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Description
INVISIBLE 18 MM X 25 M, O 12 MM X 50 M
Classification
Artículos de consumo. Utiles de oficina
IMSS product code
312.205.0416.01
Each circle represents one of the 2 purchases of CINTA ADHESIVA made by the IMSS between 2016 and 2016.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Morelos Almacen Delegacional En Morelos | Morelos | 1 | 278.4 MXN | 195.2 MXN | 234.5 % | 23.4 | 21 de abril de 2016 |
| Oficinas Centrales Ofnas Centrales -reforma- Coordinacion De Abastecimiento | 1 | 3,873.2 MXN | 377.5 MXN | 10.8 % | 45.4 | 28 de julio de 2016 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| MANTENIMIENTO PREVENTIVO Y CORRECTIVO SA DE CV | 1 | 195.2 MXN | 234.5 % | 23.4 | 2016 - 2016 |
| PRODUCCIONES CONTI, S.A. DE C.V. | 1 | 377.5 MXN | 10.8 % | 45.4 | 2016 - 2016 |
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=312.205.0416.01")
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=312.205.0416.01')
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=312.205.0416.01')