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Description
CINCEL GUBIA RECTO DE 15 MM. ANCHO DE HOJA, CON MANGO SINTETICO.
IMSS product code
537.191.2394.01
Each circle represents one of the 8 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 Quintana Roo Almacen Delegacional En Quintana Roo | Quintana Roo | 2 | 17,787.6 MXN | 8,052 MXN | 85.2 % | 3.73 | 9 de mayo de 2018 |
| Delegación Aguascalientes Almacen Delegacional En Aguascalientes | Aguascalientes | 1 | 18,270 MXN | - MXN | - | - | 8 de agosto de 2018 |
| Delegación Estado de México Poniente Almacen Delegacional En El Estado De Mexico Poniente | Estado de México | 1 | 2,923.2 MXN | 403.2 MXN | 16 % | 0.32 | 6 de junio de 2014 |
| Delegación Guanajuato Almacen Delegacional En Guanajuato | Guanajuato | 1 | 7,917 MXN | 873.6 MXN | 12.4 % | 0.372 | 17 de agosto de 2018 |
| Delegación Tamaulipas Almacen Delegacional En Tamaulipas | Tamaulipas | 1 | 1,461.6 MXN | 201.6 MXN | 16 % | 0.16 | 26 de abril de 2012 |
| Delegación Veracruz Norte Almacen Delegacional En Veracruz Norte | Veracruz | 1 | 1,461.6 MXN | 201.6 MXN | 16 % | 0.16 | 17 de febrero de 2012 |
| Delegación Zacatecas Almacen Delegacional En Zacatecas | Zacatecas | 1 | 2,923.2 MXN | 403.2 MXN | 16 % | 0.32 | 21 de septiembre de 2010 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| QUIRURGICA ORTOPEDICA, S. A. DE C. V. | 7 | 2,889.6 MXN | 13.2 % | 1.97 | 2010 - 2018 |
| GENESIS HEALTHCARE ADVISERS, S. A. DE C. V. | 1 | 7,245.6 MXN | 154.3 % | 3.09 | 2018 - 2018 |
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=537.191.2394.01")
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=537.191.2394.01')
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=537.191.2394.01')