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Description
NITROFURANTOINA DISCOS CON-300 MCG EN FRASCO O TUBORTC.
IMSS product code
080.316.0100.10
Each circle represents one of the 2 purchases of DISCOS CON ANTIMICROBIANOS made by the IMSS between 2010 and 2011.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Sinaloa Almacen Delegacional En Sinaloa | Sinaloa | 1 | 1,276 MXN | 176 MXN | 16 % | 3.2 | 25 de junio de 2010 |
| H. de Especialidades No. 1, "Lic. Ignacio García Tellez" Mérida, Yucatán. Umae Especialidades Yucatan | Yucatán | 1 | 638.9 MXN | 88.1 MXN | 16 % | 1.92 | 1 de enero de 2011 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| ABASTECEDOR HOSPITALARIO DEL SURESTE, S.A. DE C.V. | 1 | 88.1 MXN | 16 % | 1.92 | 2011 - 2011 |
| BIOLOGISTICA INTEGRAL, S.A. DE C.V. | 1 | 176 MXN | 16 % | 3.2 | 2010 - 2010 |
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=080.316.0100.10")
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=080.316.0100.10')
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=080.316.0100.10')