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Description
SUEROS PARA TIPIFICAR LA SANGRE, MEDIOS PROTEICOS, ENZIMAS Y ANTIGENOS. ANTI- rh' (ANTI-E) ANTICUERPOS PARA TIPIFICAR SANGRE. FRASCO DE 2 Y 5 ML. RTC.
IMSS product code
080.081.0467.11
Each circle represents one of the 6 purchases of SUSTANCIAS BIOLÓGICAS made by the IMSS between 2015 and 2018.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Chihuahua Almacen Delegacional En Chihuahua | Chihuahua | 3 | 543,286 MXN | 62,808.9 MXN | 14.5 % | 20.6 | 9 de marzo de 2017 |
| Delegación Jalisco Almacen Delegacional En Jalisco | Jalisco | 1 | 62,571.2 MXN | 21,852.7 MXN | 53.7 % | 5.37 | 17 de octubre de 2018 |
| H. de Especialidades No. 1, "Lic. Ignacio García Tellez" Mérida, Yucatán. Umae Especialidades Yucatan | Yucatán | 1 | 55,680 MXN | 19,807.1 MXN | 55.2 % | 6.63 | 3 de junio de 2015 |
| H. de Pediatría, Centro Médico Nacional Siglo XXI Umae Pediatria C.m.n. Siglo Xxi | Ciudad de México | 1 | 41,342.4 MXN | - MXN | - | - | 27 de marzo de 2018 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| PIZAYA MOLINA JAIME ARTURO | 3 | 62,808.9 MXN | 14.5 % | 20.6 | 2015 - 2017 |
| ABASTECEDORA INTEGRAL ESPECIALIZADA, SA DE CV | 1 | - MXN | - | - | 2018 - 2018 |
| DIAGNOSTICO Y PREVENCION DEL SUR S.A. DE C.V. | 1 | 21,852.7 MXN | 53.7 % | 5.37 | 2018 - 2018 |
| VALBREN DE MEXICO, S.A. DE C.V. | 1 | 19,807.1 MXN | 55.2 % | 6.63 | 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=080.081.0467.11")
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=080.081.0467.11')
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=080.081.0467.11')