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Description
ANTISEPTICOS Y GERMICIDAS. SOLUCION QUE CONTIENE YODOFORO (0.7 % DE YODO LIBRE), ALCOHOL ISOPROPILICO AL 74 % Y UN POLIMERO QUE FORMA SOBRE LA PIEL UNA PELICULA. CONTIENE: DOS HISOPOS, UN APLICADOR DE PLASTICO Y UNA AMPOLLETA CON
IMSS product code
060.066.0922.02
Each circle represents one of the 15 purchases of ANTISÉPTICOS made by the IMSS between 2009 and 2013.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Baja California | Baja California | 3 | 5,884.3 MXN | 2,303.3 MXN | 77.7 % | 15 | 16 de noviembre de 2010 |
| H. de Especialidades Cardiológicas No. 34, Centro Médico Nacional del Noreste. Umae Cardiologia En Nuevo Leon | Nuevo León | 3 | 109,051.7 MXN | 14,818.2 MXN | 15.6 % | 134.8 | 20 de enero de 2011 |
| H. Traumatología "Dr. Victorio De La Fuente Narváez" Umae Trauma Y Orto M.s. "dr. Victorio De La Fuente Narvaez" (d.f. Nort | Ciudad de México | 2 | 54,296.4 MXN | 5,972.4 MXN | 8 % | 48.3 | 30 de diciembre de 2013 |
| Delegación Baja California Almacen Delegacional En Baja California Norte | Baja California | 1 | 103,787.5 MXN | 15,929.1 MXN | 18.1 % | 172.2 | 1 de enero de 2009 |
| Delegación Chihuahua Almacen Delegacional En Chihuahua | Chihuahua | 1 | 1.8 millones MXN | 239,590.6 MXN | 14.9 % | 2,590.7 | 1 de enero de 2009 |
| Delegación Norte del DF Almacen Delegacional En El D.f. Zona Norte | Ciudad de México | 1 | 7,980.8 MXN | 1,835.8 MXN | 29.9 % | 11.9 | 10 de diciembre de 2010 |
| H. de Especialidades No. 1, "Lic. Ignacio García Tellez" Mérida, Yucatán. Umae Especialidades Yucatan | Yucatán | 1 | 272,084.5 MXN | 35,329.3 MXN | 14.9 % | 382 | 1 de enero de 2009 |
| H. de Especialidades No. 14 "Adolfo Ruíz Cortines", Veracruz. Umae Especialidades Veracruz (nte.) | Veracruz | 1 | 384,531.9 MXN | 49,930.2 MXN | 14.9 % | 539.9 | 1 de enero de 2009 |
| H. de Gineco Obstetricia Núm. 23, "Ignacio Morones Prieto" Monterrey, N.L. Umae Gineco - Obstetricia Nuevo Leon | Nuevo León | 1 | 1.3 millones MXN | 171,982 MXN | 14.9 % | 1,859.6 | 1 de enero de 2009 |
| H. de Oncología, Centro Médico Nacional Siglo XXI Umae Oncologia C.m.n. Siglo Xxi | Ciudad de México | 1 | 213,628.8 MXN | 27,739 MXN | 14.9 % | 299.9 | 1 de enero de 2009 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| SELECCIONES MEDICAS DEL CENTRO. S. A. DE C. V. | 5 | 524,571.2 MXN | 14.9 % | 5,672.1 | 2009 - 2009 |
| SELECCIONES MEDICAS, S. A. DE C. V. | 4 | 30,747.3 MXN | 16.3 % | 307 | 2009 - 2011 |
| INSTRUMENTACION Y EQUIPOS MEDICOS, S. DE R.L. DE C | 3 | 2,303.3 MXN | 77.7 % | 15 | 2010 - 2010 |
| JTC PROVEEDOR MEDICO, S. A. DE C. V. | 2 | 5,972.4 MXN | 8 % | 48.3 | 2010 - 2013 |
| DE LA MADRID HERNANDEZ CARMEN | 1 | 1,835.8 MXN | 29.9 % | 11.9 | 2010 - 2010 |
Date updated in QQW
3 de octubre de 2022
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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=060.066.0922.02")
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=060.066.0922.02')
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=060.066.0922.02')