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Description
SUERO PARA TIPIFICAR LA SANGRE ANTI-RH" (ANTI-E) FRASCODE 2 ML., RTC.
IMSS product code
080.081.0467.01
Each circle represents one of the 21 purchases of SUSTANCIAS BIOLÓGICAS made by the IMSS between 2009 and 2013.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Chihuahua Almacen Delegacional En Chihuahua | Chihuahua | 7 | 518,791 MXN | 89,494.6 MXN | 27.4 % | 54.9 | 11 de enero de 2013 |
| H. de Pediatría, Centro Médico Nacional Siglo XXI Umae Pediatria C.m.n. Siglo Xxi | Ciudad de México | 4 | 63,246.6 MXN | 10,246.1 MXN | 47.3 % | 6.11 | 13 de junio de 2013 |
| Delegación Campeche Almacen Delegacional En Campeche | Campeche | 3 | 60,691.2 MXN | 7,666.1 MXN | 20.6 % | 7.52 | 1 de enero de 2011 |
| Delegación Aguascalientes Almacen Delegacional En Aguascalientes | Aguascalientes | 2 | 4,496.2 MXN | 535 MXN | 13.4 % | 0.537 | 1 de enero de 2011 |
| H. de Especialidades No. 1, "Lic. Ignacio García Tellez" Mérida, Yucatán. Umae Especialidades Yucatan | Yucatán | 2 | 6,113.2 MXN | 1,752.3 MXN | 40.2 % | 0.804 | 21 de mayo de 2013 |
| Delegación Chihuahua | Chihuahua | 1 | 3,519 MXN | 828 MXN | 30.8 % | 1.06 | 8 de septiembre de 2009 |
| Delegación Sinaloa Almacen Delegacional En Sinaloa | Sinaloa | 1 | 1,450 MXN | - MXN | - | - | 12 de julio de 2013 |
| H. de Especialidades No. 14 "Adolfo Ruíz Cortines", Veracruz. Umae Especialidades Veracruz (nte.) | Veracruz | 1 | 1,183.2 MXN | 223.5 MXN | 23.3 % | 0.233 | 4 de marzo de 2011 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| ABASTECEDOR HOSPITALARIO DEL SURESTE, S.A. DE C.V. | 3 | 1,975.8 MXN | 34.6 % | 1.04 | 2011 - 2013 |
| QUIMICA TECH, S. A. DE C. V. | 3 | 3,169.6 MXN | 27.4 % | 3.82 | 2009 - 2010 |
| CORPORATIVO LAYN PLUS, S. A. DE C. V. | 2 | 20,954.5 MXN | 23.3 % | 20.8 | 2009 - 2010 |
| HIPODERMICOS ARMA, S.A. DE C.V. | 2 | 1,839.8 MXN | 35.6 % | 1.8 | 2010 - 2010 |
| QUIMICA DE AGUASCALIENTES, S.A. DE C.V. | 2 | 535 MXN | 13.4 % | 0.537 | 2010 - 2011 |
| ABALAT, S.A. DE C.V. | 1 | 7,969 MXN | 36.5 % | 3.65 | 2013 - 2013 |
| CARDENAS PAYAN LIZETH ANAHI | 1 | - MXN | - | - | 2013 - 2013 |
| COMERCIALIZADORA LUIV, S. A. DE C. V. | 1 | 1,400.9 MXN | 146 % | 1.46 | 2011 - 2011 |
| CONTROL TECNICO Y REPRESENTACIONES, S. A. DE C. V. | 1 | 324 MXN | 1.73 % | 0.415 | 2009 - 2009 |
| IMPULSORA MEDICA QUIM. E INDUST. DE CAMPECHE,S.A. | 1 | 765.3 MXN | 25 % | 0.75 | 2010 - 2010 |
| LABSSA, S.A. DE C.V. | 1 | 223.5 MXN | 23.3 % | 0.233 | 2011 - 2011 |
| PIZAYA MOLINA JAIME ARTURO | 1 | 64,358.8 MXN | 22.4 % | 29.5 | 2013 - 2013 |
| QUIMICA INDUSTRIAL Y DE SALUD, SA DE CV | 1 | 552.2 MXN | 4.79 % | 0.575 | 2011 - 2011 |
| SAINZ DE LA ROSA NATIVIDAD | 1 | 6,677.3 MXN | 13.6 % | 6.54 | 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=080.081.0467.01")
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=080.081.0467.01')
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=080.081.0467.01')