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Description
SUEROS PARA TIPIFICAR LA SANGRE, MEDIOS PROTEICOS, ENZIMAS Y ANTIGENOS. ANTI M. FRASCO DE 2 Y 5 ML. RTC.
IMSS product code
080.081.0475.11
Each circle represents one of the 8 purchases of SUEROS PARA TIPIFICAR LA SANGRE MEDIOS PROTEICOS ENZIMAS Y ANTÍGENOS 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 | 5 | 493,802.5 MXN | 69,057.3 MXN | 16.3 % | 24.6 | 5 de abril de 2017 |
| Delegación Chihuahua | Chihuahua | 1 | 10,440 MXN | 2,194.6 MXN | 26.6 % | 0.617 | 17 de noviembre de 2016 |
| H. de Especialidades, "Lic. Ignacio García Tellez" Centro Médico Nacional de Occidente, Jalisco Umae Especialidades Jalisco | Jalisco | 1 | 2,143.7 MXN | - MXN | - | - | 4 de febrero de 2014 |
| H. de Pediatría, Centro Médico Nacional Siglo XXI Umae Pediatria C.m.n. Siglo Xxi | Ciudad de México | 1 | 5,324.4 MXN | 734.4 MXN | 16 % | 0.32 | 27 de marzo de 2018 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| PIZAYA MOLINA JAIME ARTURO | 4 | 65,903.7 MXN | 15.8 % | 23.3 | 2014 - 2017 |
| ABASTECEDORA INTEGRAL ESPECIALIZADA, SA DE CV | 1 | 734.4 MXN | 16 % | 0.32 | 2018 - 2018 |
| BIO LEBEN, S.A. DE C.V. | 1 | 3,153.6 MXN | 18.4 % | 1.29 | 2017 - 2017 |
| MARCAS ESPECIALIZADAS EN DIAGNOSTICO Y REPRESENTAC | 1 | - MXN | - | - | 2014 - 2014 |
| RUIZ ORTEGA MIGUEL ANDRES | 1 | 2,194.6 MXN | 26.6 % | 0.617 | 2016 - 2016 |
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=080.081.0475.11")
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=080.081.0475.11')
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=080.081.0475.11')