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Description
MARCA LEXMARK MODELO OPTRA 40, PARTE 12A1985, DE COLOR
Classification
Material médico. Material de uso en equipos de computo
IMSS product code
372.197.0477.00
Each circle represents one of the 4 purchases of CARTUCHO PARA IMPRESORA made by the IMSS between 2009 and 2015.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| H. de Oncología, Centro Médico Nacional Siglo XXI Umae Oncologia C.m.n. Siglo Xxi | Ciudad de México | 4 | 14,979.7 MXN | 2,052.3 MXN | 15.8 % | 2.53 | 1 de enero de 2015 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| COMERCIALIZADORA TONYCOM,S.A DE C.V | 2 | 1,747.8 MXN | 16 % | 1.92 | 2012 - 2015 |
| FRANCO RIVERA ARACELI ABIGAIL | 1 | 240.5 MXN | 15 % | 0.45 | 2009 - 2009 |
| SOLUCIONES Y SUMINISTROS JELINOVA S. A. DE C. V. | 1 | 64 MXN | 16 % | 0.16 | 2011 - 2011 |
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=372.197.0477.00")
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=372.197.0477.00')
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=372.197.0477.00')