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Description
PARA IMPRESION MARCA IBM LEXMARK, MODELO 4076, PARTE 13620 HC, NEGRO, DESCRIPCION CANCELADA
Classification
Material médico. Material de uso en equipos de computo
IMSS product code
372.197.0014.00
Each circle represents one of the 4 purchases of CARTUCHO DE TINTA made by the IMSS between 2009 and 2012.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Chihuahua Almacen Delegacional En Chihuahua | Chihuahua | 1 | 8,062.6 MXN | 671.7 MXN | 9.09 % | 1.73 | 1 de enero de 2009 |
| Delegación Michoacán | Michoacán | 1 | 999 MXN | 188.1 MXN | 23.2 % | 0.269 | 6 de mayo de 2012 |
| Delegación Oaxaca Almacen Delegacional En Oaxaca | Oaxaca | 1 | 2,244.6 MXN | 147.4 MXN | 7.03 % | 0.211 | 17 de abril de 2012 |
| Delegación Sonora Almacen Delegacional En Sonora | Sonora | 1 | 9,384 MXN | 1,604 MXN | 20.6 % | 4.12 | 20 de marzo de 2009 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| JLB-PRODUCTS SOFT & HARDWARE S DE RL DE MICROINDUS | 1 | 671.7 MXN | 9.09 % | 1.73 | 2009 - 2009 |
| MEJIA GOMEZ MARCO ANTONIO | 1 | 147.4 MXN | 7.03 % | 0.211 | 2012 - 2012 |
| NUEVA WAL MART DE MEXICO, S. DE R.L. DE C.V. | 1 | 188.1 MXN | 23.2 % | 0.269 | 2012 - 2012 |
| PROVINMED, S.A. DE C.V. | 1 | 1,604 MXN | 20.6 % | 4.12 | 2009 - 2009 |
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=372.197.0014.00")
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=372.197.0014.00')
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=372.197.0014.00')