python - 读取 CSV 文件的每一列作为字典的键

Question

我正在使用带有 python 的 googlemaps API，我想读取一个包含 LOCATIONID、LOCATION、X、Y、LAT、LNG、REF、ID 的 csv 文件，其中每一个都作为字典键

数据集摘录

ChIJWzKeTARawokRjoqe_C9poOA,THEGIRLSOUTFITS,0,17,40.71380629999999,-74.0222972,dc1885d8c12ac669e9de3a73fedfb08c40deefd3,CmRSAAAA4Mvy3PVnmnYQKIZg-VX9-UrnrhlwOs7YFeY40gdXw1JfuUeEZndlhWxoIdI2K0nt1voCQDg2mqUVKV6EBgOKMTrHjDsMHOy7MJYBCUWguzLroifP1UMWTYSfUJD6E6sMEhB3psbJCGcDh5iS1PHyX4k5GhRBXigoOyADpURVG3NG2bIqXJ2i_g
ChIJDaBbDPlZwokRuHXkJGK9ER0,NYNJ State Line,0,29,40.7245721,-74.02168689999999,3d2cfc0a35b583760187c2369bb957b5a8cd9755,CmRRAAAAN25LD8IWAiu8CAIFM2eMS7eJVReV_UHzmR6sbaRkhDlJgiX-wK0Xlb85hC1qmDkarwQrGoM2u60zfSMr1MxcyzMAg3UDgL6nYwwu3WgG1aNlbpiqR2HlLFlK5XhimqI4EhDrfqXHOxKeztoT01Aicp3hGhSETo6Pj7gTk-dajA0RWco1djlrVA
ChIJQX6hfdlZwokRoCdPrD-8wSY,Shipyard Marina,0,59,40.751581,-74.021287,5f5e1aa75a39ce1880085d5094694a9ceda1ff43,CmRRAAAAp_VV6L2SQgnjC_TeMYRe_m2EYyjo_IdAOUqSeuRM9kbEMHSyguWco9jDV6rdYxk5s1E5s21BX0P7flWfK2LCegcKi1m_AOp2LuYtuzv0ql4-Jeq6-yx50Z180J9U4nrHEhAihnIm2i8MWwk7ATToiLBgGhR-w02BFnO9EGniCms-XWq00VrGOg
ChIJi3MPPNNZwokRDu8nE0ldrwk,Lincoln Harbor,0,68,40.759708,-74.02225,a3192a26d0a5a779da702a7f871612992e26f606,CmRRAAAAGcYQNoc-WgRCwh3rlBzeEmlG_XQgk_coHa4qUpzWU_9DiDWnU8eLjhInrZqpR7nKibXc0dcZIYiZEb-ehKvIrF6OfbLGrpmbf47YNaofAebceKirPZ_g6jMsc-_dcITaEhAKqkWagpXbgd3CcQf8Rtz-GhQtzlAGJlP7gOzV2KfXRGFIF2ZbAA
ChIJq35iOdNZwokRKvT9_KFP8jg,Lincoln Harbor,0,68,40.75984079999999,-74.0223211,38ea8de2bbf6d8a710bec3104d180d71b3d00735,CmRRAAAASNnGG2MHHIDGcXfgH-8iWUQOEahJdMZz6dy24azZrqyXqEtMb_yP1MJRGMV6Cp6lX05MgU2vNIfHcOGBfXiG0yWU7Qe0-t9_Uhm7JxNuAOEge9ZaCwNlrtxuxr8xSYsJEhAkL9vA29DV4nReD4e85D1TGhTbZYRfvNNRZi5a3NMUA0gyMYoR_A
ChIJ07hkOtNZwokRfY7FzKrxTkA,852858 Harbor Blvd,0,68,40.7599265,-74.02213569999999,29cfd2338edc10f94f5464b2fe152ab7bab3fca6,CmRbAAAAdlTDQx7qWhNnvgDQ_1afttKRpJ_MzBULrJLNX0TFEwpvKTjCvCZoXfV1F0A_diKH5D8qDjjucrjUC3gV8iVxqOYoHRGYwifE2FSiVycUrjunQxiDYAd-C6Q7QOqswAomEhAewuH-Q09vSAW_hNbQ0AUOGhQqRXCRrgxc6EAl2xRv1Z73M4MMug
