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Description
DE MELAMINA
Classification
Artículos de consumo. Articulos de cocina y comedor
IMSS product code
120.736.1567.00
Each circle represents one of the 10 purchases of PLATO made by the IMSS between 2009 and 2018.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Coahuila Almacen Delegacional En Coahuila | Coahuila | 5 | 5,256.4 MXN | 672.5 MXN | 15.2 % | 116.9 | 1 de enero de 2015 |
| Delegación Durango Almacen Delegacional En Durango | Durango | 4 | 30,462.4 MXN | 4,201.7 MXN | 16 % | 614.4 | 19 de julio de 2018 |
| Delegación Michoacán Almacen Delegacional En Michoacan | Michoacán | 1 | 340.2 MXN | 84 MXN | 32.8 % | 19.7 | 1 de enero de 2009 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| ABASTECEDORA URUGUAY, S. A. DE C. V. | 2 | 269 MXN | 22.4 % | 63 | 2009 - 2009 |
| JARAMILLO ORTIZ VERONICA | 2 | 1,732.1 MXN | 16 % | 209.6 | 2017 - 2018 |
| MASI CIENTIFICA S.A. DE C.V. | 2 | 949 MXN | 16 % | 172.8 | 2012 - 2014 |
| SAEC, S. A. DE C. V. | 2 | 281.6 MXN | 16 % | 41.6 | 2011 - 2015 |
| DAYEALI, S.A. DE C.V. | 1 | 1,651.2 MXN | 16 % | 256 | 2016 - 2016 |
| FERRETERIA SIEBER, S.A. DE C.V. | 1 | 75.3 MXN | 16 % | 8 | 2010 - 2010 |
Entity type
Articulos de cocina y comedor
Date updated in QQW
3 de octubre de 2022
Source(s)
Part of the project
Organization responsible for the import
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Choose the system where you want to use the data to see the instructions. For research methodology, see the Manual for investigating open contracting.
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=120.736.1567.00")
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=120.736.1567.00')
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=120.736.1567.00')