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Description
ROSA EXTENDIDO DE75 GRS. (36 KG.) 4 CARTAS DE43.5 X 57 CMS. PARA IMPRESION EN OFFSET.
Classification
Artículos de consumo. Papeleria
IMSS product code
311.685.1837.00
Each circle represents one of the 5 purchases of PAPEL BOND made by the IMSS between 2009 and 2015.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Sinaloa Almacen Delegacional En Sinaloa | Sinaloa | 4 | 3,446.5 MXN | 751.1 MXN | 27.6 % | 5.51 | 28 de septiembre de 2009 |
| Delegación Michoacán Almacen Delegacional En Michoacan | Michoacán | 1 | 1,120.1 MXN | 154.5 MXN | 16 % | 2.56 | 6 de mayo de 2015 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| SANTOS RIOS JOSE GUADALUPE | 4 | 751.1 MXN | 27.6 % | 5.51 | 2009 - 2009 |
| PAPELERIA MADERO VALLADOLID SA DE CV | 1 | 154.5 MXN | 16 % | 2.56 | 2015 - 2015 |
Entity type
Papeleria
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=311.685.1837.00")
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=311.685.1837.00')
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=311.685.1837.00')