ChIJnYuB1ixYwokR3w26K1mr3JQ,1500 Harbor Blvd,0,69,40.7609258,-74.02135559999999,ed57711af76a2534406a70f21d8a7119170b0f72,CmRbAAAAbPsHkeqeX3cx5MdED0Ao6ic0PE56xhGMdda0zXolIU7KsPmgPbT1CjXfyZ0p4ws_GYgdORZB3qP0idFvWBtMpdYpXCq0VknITsvfAoNfwYXoccYGsP7QvfpBPb1oTnywEhDwyrKX9JiQkYx9YaIXhkOwGhRCtFkL2futi7BkUxo_dMYEtsWVWA
ChIJk7Y29CxYwokRLcD4dsTPCCM,800816 Waterfront Terrace,0,71,40.7629756,-74.0223474,727cf2af87d28ec3a45f11e76e0746acfbec03b0,CmRbAAAAzgEUAIfexip_ePX2VQ29-iZMDPe-5RA4aGhFRoDkEGHrTaUON7ZGyn1r16erRSWIAhESFzycoG4Rwuw4OijSlLjKfK3_HCvC4fkrX-d6I7g7ffkIotwc1KK77UkHPMz-EhBoESHGx4Ke3H9y6XfDt9iaGhSGqEI5BmtpMu4URYwFmrT-2npHWQ
ChIJsZ2B5CxYwokRL8NrRMKxD9Q,Estuary Marketplace,0,71,40.7622809,-74.021577,1b6c2bd55b1bbabe3aac0d1eb2153e812c1026fd,CmRSAAAAO_HAcE9pNnA6r0FDp1eVsfS6jVn31DxU_JhcZNACGz9kfI5xOPjTbgM77JhJLxZPJqLgO_AnNXIIyEQV_wqO5Pr-YWJaIyhCEYA8Ene36VXgQ_90NMQwa_HNJJnWywkpEhBYQL6JbpsO0FJcOawnw5-2GhRE_QU6uh-cP-RKArGSyfEE2cxL3A
ChIJ64dzUNRZwokRIHBPnvi-eJs,Estuary Apartments,0,71,40.76240009999999,-74.0216088,8219ad9d883d8891a651bc35ff7bf7abe7c7b72a,CmRSAAAA7t8RT2MVUpaxNWBPItFU3pTQwNqXDuRY28GxZ_cywaLqOFIJ7taeXDHvGg19Y0MoIerm94HrD0iZQ_iIyoUrCKueeUETgHUGf8LQJMl9mqu784B5iIIXdf9-YrylAFJ9EhCvaowPZkGZvaEVLENy8fywGhRSEtZOm86qEyOCksoFWNJp9L_daw
ChIJWexh_9hZwokRgU6sf8pvbUg,Hoboken Weehawken Notary Public  Dorian Cattani,0,71,40.762501,-74.021528,11be9c0505e8db6a7fcaea5fd4003d336b8667f2,CmRRAAAA9hteDDXN0TehPTxfnx6LxRjZTVHZOyOgbE1GJ42XOzB2v6htFgfliFz39e6llMHSlqvFS3uBiIKuH9bNu9qIfeSD8LlrSW5UXKP4U7sN-Zi1-IWH5QJw5S2hQCZHaNfeEhAT4Y9Q2hC0uG0vVi7CJPuVGhQPb5J4VpGisRfvRfiqEyPgTR8F5w
ChIJRaQT-CxYwokRlEhCGnjf6fs,EcoPure Home Cleaning Service Weehawken,0,72,40.76302460000001,-74.0218549,33800368abbf808a39da3e805c685b245e5baac4,CmRSAAAAyod24y6jY17fcd2b2mk6qgIoN_KWOCNxEN1zDniW9n7RHoWTm-MPXFN6N77XwYzORC-WarFmyP9jULhochuKcXcYP2y2ni7SWFviXVXOBtxvYVlHmfsyHctEvBy_GxKbEhB5ihU8my5kq4lQpQrwGIrQGhT-0cYHqRnMImt55xhU7CBDPPlA1w
ChIJFU-XRyxYwokRo5Do2LLO_mE,New Jersey 495,0,73,40.76429109999999,-74.0220365,23e5baf02ae51b7aeaf94efa56624c064bdbb456,CmRbAAAA_30BmNHIeCFJ7SVhLHWIbSa8llsfKQfYpVRC8X0feMrRlQ9ih9_vKtBfq-KRC6lcagEYQCBRdCfDob2divgzQEbrVkc9dR4v3oIfdyc5l9mlRyTnl1fOBxSeR8xMz78sEhD8FAIlIOza3aIMvqsdfjzrGhTj2R00Cv-lzmKIFEwLumKKd8g1cQ

