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SERVICIO DE FUMIGACIÓN EN LOS DIFERENTES INMUEBLES DE LA SECTUR.

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RECORD SUMMARY ocds-0ud2q6-1336

Total amount

109,187.9

Number of contracts

1

Buying unit

DIRECIÓN GENERAL DE ADMINISTRACIÓN belonging to ADMINISTRACIÓN PORTUARIA INTEGRAL DE DOS BOCAS

PLANNING

No data

CALL FOR TENDERS

Government agency

ADMINISTRACIÓN PORTUARIA INTEGRAL DE DOS BOCAS

Buying unit

DIRECIÓN GENERAL DE ADMINISTRACIÓN

Call type

ADJUDICACION DIRECTA (direct)

Call status

complete

AWARDS AND CONTRACTS

Awarded contract code 1336

Title

SERVICIO DE FUMIGACIÓN EN LOS DIFERENTES INMUEBLES DE LA SECTUR.

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Supplier(s)

Protección y Alarmas Privadas S.A. de C.V. ,

MORESCHI LOPEZ CELIA ,

Canon Mexicana S. de R.L. de C.V. ,

CASA DE LA AMISTAD PARA NIÑOS CON CANCER.I.A.P. ,

POLIMEROS 2000 S.A. DE C.V. ,

CONTROL TECNICO Y REPRESENTACIONES S A DE C V ,

Servicios profesinales Gisnet S.A. De C.V. ,

CRISERIVES S.A. DE C.V.

Amount

109,187.9 pesos mexicanos

Award status

active

Signature date

16 de enero de 2009

Execution period

1 de marzo de 2009 to 31 de diciembre de 2009

Official documents

See awardNotice 1 on official site www.portaltransparencia.gob.mx

This contract is (terminated)

IMPLEMENTATION

No data

GENERAL INFORMATION

Date updated in QQW

9 de mayo de 2021

Source(s)

Portal de Obligaciones de Transparencia (POT)

Part of the project

TodosLosContratos.mx

Organization responsible for the import

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                        library(rjson) 

                        #Read JSON data into R  

                        data <- fromJSON(file="http://localhost:10010/v3/record?limit=1&sort=&embed=true&db_prefix=&ocid=ocds-0ud2q6-1336")

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                        import json, urllib 


                        #Read JSON data into python  

                        response = urllib2.urlopen('http://localhost:10010/v3/record?limit=1&sort=&embed=true&db_prefix=&ocid=ocds-0ud2q6-1336')   

                        data = json.loads(response.read())

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                        import pandas as pd 


                        #Read JSON data into pandas  

                        df = pd.read_json('http://localhost:10010/v3/record?limit=1&sort=&embed=true&db_prefix=&ocid=ocds-0ud2q6-1336')