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Description
Compra Emergente
IMSS product code
060.463.1473.11
Each circle represents one of the 3 purchases of GUÍAS made by the IMSS between 2010 and 2010.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Sinaloa Almacen Delegacional En Sinaloa | Sinaloa | 1 | 4,485.3 MXN | 3,573 MXN | 391.6 % | 3.92 | 6 de octubre de 2010 |
| Delegación Veracruz Norte Almacen Delegacional En Veracruz Puerto (ext. Bienes Terapeuticos) | Veracruz | 1 | 1,461.6 MXN | - MXN | - | - | 28 de mayo de 2010 |
| Delegación Veracruz Norte | Veracruz | 1 | 1,461.6 MXN | - MXN | - | - | 31 de marzo de 2010 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| PRODUCTOS MEDICOS REGIOMONTANOS, S. A. DE C. V. | 2 | - MXN | - | - | 2010 - 2010 |
| SOLUMEDI, S.A. DE C.V. | 1 | 3,573 MXN | 391.6 % | 3.92 | 2010 - 2010 |
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=060.463.1473.11")
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=060.463.1473.11')
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=060.463.1473.11')