我正在尝试的当前代码:

import pandas as pd
import numpy as np
import numpy.random as rdm
import matplotlib.pyplot as plt
import math as m

data = np.genfromtxt('PlacesFinalNew.csv', delimiter = ',')
size = int(data.size/8)

dict = {'LOCATIONID':[], 'LOCATION':[], 'X':[],'Y':[],'LAT':[],'LNG':[],'ID':[],'REF':[]}
for i in range(size):
    dict['LOCATIONID'].append(data[i][0])
    dict['LOCATION'].append(data[i][1])
    dict['X'].append(data[i][2])
    dict['Y'].append(data[i][3])
    dict['LAT'].append(data[i][4])
    dict['LNG'].append(data[i][5])
    dict['ID'].append(data[i][6])
    dict['REF'].append(data[i][7])

这适用于除 Location 之外的所有键。当我打印出 dict['LOCATION'] 时，我得到了一个 nan 列表。有人可以向我指出问题吗？

Answer 1

你可以使用zip:

import csv
headers = ['LOCATIONID', 'LOCATION', 'X', 'Y', 'LAT', 'LNG', 'REF', 'ID']
with open('filename.csv') as f:
  data = [dict(zip(headers, i)) for i in csv.reader(f)]

final_results = {i:[c[i] for c in data] for i in headers}

---

import json
print(json.dumps(final_results, indent=4))

输出:

