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Description
Para drenaje ventricular y monitoreo de líquido cefalorraquídeo incluye: Un catéter ventricular de elastómero de silicón radiopaco de 20 a 35 cm de longitud un estilete de acero inoxidable para la colocación del catéter un trocar curvo de acero inoxidable con punta aguda para el paso del catéter subcutáneamente válvula de conexión con catéter distal tabla integrada de presión intracraneal en mm de Hg y cm de agua cámara de goteo de 50 a 75 cm con válvula antirreflujo y tapa para conservar la esterilidad tubo de plástico de 150 a 170 cm de longitud con dos pinzas para ajuste dos Llaves. de paso dos sitios para inyección una bolsa de recolección de vinil con capacidad para 700 ml con marcas cada 50 ml y asa para colgar ajustable a la altura deseada. Estéril y desechable
Classification
Material médico. Material de curacion
IMSS product code
060.345.2483.00
Presentation
Equipo
Each circle represents one of the 2 purchases of EQUIPOS made by the IMSS between 2009 and 2009.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Tabasco | Tabasco | 2 | 23,575 MXN | 766.7 MXN | 4.88 % | 0.112 | 13 de mayo de 2009 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| FERNANDEZ DE LARA CASTILLO JUAN MANUEL | 2 | 766.7 MXN | 4.88 % | 0.112 | 2009 - 2009 |
Entity type
Material de curacion
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=060.345.2483.00")
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=060.345.2483.00')
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=060.345.2483.00')