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Description
TALLA: ESPECIAL, TELA: POPELINA FALLA: 80% POLIESTER -20% ALGODON. (LAS PRENDAS DE COLOR), POPELINA FALLA: 70% POLIESTER - 30% ALGODON. (SACO Y PANTALONES BLANCOS), COLOR: ROSA 13-2010 TP O
Classification
Ropa y Telas. Ropa contractual
IMSS product code
210.125.3397.02
Each circle represents one of the 4 purchases of SACO DE MANGA CORTA Y PANTALON FEMENINO made by the IMSS between 2009 and 2009.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Norte del DF Almacen Delegacional En El D.f. Zona Norte | Ciudad de México | 2 | 964.9 MXN | 125.9 MXN | 15 % | 0.9 | 1 de enero de 2009 |
| Delegación Sur del DF Almacen Delegacional En El D.f. Zona Sur | Ciudad de México | 2 | 482.4 MXN | 62.9 MXN | 15 % | 0.45 | 1 de enero de 2009 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| CORPORACION TETRA MEXICO, S.A. DE C.V. | 2 | 125.7 MXN | 15 % | 0.899 | 2009 - 2009 |
| IMAGINE TEXTILIS, S.A. DE C.V. | 2 | 63.1 MXN | 15 % | 0.451 | 2009 - 2009 |
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=210.125.3397.02")
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=210.125.3397.02')
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=210.125.3397.02')