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Description
INJERTOS TUBULARES, RECTOS, DE PARED REGULAR. 10 MM X 80 CM.
IMSS product code
060.506.1878.11
Each circle represents one of the 2 purchases of INJERTOS made by the IMSS between 2009 and 2011.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Sinaloa Almacen Delegacional En Sinaloa | Sinaloa | 1 | 7,800.2 MXN | 1,075.9 MXN | 16 % | 0.16 | 26 de octubre de 2011 |
| H. de Especialidades No. 1 Centro Médico Nacional del Bajio, León, Gto. Umae Especialidades Guanajuato | Guanajuato | 1 | 32,963.8 MXN | 4,299.6 MXN | 15 % | 1.65 | 1 de enero de 2009 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| COMETA MERCANTIL, S.A. DE C.V. | 1 | 1,075.9 MXN | 16 % | 0.16 | 2011 - 2011 |
| MEDIGROUP DEL PACIFICO, S.A. DE C.V. | 1 | 4,299.6 MXN | 15 % | 1.65 | 2009 - 2009 |
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=060.506.1878.11")
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=060.506.1878.11')
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=060.506.1878.11')