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Description
CATETERES FEMORAL VISCERAL DE 0,038", CON UN ORIFICIO, ESTERIL TIPO: COBRA A I. LONGITUD 65 CM. CALIBRE 7 FR.
IMSS product code
060.167.6877.11
Each circle represents one of the 43 purchases of CATÉTERES made by the IMSS between 2009 and 2017.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| H. de Especialidades Núm 25, Monterrey, N.L. Umae Especialidades Nuevo Leon | Nuevo León | 39 | 1.8 millones MXN | 627,053.1 MXN | 92.9 % | 447.5 | 23 de marzo de 2017 |
| H. de Especialidades, "Dr. Bernardo Sepulveda Gutiérrez" Centro Médico Nacional Siglo XXI Umae Especialidades C.m.n. Siglo Xxi | Ciudad de México | 2 | 16,066 MXN | 7,943.7 MXN | 496.6 % | 10.8 | 1 de junio de 2016 |
| Delegación San Luis Potosí Almacen Delegacional En San Luis Potosi | San Luis Potosi | 1 | 14,927 MXN | 1,947 MXN | 15 % | 3.3 | 3 de abril de 2009 |
| H. de Gineco Pediatría Núm 48, León Gto. Umae Gineco - Pediatria Guanajuato | Guanajuato | 1 | 1,740 MXN | - MXN | - | - | 11 de abril de 2015 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| LEVBETH MEDICAL, S.A. DE C.V. | 40 | 560,645.8 MXN | 106.8 % | 437.7 | 2012 - 2017 |
| AVANT MEDICAL, S.A. DE C.V. | 1 | 74,351 MXN | 342.7 % | 20.6 | 2013 - 2013 |
| DURFA, S. A. DE C. V. | 1 | - MXN | - | - | 2013 - 2013 |
| GRUPO EMEQUR, S.A. DE C.V. | 1 | 1,947 MXN | 15 % | 3.3 | 2009 - 2009 |
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=060.167.6877.11")
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=060.167.6877.11')
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=060.167.6877.11')