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Description
ASA PARA TROMPAS UTERINAS, DE ACERO INOXIDABLE. LONGITUD 200 MM.
IMSS product code
537.089.0328.01
Each circle represents one of the 2 purchases of ASA made by the IMSS between 2009 and 2009.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Baja California Almacen Delegacional En Baja California Norte | Baja California | 2 | 17,321 MXN | 2,041 MXN | 23.8 % | 5.34 | 6 de mayo de 2009 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| ABASTECIMIENTO MEDICO DE HERMOSILLO, S.A. DE C.V. | 1 | 339 MXN | 2.96 % | 0.887 | 2009 - 2009 |
| GONZALEZ FLORES CARLOS ALBERTO | 1 | 1,702 MXN | 44.6 % | 4.46 | 2009 - 2009 |
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=537.089.0328.01")
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=537.089.0328.01')
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=537.089.0328.01')