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Description
DE TAMAÑO 14" X 17" PARA IMPRESORA LASER EN SECO MARCA: KONICA MINOLTA MODELO DRYPRO 832 NÚMERO DE CATÁLOGO: 0163014, PARA SU USO EN EL EQUIPO MEDICO: CLAVE 531 341 0499 01 01
Classification
Material médico. Consumibles de equipos medicos y de laboratorio
IMSS product code
379.687.1378.00
Presentation
CAJA CON 125 PELICULAS.
Each circle represents one of the 38 purchases of PELICULA made by the IMSS between 2012 and 2018.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Sonora Almacen Delegacional En Sonora | Sonora | 14 | 5 millones MXN | 766,508.7 MXN | 50.6 % | 115.7 | 22 de noviembre de 2016 |
| Delegación Michoacán Almacen Delegacional En Michoacan | Michoacán | 8 | 4.5 millones MXN | 591,262.3 MXN | 17.7 % | 88.9 | 12 de julio de 2017 |
| Delegación Yucatán Almacen Delegacional En Yucatan | Yucatán | 8 | 7.3 millones MXN | 876,378.6 MXN | 14.8 % | 133.9 | 9 de agosto de 2017 |
| H. de Especialidades No. 1, "Lic. Ignacio García Tellez" Mérida, Yucatán. Umae Especialidades Yucatan | Yucatán | 3 | 791,700 MXN | 102,420.4 MXN | 13.3 % | 15.7 | 24 de febrero de 2014 |
| Delegación Sinaloa Almacen Delegacional En Sinaloa | Sinaloa | 2 | 1 millones MXN | 140,112 MXN | 16 % | 22.2 | 5 de noviembre de 2018 |
| Delegación Chihuahua Almacen Delegacional En Chihuahua | Chihuahua | 1 | 480,820 MXN | 136,653.3 MXN | 39.7 % | 19.9 | 13 de enero de 2012 |
| Delegación Guanajuato Almacen Delegacional En Guanajuato | Guanajuato | 1 | 156,600 MXN | 37,464.8 MXN | 31.4 % | 5.66 | 7 de julio de 2015 |
| H. de Especialidades No. 14 "Adolfo Ruíz Cortines", Veracruz. Umae Especialidades Veracruz (nte.) | Veracruz | 1 | 33,070.4 MXN | 7,365.3 MXN | 28.7 % | 1.15 | 27 de febrero de 2014 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| COMERCIALIZADORA SOLUCE SA DE CV | 12 | 817,431.6 MXN | 17.7 % | 125.9 | 2014 - 2018 |
| MARA IRASEMA CASTRO ACU?A | 7 | 228,334.3 MXN | 80.2 % | 33.9 | 2012 - 2013 |
| INDUSTRIA ELECTRONICA MEDICA, S.A. DE C.V. | 5 | 580,247.4 MXN | 14.1 % | 88.4 | 2012 - 2014 |
| ELECTRONICA Y MEDICINA, S. A. | 4 | 235,130.8 MXN | 9.4 % | 34.1 | 2012 - 2017 |
| ABASTECEDORA DE CONSUMIBLES MEDICOS, S.A. DE C.V. | 3 | 222,531.5 MXN | 17.4 % | 34.7 | 2014 - 2016 |
| CSE ELECTROMEDICOS, S.A. DE C.V. | 3 | 380,291.8 MXN | 14.1 % | 57.5 | 2013 - 2015 |
| CONTROL SCIENTIFIC, S.A. DE C.V. | 1 | 136,653.3 MXN | 39.7 % | 19.9 | 2012 - 2012 |
| CORRAL BELTRAN VICTOR | 1 | 12,714.7 MXN | 63.6 % | 1.91 | 2013 - 2013 |
| EMD S.A.P.I.DE C.V. | 1 | 37,464.8 MXN | 31.4 % | 5.66 | 2015 - 2015 |
| ESTRATEGIA HOSPITALARIA S.A. DE C.V. | 1 | 7,365.3 MXN | 28.7 % | 1.15 | 2014 - 2014 |
Entity type
Consumibles de equipos medicos y de laboratorio
Date updated in QQW
3 de octubre de 2022
Source(s)
Part of the project
Organization responsible for the import
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Add this to your code:
library(rjson)
#Read JSON data into R
data <- fromJSON(file="http://localhost:10010/v3/products?limit=1&sort=&embed=true&db_prefix=&id=379.687.1378.00")
Add this to your code:
import json, urllib
#Read JSON data into python
response = urllib2.urlopen('http://localhost:10010/v3/products?limit=1&sort=&embed=true&db_prefix=&id=379.687.1378.00')
data = json.loads(response.read())
Add this to your code:
import pandas as pd
#Read JSON data into pandas
df = pd.read_json('http://localhost:10010/v3/products?limit=1&sort=&embed=true&db_prefix=&id=379.687.1378.00')