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Description
Cincel gubia Partsh juego de cuatro piezas de 3 4 5 y 6 mm ancho de hoja longitud de 170 mm
Classification
Material médico. Instrumental de cirugia de especialidades
IMSS product code
537.191.2402.00
Presentation
Pieza
Each circle represents one of the 5 purchases of CINCEL made by the IMSS between 2010 and 2018.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Aguascalientes Almacen Delegacional En Aguascalientes | Aguascalientes | 2 | 8,905.4 MXN | 1,228.3 MXN | 16 % | 0.48 | 8 de agosto de 2018 |
| Delegación Tamaulipas Almacen Delegacional En Tamaulipas | Tamaulipas | 1 | 2,088 MXN | 288 MXN | 16 % | 0.16 | 26 de abril de 2012 |
| Delegación Veracruz Norte Almacen Delegacional En Veracruz Norte | Veracruz | 1 | 2,088 MXN | 288 MXN | 16 % | 0.16 | 17 de febrero de 2012 |
| H. de Especialidades No. 14 "Adolfo Ruíz Cortines", Veracruz. Umae Especialidades Veracruz (nte.) | Veracruz | 1 | 3,120.4 MXN | 430.4 MXN | 16 % | 0.32 | 4 de agosto de 2010 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| QUIRURGICA ORTOPEDICA, S. A. DE C. V. | 3 | 976 MXN | 16 % | 0.48 | 2012 - 2018 |
| DEWIMED, S. A. | 1 | 828.3 MXN | 16 % | 0.32 | 2011 - 2011 |
| HIDRO HOSPITAL, S.A. DE C.V. | 1 | 430.4 MXN | 16 % | 0.32 | 2010 - 2010 |
Entity type
Instrumental de cirugia de especialidades
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=537.191.2402.00")
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=537.191.2402.00')
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=537.191.2402.00')