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Description
MONTADO EN BASE DE MADERA MEDIDAS 2 X 15 CMS
Classification
Artículos de consumo. Utiles de oficina
IMSS product code
312.820.0056.00
Each circle represents one of the 31 purchases of SELLO DE GOMA made by the IMSS between 2009 and 2016.
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| DOMINGUEZ GONZALEZ SEBASTIANA | 7 | 1,484.4 MXN | 18.3 % | 10 | 2010 - 2013 |
| MORALES LOPEZ DAVID GUILLERMO | 5 | 939.9 MXN | 67 % | 5.55 | 2010 - 2016 |
| COMERCIALIZADORA DE PAPEL GODI, S.A. DE C.V. | 2 | - MXN | - | - | 2009 - 2009 |
| CRUZ MUNGUIA MARTHA OLIVIA | 2 | - MXN | - | - | 2013 - 2013 |
| GARCIA NU?EZ JENIFER | 2 | 5 MXN | 1.48 % | 0.0296 | 2010 - 2010 |
| MENA PENICHE CESAR AUGUSTO | 2 | 35.8 MXN | 8.12 % | 0.325 | 2011 - 2015 |
| OLVERES LANDEROS DAVID | 2 | 81.9 MXN | 8.82 % | 0.882 | 2009 - 2011 |
| SOSA ZAVALA NAYELI GUADALUPE | 2 | 196.7 MXN | 8.82 % | 2.12 | 2009 - 2013 |
| CHOZA SANCHEZ SANTIAGO | 1 | 22.4 MXN | 13.3 % | 0.133 | 2010 - 2010 |
| DELGADO FELIX JAZMIN | 1 | 149.7 MXN | 116.3 % | 1.16 | 2011 - 2011 |
| FLORES OLEA MIREYA DEPURACION JULIO 2011 | 1 | 17.3 MXN | 8.02 % | 0.0891 | 2012 - 2012 |
| GUZMAN BRAVO GELACIO | 1 | - MXN | - | - | 2013 - 2013 |
| HERNANDEZ AGUILAR ANA ERIKA | 1 | 91.9 MXN | 15.8 % | 0.473 | 2012 - 2012 |
| OROZCO ESPARZA LORENA | 1 | - MXN | - | - | 2016 - 2016 |
| YADIRA ESTELA VIDAL TORRES | 1 | 577.5 MXN | 89.8 % | 4.49 | 2011 - 2011 |
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=312.820.0056.00")
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=312.820.0056.00')
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=312.820.0056.00')