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Description
Taylor longitud 17 cm
Classification
Material médico. Instrumental de cirugia general
IMSS product code
535.859.3357.00
Presentation
Pieza
Each circle represents one of the 16 purchases of TIJERA made by the IMSS between 2009 and 2018.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Guanajuato Almacen Delegacional En Guanajuato | Guanajuato | 2 | 6,145.7 MXN | 847.7 MXN | 16 % | 4.16 | 17 de agosto de 2018 |
| Delegación Hidalgo Almacen Delegacional En Hidalgo | Hidalgo | 2 | 14,801.6 MXN | 2,739 MXN | 26.8 % | 6.98 | 9 de noviembre de 2012 |
| Delegación Yucatán Almacen Delegacional En Yucatan | Yucatán | 2 | 7,767.4 MXN | 1,225.5 MXN | 23.2 % | 1.73 | 16 de mayo de 2016 |
| Delegación Zacatecas Almacen Delegacional En Zacatecas | Zacatecas | 2 | 2,871 MXN | 100.8 MXN | 8 % | 0.16 | 6 de julio de 2017 |
| Delegación Chiapas Almacen Subdelegacional En Tapachula, Chiapas | Chiapas | 1 | 1,015 MXN | 251.4 MXN | 32.9 % | 0.329 | 27 de julio de 2017 |
| Delegación Colima Almacen Delegacional En Colima | Colima | 1 | 1,955 MXN | 760 MXN | 63.6 % | 1.27 | 27 de agosto de 2009 |
| Delegación Durango Almacen Delegacional En Durango | Durango | 1 | 1,461.6 MXN | 201.6 MXN | 16 % | 0.32 | 20 de marzo de 2013 |
| Delegación Estado de México Poniente Almacen Delegacional En El Estado De Mexico Poniente | Estado de México | 1 | 2,772.4 MXN | - MXN | - | - | 6 de octubre de 2016 |
| Delegación Michoacán Almacen Delegacional En Michoacan | Michoacán | 1 | 3,045 MXN | 754.3 MXN | 32.9 % | 0.988 | 27 de junio de 2017 |
| Delegación Oaxaca Almacen Delegacional En Oaxaca | Oaxaca | 1 | 3,572.8 MXN | 1,073.2 MXN | 42.9 % | 1.72 | 3 de noviembre de 2016 |
| Delegación San Luis Potosí Almacen Delegacional En San Luis Potosi | San Luis Potosi | 1 | 793.5 MXN | - MXN | - | - | 17 de agosto de 2009 |
| H. de Especialidades, "Dr. Bernardo Sepulveda Gutiérrez" Centro Médico Nacional Siglo XXI Umae Especialidades C.m.n. Siglo Xxi | Ciudad de México | 1 | 5,232.1 MXN | 2,877.1 MXN | 122.2 % | 7.33 | 1 de noviembre de 2012 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| QUIRURGICA ORTOPEDICA, S. A. DE C. V. | 9 | 5,484.1 MXN | 23.4 % | 10.8 | 2012 - 2018 |
| NEODREN, S. DE R. L. DE C. V. | 2 | 378.8 MXN | 15.2 % | 0.606 | 2016 - 2016 |
| ABASTECEDOR HOSPITALARIO DEL SURESTE, S.A. DE C.V. | 1 | 846.7 MXN | 16 % | 1.12 | 2010 - 2010 |
| ABASTECEDORA DE INSUMOS PARA LA SALUD, S.A. DE C.V | 1 | 483.8 MXN | 16 % | 3.84 | 2015 - 2015 |
| GOVAL INTERNACIONAL, S.A. DE C.V. | 1 | 760 MXN | 63.6 % | 1.27 | 2009 - 2009 |
| HIDRO HOSPITAL, S.A. DE C.V. | 1 | - MXN | - | - | 2009 - 2009 |
| IMPORTADORA MEDICA MEXICANA, S. A. | 1 | 2,877.1 MXN | 122.2 % | 7.33 | 2012 - 2012 |
Entity type
Instrumental de cirugia general
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=535.859.3357.00")
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=535.859.3357.00')
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=535.859.3357.00')