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Description
PARA ENCUADERNAR DE (1 1/2") DE DIAMETRO COLOR TRANSPARENTE CRISTAL)
Classification
Artículos de consumo. Utiles de oficina
IMSS product code
312.092.0842.00
Each circle represents one of the 2 purchases of ARILLO DE PLASTICO made by the IMSS between 2010 and 2015.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Sinaloa Almacen Delegacional En Sinaloa | Sinaloa | 1 | 176.4 MXN | 24.3 MXN | 16 % | 1.44 | 30 de noviembre de 2010 |
| Oficinas Centrales Ofnas Centrales -reforma- Coordinacion De Abastecimiento | 1 | 1,632.1 MXN | 225.1 MXN | 16 % | 48 | 23 de septiembre de 2015 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| SIGA BIENES Y SERVICIOS, S.A. DE C.V. | 1 | 225.1 MXN | 16 % | 48 | 2015 - 2015 |
| SOTELO CAMACHO FIDEL | 1 | 24.3 MXN | 16 % | 1.44 | 2010 - 2010 |
Entity type
Utiles de oficina
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=312.092.0842.00")
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=312.092.0842.00')
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=312.092.0842.00')