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Description
MONTADO EN BASE DE MADERA MEDIDAS 25 X 10 CMS
Classification
Artículos de consumo. Utiles de oficina
IMSS product code
312.820.0072.00
Each circle represents one of the 29 purchases of SELLO DE GOMA made by the IMSS between 2009 and 2018.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Baja California Sur Almacen Delegacional En Baja California Sur | Baja California Sur | 9 | 8,876.3 MXN | 2,646.6 MXN | 43.2 % | 21.1 | 17 de diciembre de 2015 |
| Delegación Nayarit Almacen Delegacional En Nayarit | Nayarit | 5 | 1,090.4 MXN | - MXN | - | - | 1 de octubre de 2012 |
| Delegación Sinaloa Almacen Delegacional En Sinaloa | Sinaloa | 4 | 2,195 MXN | 1,039.4 MXN | 101.7 % | 11 | 5 de abril de 2011 |
| Delegación Jalisco Almacen Delegacional En Jalisco | Jalisco | 2 | 4,537.4 MXN | 54.4 MXN | 6.08 % | 0.651 | 1 de enero de 2011 |
| Delegación Michoacán Almacen Delegacional En Michoacan | Michoacán | 2 | 473.6 MXN | 51.2 MXN | 8 % | 0.32 | 3 de abril de 2018 |
| Delegación Sonora Almacen Delegacional En Sonora | Sonora | 2 | 11,386.6 MXN | 2,227.6 MXN | 84.6 % | 17.9 | 25 de abril de 2012 |
| Delegación Yucatán Almacen Delegacional En Yucatan | Yucatán | 2 | 1,146.8 MXN | - MXN | - | - | 29 de abril de 2014 |
| Delegación Guanajuato Almacen Delegacional En Guanajuato | Guanajuato | 1 | 71.7 MXN | - MXN | - | - | 24 de agosto de 2009 |
| Delegación Guerrero Almacen Delegacional En Guerrero | Guerrero | 1 | 3,306 MXN | - MXN | - | - | 20 de agosto de 2012 |
| H. de Gineco Obstetricia Núm. 4 "Dr. Luis Castelazo Ayala" Umae Gineco - Obstetricia No. 4 (d.f. Sur) | Ciudad de México | 1 | 43.7 MXN | - MXN | - | - | 22 de junio de 2009 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| DOMINGUEZ GONZALEZ SEBASTIANA | 9 | 2,646.6 MXN | 43.2 % | 21.1 | 2010 - 2015 |
| CHOZA SANCHEZ SANTIAGO | 3 | 837.7 MXN | 95.1 % | 8.56 | 2010 - 2011 |
| TREVINO CONCHAS MARIA ASUNCION | 3 | - MXN | - | - | 2010 - 2012 |
| COMERCIALIZADORA YIREH, S.A. DE C.V. | 2 | - MXN | - | - | 2012 - 2012 |
| GUZMAN PEREZ MARCELO CLAUDIO | 2 | 51.2 MXN | 8 % | 0.32 | 2009 - 2018 |
| MORALES LOPEZ DAVID GUILLERMO | 2 | 2,227.6 MXN | 84.6 % | 17.9 | 2010 - 2012 |
| OLVERES LANDEROS DAVID | 2 | 54.4 MXN | 6.08 % | 0.651 | 2009 - 2011 |
| BASTO ESTRELLA LIBRADA CONCEPCION | 1 | - MXN | - | - | 2014 - 2014 |
| COMERCIALIZADORA DE PAPEL GODI, S.A. DE C.V. | 1 | - MXN | - | - | 2009 - 2009 |
| GARCIA CASTA?EDA ROSA MARIA | 1 | - MXN | - | - | 2009 - 2009 |
| IMPRESOS Y SELLOS DEL SOL, S.A. | 1 | 201.8 MXN | 121.4 % | 2.43 | 2009 - 2009 |
| LAZARO VILLEGAS CECILIO | 1 | - MXN | - | - | 2010 - 2010 |
| VARGAS MORA JUAN JOSE | 1 | - MXN | - | - | 2012 - 2012 |
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=312.820.0072.00")
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=312.820.0072.00')
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=312.820.0072.00')