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Description
MARCA LEXMARK, MODELO Z12, NO DE PARTE 17G0050
Classification
Material médico. Material de uso en equipos de computo
IMSS product code
372.197.2135.00
Each circle represents one of the 6 purchases of CARTUCHO PARA IMPRESORA made by the IMSS between 2009 and 2011.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Querétaro Almacen Delegacional En Queretaro | Querétaro | 4 | 11,098.4 MXN | 1,819.6 MXN | 30.3 % | 4.45 | 8 de febrero de 2011 |
| Delegación Baja California Sur Almacen Delegacional En Baja California Sur | Baja California Sur | 1 | 420.1 MXN | 58.9 MXN | 16.3 % | 0.163 | 13 de abril de 2009 |
| Delegación Yucatán Almacen Delegacional En Yucatan | Yucatán | 1 | 12,109.5 MXN | 1,274.7 MXN | 11.8 % | 3.53 | 29 de enero de 2009 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| NETSHELL SA. DE CV. | 2 | 508.3 MXN | 44.6 % | 1.41 | 2009 - 2009 |
| COMERCIALIZADORA DE SOLUCIONES TECNOLOGICAS S.A. D | 1 | 399.3 MXN | 16 % | 1.12 | 2010 - 2010 |
| PROVEEDORA DE PAPELES Y CONSUMIBLES, S. DE R. L. | 1 | 58.9 MXN | 16.3 % | 0.163 | 2009 - 2009 |
| SOLUCIONES Y SUMINISTROS JELINOVA S. A. DE C. V. | 1 | 1,274.7 MXN | 11.8 % | 3.53 | 2009 - 2009 |
| TCA EMPRESARIAL, S.A. DE C.V. | 1 | 912 MXN | 16 % | 1.92 | 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=372.197.2135.00")
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=372.197.2135.00')
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=372.197.2135.00')