itself each time it fails so it should not be set to a large number
wait_time = 3
# ----------------------------- Function Definitions -----------------------------#
# Creates request sessions for geocoding
class GeoSessions:
def __init__(self):
self.Arcgis = requests.Session()
self.Komoot = requests.Session()
# Class that is used to return 3 new sessions for each geocoding source
def create_sessions():
return GeoSessions()
# Main geocoding function that uses the geocoding package to covert addresses into lat, longs
def geocode_address(address, s):
g = geocoder.arcgis(address, session=s.Arcgis)
if (g.ok == False):
g = geocoder.komoot(address, session=s.Komoot)
return g
def try_address(address, s, attempts_remaining, wait_time):
g = geocode_address(address, s)
if (g.ok == False):
time.sleep(wait_time)
s = create_sessions() # It is not very likely that we can't find an address so we create new sessions and wait
if (attempts_remaining > 0):
try_address(address, s, attempts_remaining-1, wait_time+wait_time)
return g
# Function used to write data to the output file
def write_data(data, index):
file_name = (output_file_path + str(index) + ".csv")
print("Created the file: " + file_name)
done = pd.DataFrame(data)
done.columns = ['Full_Address', 'Lat', 'Long', 'Provider']
done.to_csv((file_name + ".csv"), sep=',', encoding='utf8')
# Variables used in the main for loop that do not need to be modified by the user
s = create_sessions()
results = []
failed = 0
total_failed = 0
progress = len(addresses) - start_index
# ----------------------------- Main Loop -----------------------------#
for i, address in enumerate(addresses[start_index:]):
# Print the status of how many addresses have be processed so far and how many of the failed.
if ((start_index + i) % status_rate == 0):
total_failed += failed
print(
"Completed {} of {}. Failed {} for this section and {} in total.".format(i + start_index, progress, failed,
total_failed))
failed = 0
# Try geocoding the addresses
try:
g = try_address(address, s, attempts_to_geocode, wait_time)
if (g.ok == False):
results.append([address, "was", "not", "geocoded"])
print("Gave up on address: " + address)
failed += 1
else:
#some modification here results.append([Temp1.Client_ID[i],Temp1.Client_Name[i],Temp1.Site_ID[i],address, g.latlng[0], g.latlng[1], g.provider])
"Client_ID", "Site_ID", "Client_Name"
# If we failed with an error like a timeout we will try the address again after we wait 5 secs
except Exception as e:
print("Failed with error {} on address {}. Will try again.".format(e, address))
try:
time.sleep(5)
s = create_sessions()
g = geocode_address(address, s)
if (g.ok == False):
print("Did not fine it.")
results.append([address, "was", "not", "geocoded"])
failed += 1
else:
print("Successfully found it.")
# some modification here results.append([Temp1.Client_ID[i],Temp1.Client_Name[i],Temp1.Site_ID[i],address, g.latlng[0], g.latlng[1], g.provider])
except Exception as e:
print("Failed with error {} on address {} again.".format(e, address))
failed += 1
results.append([address, e, e, "ERROR"])
# Writing what has been processed so far to an output file
if (i%write_data_rate == 0 and i != 0):
write_data(results, i + start_index)
# print(i, g.latlng, g.provider)
# Finished (I guess we need some modification here)
write_data(results, i + start_index + 1)
print("Finished! :)")