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Description
Compra Emergente
IMSS product code
060.168.2537.10
Each circle represents one of the 4 purchases of TUBOS made by the IMSS between 2010 and 2011.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Sonora Almacen Delegacional En Sonora | Sonora | 2 | 706.5 MXN | 130.4 MXN | 12.8 % | 2.57 | 18 de octubre de 2011 |
| Delegación Guanajuato | Guanajuato | 1 | 266.8 MXN | 66 MXN | 32.9 % | 3.82 | 13 de mayo de 2010 |
| H. de Especialidades Cardiológicas No. 34, Centro Médico Nacional del Noreste. Umae Cardiologia En Nuevo Leon | Nuevo León | 1 | 2,744.6 MXN | 321.6 MXN | 13.3 % | 18.6 | 22 de octubre de 2010 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| DIAGNOSTICA COMERCIAL, S.A. DE C.V. | 1 | - MXN | - | - | 2011 - 2011 |
| GRUPO MORAVI, S.A. DE C.V. | 1 | 321.6 MXN | 13.3 % | 18.6 | 2010 - 2010 |
| MAYOREO MEDICO DEL NOROESTE, S.A. DE C.V. | 1 | 130.4 MXN | 25.7 % | 2.57 | 2011 - 2011 |
| PROMEDICA GARCIA, S. A. DE C. V. | 1 | 66 MXN | 32.9 % | 3.82 | 2010 - 2010 |
Date updated in QQW
3 de octubre de 2022
Source(s)
Part of the project
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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=060.168.2537.10")
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=060.168.2537.10')
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=060.168.2537.10')