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Description
HIDROQUINONA RA POLVO TA.
IMSS product code
080.830.1477.10
Each circle represents one of the 4 purchases of REACTIVOS QUÍMICOS made by the IMSS between 2009 and 2010.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| H. de Especialidades, "Dr. Antonio Fraga Mouret" Centro Médico Nacional La Raza Umae Especialidades C.m.n. La Raza | Ciudad de México | 2 | 439.8 MXN | 78.9 MXN | 18.6 % | 0.372 | 1 de enero de 2010 |
| Delegación Sur del DF Almacen Delegacional En El D.f. Zona Sur | Ciudad de México | 1 | 197.3 MXN | 46.7 MXN | 31 % | 0.31 | 16 de febrero de 2009 |
| H. de Especialidades, "Gral. Div. Manuel Avila Camacho", Centro Médico Nacional, Puebla Umae Especialidades Puebla | Puebla | 1 | 200.8 MXN | - MXN | - | - | 30 de marzo de 2010 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| EIBL LABORATORIES, S.A. DE C.V. | 4 | 125.6 MXN | 17.1 % | 0.683 | 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=080.830.1477.10")
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=080.830.1477.10')
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=080.830.1477.10')