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Description
SUEROS PARA TIPIFICAR LA SANGRE, MEDIOS PROTEICOS, ENZIMAS Y ANTIGENOS. ANTI- rh' (ANTI-c). ANTICUERPOS PARA TIPIFICAR SANGRE. FRASCO DE 2 Y 5 ML. RTC.
IMSS product code
080.081.0202.11
Each circle represents one of the 7 purchases of SUSTANCIAS BIOLÓGICAS made by the IMSS between 2014 and 2018.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Chihuahua Almacen Delegacional En Chihuahua | Chihuahua | 4 | 720,157 MXN | 76,583.9 MXN | 11.7 % | 25.7 | 9 de marzo de 2017 |
| H. de Pediatría, Centro Médico Nacional Siglo XXI Umae Pediatria C.m.n. Siglo Xxi | Ciudad de México | 2 | 166,288.3 MXN | 34,261.4 MXN | 26.8 % | 12.9 | 27 de marzo de 2018 |
| H. de Especialidades No. 1, "Lic. Ignacio García Tellez" Mérida, Yucatán. Umae Especialidades Yucatan | Yucatán | 1 | 55,680 MXN | 19,103.1 MXN | 52.2 % | 6.27 | 3 de junio de 2015 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| PIZAYA MOLINA JAIME ARTURO | 3 | 70,283.9 MXN | 10.3 % | 23.3 | 2014 - 2016 |
| ABALAT, S.A. DE C.V. | 1 | 22,856.6 MXN | 37.6 % | 9.03 | 2014 - 2014 |
| ABASTECEDORA INTEGRAL ESPECIALIZADA, SA DE CV | 1 | 11,404.8 MXN | 16 % | 3.84 | 2018 - 2018 |
| BIO LEBEN, S.A. DE C.V. | 1 | 6,300 MXN | 16 % | 2.4 | 2017 - 2017 |
| VALBREN DE MEXICO, S.A. DE C.V. | 1 | 19,103.1 MXN | 52.2 % | 6.27 | 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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Choose the system where you want to use the data to see the instructions. For research methodology, see the Manual for investigating open contracting.
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=080.081.0202.11")
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=080.081.0202.11')
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=080.081.0202.11')