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Description
TALLA: PLUS, TELA: POPELINA FALLA: 80% POLIESTER-20% ALGODON (BATA PINTOR Y TURBANTE), POPELINA FALLA: 70% POLIESTER-30% ALGODON (PANTALON Y MOÑO), COLORES CODIGO. PANTONE: AMARILLO PAJA
Classification
Ropa y Telas. Ropa contractual
IMSS product code
210.125.4817.00
Each circle represents one of the 7 purchases of BATA PINTOR Y PANTALON FEMENINO made by the IMSS between 2010 and 2013.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Oficinas Centrales Ofnas Centrales -reforma- Coordinacion De Abastecimiento | 3 | 3,003.5 MXN | 414.3 MXN | 16 % | 1.92 | 4 de enero de 2013 | |
| Oficinas Centrales Almacen De Programas Especiales Y Red Fria | 2 | 1,215.2 MXN | 167.6 MXN | 16 % | 0.96 | 16 de mayo de 2011 | |
| Delegación Coahuila Almacen Delegacional En Coahuila | Coahuila | 1 | 572.5 MXN | 79 MXN | 16 % | 0.48 | 21 de mayo de 2010 |
| Delegación Puebla Almacen Delegacional En Puebla | Puebla | 1 | 572.5 MXN | 79 MXN | 16 % | 0.48 | 2 de enero de 2010 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| RENOVADORA DE COLCHONES, S. A. DE C. V. | 5 | 629.1 MXN | 16 % | 3.36 | 2010 - 2012 |
| CONFECCIONES SAN MATEO, S. A. DE C. V. | 1 | 37.2 MXN | 16.1 % | 0.161 | 2013 - 2013 |
| UNIFORMES RECSA, S. A. DE C. V. | 1 | 73.5 MXN | 15.9 % | 0.319 | 2013 - 2013 |
Entity type
Ropa contractual
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=210.125.4817.00")
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=210.125.4817.00')
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=210.125.4817.00')