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Description
PINZA DE ANTRO TIPO KERRISON HACIA ARRIBA, CORTANTE DE 1MM DE DIAMETRO Y DE 17 CM DE LONGITUD.
IMSS product code
537.702.7049.01
Each circle represents one of the 4 purchases of PINZA made by the IMSS between 2010 and 2018.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Coahuila Almacen Delegacional En Coahuila | Coahuila | 1 | 42,953.1 MXN | 5,924.6 MXN | 16 % | 0.96 | 8 de junio de 2012 |
| Delegación Guanajuato Almacen Delegacional En Guanajuato | Guanajuato | 1 | 11,310 MXN | 1,560 MXN | 16 % | 0.32 | 17 de agosto de 2018 |
| H. de Especialidades No. 14 "Adolfo Ruíz Cortines", Veracruz. Umae Especialidades Veracruz (nte.) | Veracruz | 1 | 9,628 MXN | 1,328 MXN | 16 % | 0.32 | 4 de agosto de 2010 |
| H. de Especialidades Núm 25, Monterrey, N.L. Umae Especialidades Nuevo Leon | Nuevo León | 1 | 12,254.3 MXN | 1,690.3 MXN | 16 % | 0.32 | 12 de octubre de 2011 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| B. BRAUN AESCULAP DE MEXICO, S.A. DE C.V. | 1 | 1,690.3 MXN | 16 % | 0.32 | 2011 - 2011 |
| HIDRO HOSPITAL, S.A. DE C.V. | 1 | 1,328 MXN | 16 % | 0.32 | 2010 - 2010 |
| QUIRURGICA ORTOPEDICA, S. A. DE C. V. | 1 | 1,560 MXN | 16 % | 0.32 | 2018 - 2018 |
| REACTIVOS Y PRODUCTOS QUIMICOS GUERRERO, S.A. C.V. | 1 | 5,924.6 MXN | 16 % | 0.96 | 2012 - 2012 |
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=537.702.7049.01")
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=537.702.7049.01')
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=537.702.7049.01')