{
"LOCATIONID": [
    "ChIJWzKeTARawokRjoqe_C9poOA",
    "ChIJDaBbDPlZwokRuHXkJGK9ER0",
    "ChIJQX6hfdlZwokRoCdPrD-8wSY",
    "ChIJi3MPPNNZwokRDu8nE0ldrwk",
    "ChIJq35iOdNZwokRKvT9_KFP8jg",
    "ChIJ07hkOtNZwokRfY7FzKrxTkA",
    "ChIJnYuB1ixYwokR3w26K1mr3JQ",
    "ChIJk7Y29CxYwokRLcD4dsTPCCM",
    "ChIJsZ2B5CxYwokRL8NrRMKxD9Q",
    "ChIJ64dzUNRZwokRIHBPnvi-eJs",
    "ChIJWexh_9hZwokRgU6sf8pvbUg",
    "ChIJRaQT-CxYwokRlEhCGnjf6fs",
    "ChIJFU-XRyxYwokRo5Do2LLO_mE"
],
"LOCATION": [
    "THEGIRLSOUTFITS",
    "NYNJ State Line",
    "Shipyard Marina",
    "Lincoln Harbor",
    "Lincoln Harbor",
    "852858 Harbor Blvd",
    "1500 Harbor Blvd",
    "800816 Waterfront Terrace",
    "Estuary Marketplace",
    "Estuary Apartments",
    "Hoboken Weehawken Notary Public  Dorian Cattani",
    "EcoPure Home Cleaning Service Weehawken",
    "New Jersey 495"
],
"X": [
    "0",
    "0",
    "0",
    "0",
    "0",
    "0",
    "0",
    "0",
    "0",
    "0",
    "0",
    "0",
    "0"
],
"Y": [
    "17",
    "29",
    "59",
    "68",
    "68",
    "68",
    "69",
    "71",
    "71",
    "71",
    "71",
    "72",
    "73"
],
"LAT": [
    "40.71380629999999",
    "40.7245721",
    "40.751581",
    "40.759708",
    "40.75984079999999",
    "40.7599265",
    "40.7609258",
    "40.7629756",
    "40.7622809",
    "40.76240009999999",
    "40.762501",
    "40.76302460000001",
    "40.76429109999999"
],
"LNG": [
    "-74.0222972",
    "-74.02168689999999",
    "-74.021287",
    "-74.02225",
    "-74.0223211",
    "-74.02213569999999",
    "-74.02135559999999",
    "-74.0223474",
    "-74.021577",
    "-74.0216088",
    "-74.021528",
    "-74.0218549",
    "-74.0220365"
],
"REF": [
    "dc1885d8c12ac669e9de3a73fedfb08c40deefd3",
    "3d2cfc0a35b583760187c2369bb957b5a8cd9755",
    "5f5e1aa75a39ce1880085d5094694a9ceda1ff43",
    "a3192a26d0a5a779da702a7f871612992e26f606",
    "38ea8de2bbf6d8a710bec3104d180d71b3d00735",
    "29cfd2338edc10f94f5464b2fe152ab7bab3fca6",
    "ed57711af76a2534406a70f21d8a7119170b0f72",
    "727cf2af87d28ec3a45f11e76e0746acfbec03b0",
    "1b6c2bd55b1bbabe3aac0d1eb2153e812c1026fd",
    "8219ad9d883d8891a651bc35ff7bf7abe7c7b72a",
    "11be9c0505e8db6a7fcaea5fd4003d336b8667f2",
    "33800368abbf808a39da3e805c685b245e5baac4",
    "23e5baf02ae51b7aeaf94efa56624c064bdbb456"
],
"ID": [
    "CmRSAAAA4Mvy3PVnmnYQKIZg-VX9-UrnrhlwOs7YFeY40gdXw1JfuUeEZndlhWxoIdI2K0nt1voCQDg2mqUVKV6EBgOKMTrHjDsMHOy7MJYBCUWguzLroifP1UMWTYSfUJD6E6sMEhB3psbJCGcDh5iS1PHyX4k5GhRBXigoOyADpURVG3NG2bIqXJ2i_g",
