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Description
DIMENSION: 8.5"X11" PLEGADO EN "Z", NÚMERO DE CATÁLOGO: 716-0237-00, PARA SU USO EN EL EQUIPO MEDICO: CLAVE 531 168 0069 ELECTROCARDIOGRAFO MULTICANAL CON INTERPRETACION, MARCA: BURDICK. ROLLO.
Classification
Material médico. Consumibles de equipos medicos y de laboratorio
IMSS product code
379.681.2315.00
Each circle represents one of the 5 purchases of PAPEL TERMICO made by the IMSS between 2015 and 2018.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Morelos Almacen Delegacional En Morelos | Morelos | 4 | 31,294.5 MXN | 8,365.3 MXN | 35.1 % | 23.6 | 17 de septiembre de 2018 |
| Delegación Estado de México Poniente Almacen Delegacional En El Estado De Mexico Poniente | Estado de México | 1 | 23,872.8 MXN | - MXN | - | - | 31 de enero de 2018 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| AKUASUL, S.A. DE C.V. | 1 | - MXN | - | - | 2018 - 2018 |
| ASESORIA Y APLICACIONES MEDICAS SA DE CV | 1 | 1,568 MXN | 16 % | 5.6 | 2017 - 2017 |
| AYALA RODRIGUEZ JUAN CARLOS | 1 | 923.5 MXN | 16 % | 3.2 | 2016 - 2016 |
| CORPORATIVO MS SISTEMAS MEDICOS, S.A. DE C.V. | 1 | 192 MXN | 16 % | 0.96 | 2015 - 2015 |
| INGENIERIA BIOMEDICA PARA LA SALUD, S.A. DE C.V. | 1 | 5,681.8 MXN | 92.3 % | 13.8 | 2018 - 2018 |
Entity type
Consumibles de equipos medicos y de laboratorio
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=379.681.2315.00")
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=379.681.2315.00')
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=379.681.2315.00')