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Description
ANTI RH (D) ALBUMINOSO RTC.
IMSS product code
080.835.0110.10
Each circle represents one of the 4 purchases of SUSTANCIAS BIOLÓGICAS made by the IMSS between 2009 and 2015.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Chihuahua Almacen Delegacional En Chihuahua | Chihuahua | 1 | 199,492.2 MXN | 24,035.6 MXN | 13.7 % | 318.4 | 1 de enero de 2011 |
| H. de Especialidades No. 1, "Lic. Ignacio García Tellez" Mérida, Yucatán. Umae Especialidades Yucatan | Yucatán | 1 | 25,056 MXN | 6,936.6 MXN | 38.3 % | 91.9 | 1 de enero de 2011 |
| H. de Especialidades No. 14 "Adolfo Ruíz Cortines", Veracruz. Umae Especialidades Veracruz (nte.) | Veracruz | 1 | 25,752 MXN | 3,552 MXN | 16 % | 19.2 | 12 de noviembre de 2015 |
| H. de Pediatría, "Lic. Ignacio García Tellez" Centro Médico Nacional de Occidente, Jalisco. Umae Pediatria Jalisco | Jalisco | 1 | 65,412 MXN | 8,532 MXN | 15 % | 108 | 1 de enero de 2009 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| LABORATORIOS LAFON, S. A. DE C. V. | 1 | 24,035.6 MXN | 13.7 % | 318.4 | 2011 - 2011 |
| PROFESSIONAL PHARMACY, S.A. DE C.V. | 1 | 6,936.6 MXN | 38.3 % | 91.9 | 2011 - 2011 |
| TESSAN GARCIA OMAR FARID | 1 | 8,532 MXN | 15 % | 108 | 2009 - 2009 |
| VALENCIA DURAN MARIA ESTER | 1 | 3,552 MXN | 16 % | 19.2 | 2015 - 2015 |
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=080.835.0110.10")
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=080.835.0110.10')
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=080.835.0110.10')