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Description
ALFA LACTO ALBUMINA (AC PRIMARIO) RTC.
IMSS product code
080.070.0213.10
Each circle represents one of the 5 purchases of SUSTANCIAS BIOLÓGICAS made by the IMSS between 2009 and 2018.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Sur del DF Almacen Delegacional En El D.f. Zona Sur | Ciudad de México | 3 | 143,167.2 MXN | 19,747.2 MXN | 16 % | 31.2 | 1 de enero de 2018 |
| H. de Especialidades, "Gral. Div. Manuel Avila Camacho", Centro Médico Nacional, Puebla Umae Especialidades Puebla | Puebla | 2 | 5,819.5 MXN | 783.3 MXN | 15.5 % | 0.31 | 19 de agosto de 2010 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| DISAMED, S.A. DE C.V. | 3 | 19,747.2 MXN | 16 % | 31.2 | 2016 - 2018 |
| RAMIREZ ROMERO JESUS ARMANDO | 2 | 783.3 MXN | 15.5 % | 0.31 | 2009 - 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=080.070.0213.10")
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=080.070.0213.10')
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=080.070.0213.10')