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Description
Compra Emergente
IMSS product code
060.841.0890.02
Each circle represents one of the 6 purchases of SUTURAS made by the IMSS between 2009 and 2010.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Baja California | Baja California | 5 | 9,464.4 MXN | 2,310.9 MXN | 42.5 % | 3.79 | 25 de noviembre de 2010 |
| Delegación Sonora Almacen Delegacional En Sonora | Sonora | 1 | 731.5 MXN | 114.1 MXN | 18.5 % | 0.185 | 10 de julio de 2009 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| MARIA ELENA MORA PEREA | 2 | 1,746.1 MXN | 64.4 % | 2.86 | 2010 - 2010 |
| EQUIPOS MEDICOS DE BAJA CALIFORNIA, S.A. DE C.V. | 1 | - MXN | - | - | 2009 - 2009 |
| ORAN Y ASOCIADOS EQUIPO DE IMAGEN, S.A. DE C.V. | 1 | - MXN | - | - | 2010 - 2010 |
| PROVEEDORA HOSPITALARIA DE AGUA PRIETA S.A DE C.V | 1 | 114.1 MXN | 18.5 % | 0.185 | 2009 - 2009 |
| SALMED DISTRIBUIDORA, S.A. DE C.V. | 1 | 564.9 MXN | 83.4 % | 0.926 | 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=060.841.0890.02")
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=060.841.0890.02')
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=060.841.0890.02')