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Description
LASER MARCA IBM, MODELO LEXMARK PARTE 1380950, NEGRO
Classification
Material médico. Material de uso en equipos de computo
IMSS product code
372.197.0493.00
Each circle represents one of the 2 purchases of CARTUCHO PARA IMPRESORA made by the IMSS between 2009 and 2014.
| 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 | 1 | 17,400 MXN | 2,400 MXN | 16 % | 0.64 | 20 de noviembre de 2014 |
| H. de Oncología, Centro Médico Nacional Siglo XXI Umae Oncologia C.m.n. Siglo Xxi | Ciudad de México | 1 | 1,981.7 MXN | 258.5 MXN | 15 % | 0.15 | 2 de junio de 2009 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| FRANCO RIVERA ARACELI ABIGAIL | 1 | 258.5 MXN | 15 % | 0.15 | 2009 - 2009 |
| RAMIREZ COLIN MARTIN EDUARDO | 1 | 2,400 MXN | 16 % | 0.64 | 2014 - 2014 |
Entity type
Material de uso en equipos de computo
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=372.197.0493.00")
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=372.197.0493.00')
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=372.197.0493.00')