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Description
Compra Emergente
IMSS product code
060.841.0312.02
Each circle represents one of the 5 purchases of SUTURAS made by the IMSS between 2010 and 2014.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Nuevo León | Nuevo León | 3 | 6,728 MXN | 0.000000000000909 MXN | 0.0000000000000135 % | 0.000000000000000627 | 8 de octubre de 2010 |
| Delegación Sonora Almacen Delegacional En Sonora | Sonora | 1 | 5,104 MXN | 704 MXN | 16 % | 2.56 | 2 de julio de 2014 |
| H. de Especialidades Núm 25, Monterrey, N.L. Umae Especialidades Nuevo Leon | Nuevo León | 1 | 4,657.4 MXN | 642.4 MXN | 16 % | 0.32 | 25 de junio de 2012 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| DURFA, S. A. DE C. V. | 4 | 642.4 MXN | 4 % | 0.32 | 2010 - 2012 |
| MEDICAMENTOS INSTITUCIONALES MEXICANOS, SA DE CV | 1 | 704 MXN | 16 % | 2.56 | 2014 - 2014 |
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=060.841.0312.02")
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=060.841.0312.02')
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=060.841.0312.02')