    "CmRRAAAAN25LD8IWAiu8CAIFM2eMS7eJVReV_UHzmR6sbaRkhDlJgiX-wK0Xlb85hC1qmDkarwQrGoM2u60zfSMr1MxcyzMAg3UDgL6nYwwu3WgG1aNlbpiqR2HlLFlK5XhimqI4EhDrfqXHOxKeztoT01Aicp3hGhSETo6Pj7gTk-dajA0RWco1djlrVA",
    "CmRRAAAAp_VV6L2SQgnjC_TeMYRe_m2EYyjo_IdAOUqSeuRM9kbEMHSyguWco9jDV6rdYxk5s1E5s21BX0P7flWfK2LCegcKi1m_AOp2LuYtuzv0ql4-Jeq6-yx50Z180J9U4nrHEhAihnIm2i8MWwk7ATToiLBgGhR-w02BFnO9EGniCms-XWq00VrGOg",
    "CmRRAAAAGcYQNoc-WgRCwh3rlBzeEmlG_XQgk_coHa4qUpzWU_9DiDWnU8eLjhInrZqpR7nKibXc0dcZIYiZEb-ehKvIrF6OfbLGrpmbf47YNaofAebceKirPZ_g6jMsc-_dcITaEhAKqkWagpXbgd3CcQf8Rtz-GhQtzlAGJlP7gOzV2KfXRGFIF2ZbAA",
    "CmRRAAAASNnGG2MHHIDGcXfgH-8iWUQOEahJdMZz6dy24azZrqyXqEtMb_yP1MJRGMV6Cp6lX05MgU2vNIfHcOGBfXiG0yWU7Qe0-t9_Uhm7JxNuAOEge9ZaCwNlrtxuxr8xSYsJEhAkL9vA29DV4nReD4e85D1TGhTbZYRfvNNRZi5a3NMUA0gyMYoR_A",
    "CmRbAAAAdlTDQx7qWhNnvgDQ_1afttKRpJ_MzBULrJLNX0TFEwpvKTjCvCZoXfV1F0A_diKH5D8qDjjucrjUC3gV8iVxqOYoHRGYwifE2FSiVycUrjunQxiDYAd-C6Q7QOqswAomEhAewuH-Q09vSAW_hNbQ0AUOGhQqRXCRrgxc6EAl2xRv1Z73M4MMug",
    "CmRbAAAAbPsHkeqeX3cx5MdED0Ao6ic0PE56xhGMdda0zXolIU7KsPmgPbT1CjXfyZ0p4ws_GYgdORZB3qP0idFvWBtMpdYpXCq0VknITsvfAoNfwYXoccYGsP7QvfpBPb1oTnywEhDwyrKX9JiQkYx9YaIXhkOwGhRCtFkL2futi7BkUxo_dMYEtsWVWA",
    "CmRbAAAAzgEUAIfexip_ePX2VQ29-iZMDPe-5RA4aGhFRoDkEGHrTaUON7ZGyn1r16erRSWIAhESFzycoG4Rwuw4OijSlLjKfK3_HCvC4fkrX-d6I7g7ffkIotwc1KK77UkHPMz-EhBoESHGx4Ke3H9y6XfDt9iaGhSGqEI5BmtpMu4URYwFmrT-2npHWQ",
    "CmRSAAAAO_HAcE9pNnA6r0FDp1eVsfS6jVn31DxU_JhcZNACGz9kfI5xOPjTbgM77JhJLxZPJqLgO_AnNXIIyEQV_wqO5Pr-YWJaIyhCEYA8Ene36VXgQ_90NMQwa_HNJJnWywkpEhBYQL6JbpsO0FJcOawnw5-2GhRE_QU6uh-cP-RKArGSyfEE2cxL3A",
    "CmRSAAAA7t8RT2MVUpaxNWBPItFU3pTQwNqXDuRY28GxZ_cywaLqOFIJ7taeXDHvGg19Y0MoIerm94HrD0iZQ_iIyoUrCKueeUETgHUGf8LQJMl9mqu784B5iIIXdf9-YrylAFJ9EhCvaowPZkGZvaEVLENy8fywGhRSEtZOm86qEyOCksoFWNJp9L_daw",
    "CmRRAAAA9hteDDXN0TehPTxfnx6LxRjZTVHZOyOgbE1GJ42XOzB2v6htFgfliFz39e6llMHSlqvFS3uBiIKuH9bNu9qIfeSD8LlrSW5UXKP4U7sN-Zi1-IWH5QJw5S2hQCZHaNfeEhAT4Y9Q2hC0uG0vVi7CJPuVGhQPb5J4VpGisRfvRfiqEyPgTR8F5w",
    "CmRSAAAAyod24y6jY17fcd2b2mk6qgIoN_KWOCNxEN1zDniW9n7RHoWTm-MPXFN6N77XwYzORC-WarFmyP9jULhochuKcXcYP2y2ni7SWFviXVXOBtxvYVlHmfsyHctEvBy_GxKbEhB5ihU8my5kq4lQpQrwGIrQGhT-0cYHqRnMImt55xhU7CBDPPlA1w",
    "CmRbAAAA_30BmNHIeCFJ7SVhLHWIbSa8llsfKQfYpVRC8X0feMrRlQ9ih9_vKtBfq-KRC6lcagEYQCBRdCfDob2divgzQEbrVkc9dR4v3oIfdyc5l9mlRyTnl1fOBxSeR8xMz78sEhD8FAIlIOza3aIMvqsdfjzrGhTj2R00Cv-lzmKIFEwLumKKd8g1cQ"
   ]
}